Noyel Deegayu Namal Bandara Thibbotuwawa B. Sc. Eng ... Deegayu Namal...Noyel Deegayu Namal Bandara Thibbotuwawa B. Sc. Eng. (Hons), M. Phil. Submitted in fulfilment of the requirements

EXPERIMENTAL AND NUMERICAL

INVESTIGATION OF STRAIN-RATE-

DEPENDENT BEHAVIOUR OF KANGAROO

SHOULDER CARTILAGE

Noyel Deegayu Namal Bandara Thibbotuwawa

B. Sc. Eng. (Hons), M. Phil.

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

School of Chemistry, Physics and Mechanical Engineering

Science and Engineering Faculty

Queensland University of Technology

2016

Keywords

Articular cartilage

Kangaroo

Shoulder cartilage

Articular cartilage biomechanics

Strain-rate-dependent behavior

Indentation testing

Porohyperelastic model

Hyperelastic coefficients

Permeability

Pore size

Strain-rate-dependent permeability

Superficial collagen

Proteoglycans

Tissue adaptation

Proteoglycan distribution

Collagen Structure

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage i

Abstract

The smooth functioning of the human shoulder joint is predominantly facilitated by a

thin articular layer called the shoulder cartilage placed between the humerus and

scapula bones. The responses of the shoulder joint to external forces are influenced

by the characteristics of shoulder cartilage, which facilitates the frictionless

movement of the shoulder joint and the distribution of load through a large contact

area to protect bone-ends from high contact stresses. Perhaps due to the relatively

low incidence of shoulder osteoarthritis in the past, only a handful of studies have

focused on identifying the characteristics and behaviour of human shoulder cartilage.

In particular, the dynamic characteristics of shoulder cartilage that are most likely

linked to osteoarthritis development [1, 2] have not been investigated. However, with

the reported increase in the incidence of shoulder osteoarthritis [3, 4], it is crucial to

investigate the behaviour of shoulder cartilage in order to identify the reasons behind

osteoarthritis, to develop better diagnostic strategies, and to engineer joint-specific

cartilage tissues.

Due to the unavailability of human shoulder cartilage samples and ethical

restrictions, kangaroo shoulder cartilage was chosen as the animal model for this

research, considering its anatomical and biomechanical similarities to that of a

human shoulder joint. In addition, the bipedal hopping locomotion of kangaroos

results in their shoulder joint being less loaded than their lower limbs, and this

provides an ideal source for investigating the effect of external loading on cartilage

tissue adaptation and its influence on the tissue’s functional behaviour. Therefore, to

investigate the strain-rate-dependent behaviour of shoulder cartilage tissues in the

present study, comprehensive indentation experiments (ranging from physiologically

ii Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

low (10-4/s) to high (10-2/s) strain-rates) were conducted on kangaroo shoulder

cartilage tissues. A porohyperelastic numerical model with a newly introduced strain-

rate-dependent permeability function was developed to understand the mechanisms

underlying strain-rate-dependent behaviour. Comparison of the porohyperelastic

model with constant, strain-dependent and strain-rate-dependent permeability models

indicated that the rate-dependent fluid flow significantly affects the behaviour of

shoulder cartilage, especially at high strain-rates. Based on the results of this

investigation it was concluded that, in addition to solid–interstitial fluid frictional-

interactions, pressure drag forces and inertia forces also begin to affect the tissue

behaviour at high strain-rates. This assists the tissue to retain fluid and act as a

protective mechanism that reduces excessive deformation of the cartilage at large

strain-rates. The results of sequential enzymatic degradation and indentation tests

indicated that proteoglycan and collagen degradation significantly compromise the

strain-rate-dependent behaviour and that superficial collagen plays a more significant

role than proteoglycans in facilitating the strain-rate-dependent behaviour of

kangaroo shoulder cartilage. Contrary to the results in studies on knee cartilage, the

superficial collagen was found to equally contribute to shoulder cartilage behaviour

at all strain-rates, thus affirming its significance in the mechanical behaviour of

shoulder cartilage.

The comparative compositional, microstructural and biomechanical

experiments showed that the proteoglycan distribution with depth in shoulder and

knee cartilage is different. A distinct, large deep zone was observed in knee cartilage,

while the size of the deep zone in shoulder cartilage was relatively small. The

superficial collagen was identified as the most significant feature in the collagen

network of shoulder cartilage tissue. Contrary to shoulder cartilage, proteoglycans

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage iii

dominated the behaviour of knee cartilage and had a considerably large effect on the

tissue behaviour at low strain-rates while the effect of superficial collagen increased

with an increase in strain-rate. The results indicated that the proteoglycan distribution

and the structural features of the collagen network adapt to external mechanical

stimuli, and hence depend on the local mechanical environment experienced by the

tissue.

Through systematic and in-depth investigation, this study has explored the

mechanisms underlying the strain-rate-dependent behaviour of kangaroo shoulder

cartilage. The findings of this study will help to bridge the existing gaps in

knowledge on the mechanical behaviours of shoulder cartilage tissues and on the

compositional and microstructural adaptation of cartilage tissues to external

mechanical loading. The findings will also help to inform the cartilage modelling

community and tissue engineers about the underlying mechanisms and extracellular

matrix features that need to be considered when modelling and engineering shoulder

cartilage tissues. The experimental strategies employed and the computational model

developed are useful for future studies on cartilage biomechanics, and will inspire

future research investigations to be carried out on shoulder cartilage tissue—an area

that has hitherto lacked attention.

iv Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

List of Publications

Journal articles

• Thibbotuwawa, N., Oloyede, A., Senadeera, W., Li, T., Gu, Y., 2015.

Investigation of the mechanical behavior of kangaroo humeral head cartilage

tissue by a porohyperelastic model based on the strain-rate-dependent

permeability. J Mech Behav Biomed Mater 51, 248-259.

• Thibbotuwawa, N., Oloyede, A., Li, T., Singh, S., Senadeera, W., Gu, Y.,

2015. Physical mechanisms underlying the strain-rate-dependent mechanical

behavior of kangaroo shoulder cartilage. Applied Physics Letters 107,

103701.

• Thibbotuwawa, N., Oloyede, A., Li, T., Singh, S., Senadeera, W., Gu, Y.,

2015. Compositional, Microstructural and Biomechanical differences

between kangaroo shoudler and knee cartilage: Implication on numerical

modelling and tissue engineering stratagies (In preparation).

Refereed conference proceedings and extended abstracts

• Thibbotuwawa, N., Gu, Y.T., Oloyede, A., Senadeera, W., Li, T., 2012.

Finite element shoulder models, In Proceedings of 4th International

Conference on Computational Methods (ICCM 2012).

• Thibbotuwawa, N., Li, T., Gu, Y.T., 2014. Porohyperelastic finite element

model for the kangaroo humeral head cartilage based on experimental study

and the consolidation theory, In Proceedings of 5th International Conference

on Computational Methods (ICCM 2014).

• Thibbotuwawa, N., Oloyede, A., Senadeera, W., Gu, Y.T., 2014.

Hyperelastic Constitutive Relationship for the Strain-Rate Dependent

Behavior of Shoulder and Other Joint Cartilages, The 15th International

Conference on Biomedical Engineering. Springer, pp. 255-258.

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage v

• Thibbotuwawa, N., Oloyede, A., Senadeera, W., Gu, Y.T.,2014. Exploration

of the biomechanical load bearing mechanisms of articular cartilage under

dynamic loading, Proceedings of the 9th Australasian Biomechanics

conference.

vi Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

Table of Contents

Keywords ................................................................................................................................................. i

Abstract .................................................................................................................................................. ii

List of Publications ................................................................................................................................. v

Table of Contents ................................................................................................................................. vii

List of Figures ......................................................................................................................................... x

List of Tables ....................................................................................................................................... xiv

Ethical Clearance for Tissue Use .......................................................................................................... xv

Statement of Original Authorship ........................................................................................................ xvi

Acknowledgement ............................................................................................................................. xviii

CHAPTER 1: INTRODUCTION ....................................................................................................... 1 1.1 Background .................................................................................................................................. 1

1.2 Research problem and questions .................................................................................................. 3

1.3 Research aims and objectives ...................................................................................................... 4

1.4 Research Significance, contribution and scope ............................................................................ 6

1.5 Thesis Outline .............................................................................................................................. 8

1.6 Research framework .................................................................................................................. 10

CHAPTER 2: LITERATURE REVIEW ......................................................................................... 13

2.1 Importance of shoulder joint and shoulder cartilage .................................................................. 13 2.1.1 Shoulder osteoarthritis and causes .................................................................................. 15 2.1.2 Adaptation of cartilage tissues in response to the mechanical environment ................... 18

2.2 Articular cartilage ...................................................................................................................... 20 2.2.1 Articular cartilage proteoglycan ..................................................................................... 21 2.2.2 Articular cartilage collagen ............................................................................................. 22 2.2.3 Articular cartilage structure ............................................................................................ 23 2.2.4 Articular cartilage collagen network architecture ........................................................... 26 2.2.5 Articular cartilage load-bearing unit: Proteoglycan and collagen entrapment ................ 27

2.3 Articular cartilage biomechanics: static and dynamic load-bearing mechanisms ...................... 29 2.3.1 Articular cartilage biomechanics: The structure–function relationship .......................... 34

2.4 Characteristics of shoulder cartilage .......................................................................................... 35

2.5 Biomechanical models of articular cartilage .............................................................................. 37

2.6 Summary and Implications ........................................................................................................ 40

CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY .................................................... 43

3.1 experimental animal model for shoulder cartilage ..................................................................... 43

3.2 Experimental methodologies and materials ............................................................................... 45 3.2.1 Tissue harvesting and preparation .................................................................................. 45 3.2.2 Evaluation of potential thickness measurement methods ............................................... 46 3.2.3 Ultrasound speed in kangaroo shoulder cartilage tissues and thickness

measurement ................................................................................................................... 47 3.2.4 Biomechanical characterisation: Mechanical tests performed on articular

cartilage .......................................................................................................................... 50 3.2.5 Critical evaluation of confined, unconfined and indentation mechanical tests ............... 51 3.2.6 Mechanical testing protocol ............................................................................................ 53

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage vii

3.3 Numerical modelling methodology ........................................................................................... 56 3.3.1 Numerical modelling to investigate the physical mechanisms underlying the

mechanical behaviour of cartilage: Initial model development ...................................... 56 3.3.2 Assessing the suitability of the porohyperelastic model for investigating the solid

and fluid behaviour of cartilage tissues: The preliminary porohyperelastic FE model .............................................................................................................................. 64

3.3.3 Development of force–indentation relationship for the 2-term reduced hyperelastic model .......................................................................................................... 70

CHAPTER 4: EFFECT OF INTERSTITIAL FLUID ON THE STRAIN-RATE-DEPENDENT BEHAVIOUR OF KANGAROO SHOULDER CARTILAGE ...................................................... 75 4.1 Introduction ............................................................................................................................... 75

4.2 Aims and objectives ................................................................................................................... 76

4.3 Hypotheses ................................................................................................................................. 76

4.4 Strain-rate-dependent mechanical behavioUr of kangaroo shoulder cartilage ........................... 76 4.4.1 Tissue stiffness: Piecewise linear regression method ..................................................... 77 4.4.2 Stiffness variation with strain and strain-rate ................................................................. 78 4.4.3 Solid–fluid interaction and its effect on the strain-rate-dependent behaviour ................ 80

4.5 Porohyperelastic field theory for soft biological tissues ............................................................ 81 4.5.1 Porohyperelastic FE model development for indentation test ........................................ 84 4.5.2 Permeability variation with strain-rate ........................................................................... 87

4.6 Extension OF Porohyperelastic Field theory: Strain-rate-dependent permeability function ..... 88 4.6.1 Material parameter identification ................................................................................... 92

4.7 Results and Discussion .............................................................................................................. 92 4.7.1 Biomechanical parameters of kangaroo shoulder cartilage ............................................ 92 4.7.2 Comparison of constant, strain-dependent and strain-rate-dependent model

predictions ...................................................................................................................... 94 4.7.3 Effects of strain-dependent and strain-rate-dependent permeability .............................. 95 4.7.4 Mechanisms underlying the strain-rate-dependent tissue behaviour .............................. 97 4.7.5 Role of cartilage as a protective layer at large strain-rates ............................................. 99 4.7.6 Limitations of the strain-rate-dependent permeability model and possible

improvements to the FE porohyperelastic model ......................................................... 101

4.8 Conclusion and Remarks ......................................................................................................... 103

CHAPTER 5: EFFECT OF PROTEOGLYCAN AND SUPERFICIAL COLLAGEN ON THE STRAIN-RATE-DEPENDENT MECHANICAL BEHAVIOUR OF KANGAROO SHOULDER CARTILAGE ................................................................................................................................... 107 5.1 Introduction ............................................................................................................................. 107

5.2 Aims and Objectives ................................................................................................................ 109

5.3 Hypotheses ............................................................................................................................... 110

5.4 Experimental Methodology ..................................................................................................... 110 5.4.1 Assessment of tissue preservation methods: The PBS-solution at 4 °C vs the

multiple freeze–thaw method ....................................................................................... 111 5.4.2 Proteoglycan, superficial collagen degradation and surface delipidisation .................. 114 5.4.3 Statistical data analysis procedure ................................................................................ 122

5.5 Results and discussion ............................................................................................................. 122 5.5.1 Effect of proteoglycan degradation on strain-rate-dependent behaviour and

mechanical properties ................................................................................................... 124 5.5.2 Effect of superficial collagen degradation on strain-rate-dependent behaviour and

mechanical properties ................................................................................................... 127 5.5.3 Effect of surface phospholipid removal on strain-rate-dependent behaviour and

mechanical properties ................................................................................................... 131 5.5.4 Comparison of the effect of proteoglycan and superficial collagen on strain-rate-

dependent behaviour ..................................................................................................... 133

viiiExperimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

5.5.5 Effect of proteoglycan and superficial collagen degradation on long-term functional load-bearing ability of the tissue .................................................................. 137

5.6 Conclusion and remarks ........................................................................................................... 139

CHAPTER 6: COMPOSITIONAL, MICROSTRUCTURAL AND BIOMECHANICAL DIFFERENCES IN KANGAROO SHOULDER AND KNEE CARTILAGE ............................ 143

6.1 Introduction .............................................................................................................................. 143

6.2 Aims and objectives ................................................................................................................. 144

6.3 Hypothesis ............................................................................................................................... 145

6.4 Methods and materials ............................................................................................................. 145 6.4.1 Cryostat tissue sectioning: Tissue preparation for histological studies ......................... 145 6.4.2 Safranin-O staining protocol ......................................................................................... 146 6.4.3 Proteoglycan quantification: Optical absorbance measurements .................................. 147 6.4.4 Sample preparation for PLM measurements ................................................................. 148 6.4.5 Collagen quantification: PLM measurements ............................................................... 150

6.5 Results and discussion ............................................................................................................. 152 6.5.1 Differences in proteoglycan concentration with depth in knee and shoulder

cartilage ........................................................................................................................ 152 6.5.2 Differences in collagen network of knee and shoulder cartilage .................................. 154 6.5.3 Comparison of strain-rate-dependent mechanical behaviour and biomechanical

properties of knee and shoulder cartilage ..................................................................... 160 6.5.4 Significance and implications for numerical modelling and tissue engineering ........... 166

6.6 Conclusion and remarks ........................................................................................................... 168

CHAPTER 7: CONCLUSIONS ...................................................................................................... 171

7.1 Conclusions .............................................................................................................................. 171

7.2 Limitations ............................................................................................................................... 175

7.3 Future Research Directions ...................................................................................................... 175

BIBLIOGRAPHY ............................................................................................................................. 179

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage ix

List of Figures

Figure 1.1: Research framework ........................................................................................................... 11

Figure 2.1: Parts of the shoulder joint showing the humeral head, scapula, shoulder cartilage, and muscle and tendon structure of the rotator cuff [27]. .................................................... 14

Figure 2.2: Articular cartilage proteoglycan aggregate ......................................................................... 21

Figure 2.3: Collagen triple helix structure and assembly [110]. ........................................................... 23

Figure 2.4: Zonal variation of matrix components in articular cartilage [117] ..................................... 24

Figure 2.5: Complex fibre and proteoglycan molecule arrangement; the proteoglycans are trapped in three dimensional collagen fibre network [125] .................................................. 26

Figure 2.6: (a) Idealised fibre arrangement in articular cartilage – Benninghoff structure; (b) Typical segmental obliquity in collagen fibres observed; (c) Cross-linking and interlocking of collagen fibres facilitated by the segmental obliquity [129] ........................ 27

Figure 2.7 Three-dimensional network of fibres in articular cartilage generated from repeated cross-linking of string elements; (b) The balloons representing proteoglycans packed and constrained in the fibre network; (c) The complete balloon-string model showing upper tension diaphragm of the surface layer and fibre-proteoglycan arrangement [130]. ............................................................................................................... 28

Figure 2.8: The load-bearing functional unit of articular cartilage; the confining forces of the collagen network resist the osmotic swelling pressure of the proteoglycan and give rise to the intrinsic stiffness of the cartilage matrix [134] .................................................... 29

Figure 2.9: (a) Mechanical analogy illustrating the stress-sharing stress-transfer consolidation mechanism; (b) Pore pressure variation, when the articular cartilage is statically loaded, illustrating how the fluid supports the external load [135]. ..................................... 30

Figure 2.10: Extended rheological analogy of cartilage matrix featuring σa, applied stress; kv stiffness of instantaneous spring; di (i=0,1,2,…), length of ith dent; ki (i=1,2,…), stiffness of ith spring; D1, instantaneous damping coefficient for unbound fluid; D2, damping coefficient relating to bound fluid; Di, general damping coefficient of unbound fluid in the dashpot; σeff, solid’s effective stress; Q, permeability coefficient of the matrix; O, active osmotic component [151]. .............................................................. 32

Figure 3.1: (a) 8 mm diameter cartilage sample; (b) Specimen-harvested region (near the central area of the humeral head); (c) Bone was constrained using a stainless steel holder and submerged in physiological (0.15 M) saline solution; (d) Indentation testing on the sample ............................................................................................................ 46

Figure 3.2: (a) Needle probe measurement location in the sample; (b) A typical force–indentation curve during needle probe indentation – The curve is characterised by articular cartilage (AC) surface puncture due to piercing of the cartilage surface; the initial gradient of the curve significantly increases when the cartilage-calcified bone surface is reached ................................................................................................................. 49

Figure 3.3: Plot between ultrasound travel time and kangaroo shoulder cartilage thickness from needle probe measurements; the slope of the curve is the average ultrasound speed in the tissue ........................................................................................................................... 50

Figure 3.4: (a) The model geometry, mesh, boundary condition and loading configuration of the cartilage–bone FE model; (b) Simplified FE model (without the bone) with mesh and boundary conditions – In this model, the bone is replaced by a rigid constraint (indicated by the red line) which restricts the displacement of the bottom plane of the cartilage .......................................................................................................................... 61

Figure 3.5: (a) Stress distribution for cartilage on rigid bone indented to 10% strain; (b) Stress distribution for cartilage on rigid constraint indented to 10% strain; (c) Comparison

x Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

of the numerical model’s result (force on indenter) with the theoretical prediction of Eq. (3.2) and mesh sensitivity data; (d) Comparison of elastic cartilage on rigid bone laminate model results and elastic cartilage-rigid constraint model results with theoretical model results ....................................................................................................... 62

Figure 3.6: (a) Cartilage, indenter geometry (3 mm diameter with 0.1 mm fillet radius at the edge), the mesh, boundary condition and loading configuration based on mechanical testing carried on kangaroo shoulder cartilage samples; (b) Numerical result of elastic cartilage samples indented up to 30% engineering strain; (c) Variation of force on indenter based on mesh element number................................................................ 63

Figure 3.7: Boundary conditions employed in preliminary porohyperelastic FE model ....................... 66

Figure 3.8: Solid skeleton effective stress-strain curve fitted with a piecewise linear curve to extract the solid skeleton material parameters ...................................................................... 68

Figure 3.9: (a) Pore pressure measurements compared with FE model predictions; (b) Creep strain measurements compared with FE model predictions ................................................. 69

Figure 3.10: Mesh sensitivity analysis for (a) pore pressure predictions (b) creep strain prediction .............................................................................................................................. 70

Figure 3.11: Variation of correction factors k1, k2 with sample thickness ............................................ 74

Figure 4.1: Piecewise linear curve fit to nominal stress-nominal strain data ........................................ 77

Figure 4.2 (a) Strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage indicated by nominal stress-strain data; (b) Stiffness variation with strain and strain-rate – Stiffness was calculated by force divided by the indentation area and by displacement divided by the cartilage’s original thickness .................................................. 78

Figure 4.3: (a) Experimental data from 10-2/s of a representative sample fitted to neo-Hookean, Mooney–rivlin and 2-term reduced polynomial incompressible hyperelastic functions; (b) R-squared values indicating the goodness of fit of neo-Hookean, Mooney–rivlin and 2-term reduced polynomial incompressible hyperelastic functions to the experimental data ........................................................................................ 86

Figure 4.4: An exponential function (Eq. 4.19) fitted to Lai and Mow’s (1980) data; (b) Variation of coefficient M with coefficient a is approximated as a second-order polynomial function; (c) Variation of coefficient a with pressure difference (P) approximated as a power function ........................................................................................ 90

Figure 4.5: (a) Re-analysis of Oloyede and Broom’s [149] Variation of pressure difference (P) between the inside and outside of the tissue with strain-rate; (b) Variation of permeability with strain-rate as predicted by Eq. (4.23) ...................................................... 91

Figure 4.6: Comparison of constant, strain-dependent and strain-rate-dependent model prediction to average (n=10) experimental data of the samples tested – (a) Constant permeability; (b) Strain-dependent permeability; (c) Strain-rate-dependent permeability; (d) Model predictions in terms of R-squared (R2) values and the corresponding significant differences among constant, strain-dependent and strain-rate-dependent models at individual strain-rates .................................................................. 95

Figure 4.7: An ideal representation of part of a tissue with pores represented by circles (undeformed) and ellipse (deformed); (a) Constant permeability – Pore volume/effective fluid-flow area does not change; (b) Strain-dependent permeability – Pore volume/effective flow area is reduced due to application of strain (ε); (c) Strain-rate-dependent permeability – Large pressure differences due to suddenly applied load (Tt2<<<Tt1) result in larger drag forces; this will compact the tissue to reduce the pore size (indicated by the red hatched area), creating congestion for fluid particles to move through pores and, therefore, the fluid particles experience a reduction of pore size/effective flow area ............................................................................ 96

Figure 4.8 : Comparison of pore pressure and velocity profiles at 10-2/s – (a) Strain-dependent permeabilty; (b) Strain-rate-dependent permeability; (c) Fluid velocity at the bottom left (point P) of the cartilage matrix ..................................................................................... 98

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage xi

Figure 5.1: (a) Mechanical properties after 72 hrs in PBS-inhibitor solution at 4 °C; (b) Mechanical properties after 1 week in PBS-inhibitor solution at 4 °C ............................... 112

Figure 5.2 : Mechanical property change due to multiple freeze thaw cycles .................................... 113

Figure 5.3: Steps in sequential trypsin treatment (0.05 mg/ml) and mechanical testing on kangaroo shoulder cartilage samples .................................................................................. 115

Figure 5.4: Safranin-O staining of cryosectioned samples harvested from near the central load-bearing area of the humeral head – (a) Untreated sample; (b) 1 hr trypsin-treated sample; (c) 2 hr trypsin-treated sample; (c) 4 hr trypsin-treated sample ............................ 117

Figure 5.5: Steps carried out to investigate the effect of superficial collagen on the strain-rate-dependent behaviour of kangaroo shoulder cartilage ......................................................... 118

Figure 5.6: Safranin-O staining of (a) untreated samples; (b), (c), (d) collagenase-treated samples 1, 2, 3, respectively ............................................................................................... 119

Figure 5.7: (a) Alcian blue 0.1 ml mixed in 1 ml of distilled water (control test); (b) Alcian blue 0.1 ml mixed in the resulting solution after a cartilage sample being digested in 1 ml of 30 U/ml collagenase for 44 hrs; (c) Sample after digesting in collagenase was treated in 1 ml of trypsin–PBS solution (0.05 mg/ml) for 4 hrs and then mixed with 0.1 ml of alcian blue ........................................................................................................... 120

Figure 5.8: Steps carried out to investigate the effect of surface lipids on the mechanical behaviour of kangaroo shoulder cartilage .......................................................................... 121

Figure 5.9 : Effect of mechanical behaviour when (a) normal sample is (b) treated in trypsin (0.05 mg/ml) for 4 hrs, and when (c) normal sample is (d) treated with collagenase (30 U/ml) for 44 hrs, and when (e) normal sample is (f) treated with Folch reagent to remove surface lipids ......................................................................................................... 123

Figure 5.10: Effect of 1 hr, 2 hrs and 4 hrs of trypsin treatment (0.05 mg/ml) on (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-

4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates ....................................................................... 125

Figure 5.11 : Effect of 44 hr collagenase treatment (30 U/ml) on (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates ............................................................................................ 128

Figure 5.12: Effect of surface lipid removal on (a) Young’s modulus; and (b) the nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates ................................................................................................................ 132

Figure 5.13: Effect on average normalised force–indentation curves due to (a) 4 hrs of trypsin (0.05mg/ml) treatment, i.e. proteoglycan completely removed (n=12); (b) 44 hrs of collagenase treatment, i.e. severe disruption to superficial collagen (n=10); and (c) surface phospholipid removal (n=9) .................................................................................. 135

Figure 5.14: Percentage decrease in (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage due to complete removal of proteoglycans (4 hrs of treatment in 0.05 mg/ml trypsin) and severe disruption to superficial collagen (44 hrs of treatment in 30 U/ml collagenase) ........................................................................... 137

Figure 5.15: Variation of pore pressure with strain for 4 hr trypsin-treated and 44 hr collagenase-treated samples ............................................................................................... 138

Figure 6.1: Split line directions identified through the pin-prick test performed on (a) femur; (b) tibia; (c) humeral head; and (d) glenoid of kangaroo knee and shoulder joints ............ 150

Figure 6.2: (a) Variation in proteoglycan concentration (indicated by light absorbance by safranin-O) with depth for samples harvested from four locations of knee cartilage (i.e. lateral femur, medial femur, lateral tibia, medial tibia) and from central humeral head in shoulder joint; (b) Area under absorbance curve, i.e. proteoglycan content in LF, MF, LT, MT and H; (c) LF, MF, LT, MT and H cartilage stained by 0.1% safranin-O indicating the proteoglycan variation with depth ............................................. 153

Figure 6.3: Typical images of cartilage when exposed to polarised light – The dark image at 0° angle corresponds to the cross-polarised configuration; in a sequence of every 45°,

xii Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

bright images are visible indicating the polarised light has been transmitted through the samples; (b) For 0°,90°, 180° and 270° angles, the light transmittance through the samples is literally uniform; (c) For 45°,135°, 225° and 315° angles, the variation in light transmitted through depth corresponds to the zonal arrangement of cartilage fibres (These results are for typical samples harvested from a medial femur of kangaroo knee cartilage) ................................................................................................ 156

Figure 6.4: (a) PLM images obtained from four locations of kangaroo knee (LF, MF, LT and MT) and from the central humeral head; (b) Depth-dependent light transmittance profiles of the samples (i.e. LF, MF, LT, MT and H) ........................................................ 157

Figure 6.5: (a) Confocal image of a typical cartilage sample harvested from the kangaroo humeral head indicating the region (red arrow) near the calcified bone where fibres are perpendicular to the bone – in the same image, near to the top (black arrow), the transition from perpendicular fibres to a random fibre arrangement can be observed; (b) Confocal image enlarged from top region of image (a) indicating random fibre arrangement; (c) Transition from near perpendicular to random fibre arrangement is shown in this enlarged figure taken from the transitional area of image (a) ...................... 159

Figure 6.6: Normalised force vs indentation graphs for: (a) normal and trypsin-treated (in 0.1 mg/ml for 4 hrs) knee cartilage; (b) normal and trypsin-treated (in 0.05 mg/ml for 4 hrs) shoulder cartilage; (c) the effect of complete removal of proteoglycan (due to 0.1/mg/ml trypsin treatment for 4 hrs) on Young’s modulus of kangaroo knee cartilage; (d) Comparison of percentage decrease in Young’s modulus due to complete removal of proteoglycans for kangaroo knee and shoulder cartilage .................. 163

Figure 6.7: Percentage decrease in Young’s modulus after complete proteoglycan-removed samples were treated for 44 hrs in collagenase; (b) Contribution of superficial collagen to tissue behaviour at four strain-rates (10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s) ....... 165

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilagexiii

List of Tables

Table 1.1: Aims and objectives ............................................................................................................... 5

Table 2.1: Pathoanatomical changes in shoulder osteoarthritis [37, 38]. .............................................. 16

Table 3.1: Parameters of the model used for mesh, boundary and loading condition validations ........ 59

Table 3.2: Hyperelastic material parameters and permeability values used for the initial porohyperelastic FE model................................................................................................... 68

Table 5.1: Young’s moduli (MPa) of 4hr trypsin-treated and 44 hr collagenase-treated kangaroo shoulder cartilage at four strain-rates ................................................................. 134

Table 5.2: FE model parameters for normal, 4 hr trypsin-treated and 44 hr collagenase-treated samples ............................................................................................................................... 139

xivExperimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

Ethical Clearance for Tissue Use

The Research Ethics Unit of Queensland University of Technology approved

(approval number is 1200000376) the use of kangaroo shoulder cartilage tissues for

the present research study. The approval was later extended to use kangaroo knee

cartilage as well in the study. The shoulder and knee cartilage tissue samples were

obtained from the same source.

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage xv

QUT Verified Signature

To my beloved Father, Mother, Sister, Brother and Wife.

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilagexvii

Acknowledgement

This thesis has been a one of the most challenging, yet an inspiring experience for

me. During this time, I have been fortunate to work with a number of people, whose

involvement has been instrumental for the success of this research study and hence

their sincere contribution truly needs to be acknowledged. It is my pleasure to

convey my heartfelt gratitude to all of them in this humble acknowledgment.

First and foremost I am greatly thankful to my supervisor, Professor YuanTong

Gu, for his constant support, inspiration and guidance provided during the course of

my PhD study in the School of Chemistry, Physics and Mechanical Engineering

(CPME) at Queensland University of Technology (QUT). I am amazed and

motivated by his affectionate nature, patience and courage and truly grateful for all

the productive discussions we had. His critical insight and academic experience have

been a constant inspiration to me. Without his immense contribution of time, support

and funding, I would not have been able to finish this research study successfully.

Words would not do justice to all the advice, guidance and assistance provided by

him and I am forever grateful to him.

I am thankful and appreciate the guidance provided by my associate

supervisors Professor Kunle Oloyede and Dr. Wijitha Senadeera. Professor

Oloyede’s original research in the field of biomechanics of articular cartilage and his

encouragement for philosophical thinking truly helped me to understand the depth

and value of a PhD study. He greatly helped me to mould my own research path

during the course of my PhD experience. His motivating and encouraging words will

always be remembered. I am grateful to Dr. Senadeera for introducing me to a PhD

opportunity in QUT and continuously encouraging me during my course of study.

xviiiExperimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

While envying his simplicity, affection and openness I will always remember him as

a truly remarkable human being. I am grateful for all his support too.

My heartfelt gratitude goes to QUT and its community as a whole for

providing me with generous funding in addition to space and a friendly environment.

The exposure, experience and relationships that I have accumulated during QUT has

not only helped my professional development but has enabled me to face the future

with a clear mindset and direction. Special thank also goes to the Higher Degree

Research (HDR) supporting team at Science and Engineering Faculty of QUT and

CPME school staff for their immense support in terms of taking care of all the

administrative work related to my PhD study and for been their always to guide

whenever there was an administrative problem.

I would also like to thank Dr. Sanjleena Singh, Mrs. Helen O’Conner, Ms.

Melissa Johnston, Mr. Len Wilcox, Dr. Hayley Moody and Dr. Mark Wellard for the

immense support given, to the best of their capacity, especially for my experimental

studies. Also my special heartiest gratitude goes to each and every colleague in the

Laboratory for Advanced Modelling in Simulation in Engineering and Science

(LAMSES) group for their continuous support and encouraging words. Their

constructive advices have helped me remarkably in carrying out my research and

made my stay at QUT smooth. Special thanks go to Haifei Zhang, Chaminda

Karunasena, Tong Li, Trung Dung Nguyen, Hasitha Nayanajith, Yei Wei, Izzat

Thiyahuddin, Suchitra De Silva and Charith Rathnayaka who are some of my past

and present LAMSES colleague, for their friendship. My heartiest thanks go to Dilini

Galpaya for being a sister to me during my stay in QUT and helping a lot with my

experimental studies and I am also thankful to Helen Whittle for helping me to proof

read my thesis. Special thanks also goes to Sri Lankan student community in QUT

Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilagexix

and the people who I play cricket in every Saturday afternoon, who made my life in

QUT exciting.

Lastly, I am forever grateful to my mother, father, brother and sister for their

constant love, understanding and advices that have not only helped me to grow as a

person but have taught me to define ‘success’ in my own terms in life. Finally, I am

forever grateful to my wife, for all the continuous support given throughout my study

period and for filling my life with love and happiness.

xx Experimental and Numerical Investigation of Strain-rate-dependent Behaviour of Kangaroo Shoulder Cartilage

Chapter 1: Introduction

This chapter first provides an introduction to the research background (Section 1.1)

and research problems (Section 1.2). Then it presents the aims and objectives of this

study (Section 1.3), followed by an outline of the research significance, its

contribution to the field of biomechanics of cartilage tissue, and the research scope

(Section 1.4). Additionally, to provide a better understanding of the content covered

in this thesis, a brief outline of each chapter is included (Section 1.5). In the final

section (Section 1.6), the research framework is presented.

1.1 BACKGROUND

The shoulder joint is the most flexible of all major human joints [5-7]. From object

manipulating to typing and sporting activities, the shoulder joint plays a significant

role in performing a variety of physical activities that are essential for daily human

function. The shoulder joint’s smooth function and flexibility are vital for

individuals’ productivity and efficiency in performing daily activities, and thus are

significant in the human endeavour to lead a quality life. Smooth functioning of the

shoulder joint is predominantly facilitated by a thin articular layer called the shoulder

cartilage that is positioned between the humerus and scapula bones The response of

the shoulder joint to external forces is influenced by the characteristics of the

shoulder cartilage which facilitate the frictionless movement of the shoulder joint [6,

8] and the distribution of load through a large contact area so as to protect bone-ends

from high contact stresses [8, 9].

Flexibility of the shoulder joint comes at the expense of its vulnerability to

injuries and disease. Due to repetitive dislocation, overuse or trauma, the

Chapter 1: Introduction 1

functionality of the shoulder joint may be compromised and lead to degeneration of

its soft tissues [6]. The most prevalent among the potential degenerative changes is

known as arthritis—a complex family of degenerative joint conditions of which the

most common is osteoarthritis [10-12]. High contact stresses on shoulder cartilage

due to trauma and dislocation is known to trigger shoulder osteoarthritis [13], which

degrades the constituents of the tissue and leads to the structural and functional

breakdown of the cartilage. Athletes, wheelchair users and construction workers who

often utilise the shoulders for repetitive load-bearing tasks are the most at risk of

shoulder injuries and eventually of shoulder osteoarthritis development [13].

Osteoarthritis is the most common musculoskeletal joint disorder, affecting the

wellbeing of more than 15-20 million individuals worldwide. After the knee and hip,

the shoulder is the third most common osteoarthritis-affected joint, accounting for

3% of all types of osteoarthritis [14]. Total of 20,000–25,000 semi or total shoulder

arthroplasty procedures have been reported to the Australian Orthopaedic

Association National Joint Replacement Registry (AOANJRR) in the period of 2008

to 2013. This is approximately 5–6% of all joint replacements reported to AOANJRR

[15]. Probably due to the relatively low incidence of shoulder osteoarthritis in the

past, few studies have focused on characterising the behaviour of shoulder cartilage.

In particular, the dynamic characteristics of shoulder cartilage, which are most likely

linked to osteoarthritis development [1, 2], have not been investigated until now. Due

to the growing number of shoulder joint replacements and active participation in

sports among youth, there is now a growing interest in investigating the upper

extremity tissues such as the shoulder cartilage [13, 15].

Biological tissues such as shoulder cartilage are complicated materials which

are naturally designed and adapted to the kinematics and dynamics of the human

2 Chapter 1: Introduction

body. Due to the adaptability of biological structures to mechanical stimuli, it can be

hypothesised that shoulder cartilage is different in composition and structure to lower

limb joint cartilage such as knee cartilage. Until now, scarce research has been

carried out to specifically investigate the adaptation of shoulder cartilage tissues to

the mechanical environment and its biomechanical and functional implications for

cartilage behaviour. Further, it is essential that the compositional and structural

adaptation of cartilage tissues to mechanical loading is known in order to formulate

and regulate strategies to engineer cartilage tissues to specific joints such as the

shoulder. The present study therefore specifically focuses on investigating the

mechanical behaviour of shoulder cartilage and its structure–function relationship.

1.2 RESEARCH PROBLEM AND QUESTIONS

In physical activities, such as lifting and throwing, the shoulder cartilage is subjected

to physiologically different strain-rates [1]. Therefore, the shoulder cartilage should

have the ability to undergo controlled deformation in response to these different

external loading conditions, in order to reduce the risk of bone-to-bone contact in the

joint. Solid–fluid interaction is considered to play a significant role in facilitating this

behaviour of shoulder cartilage tissues. To date, however, there are limited

systematic studies investigating factors affecting the strain-rate-dependent

mechanical behaviour of shoulder cartilage tissues specifically. It is crucial to

understand the extent to which solid–fluid interaction facilitates the strain-rate-

dependent behaviour of shoulder cartilage tissues, in order to identify its implications

on the initiation of shoulder osteoarthritis and the development of artificial shoulder

cartilage tissues.

Differences in the contribution of cartilage constituents, namely, proteoglycans

and the collagen network, to the static and dynamic responses of knee cartilage


tissues have been reported [16, 17]. As mentioned earlier, since biological tissues

adapt to their mechanical environment, it is expected that proteoglycan composition,

proteoglycan distribution and the structural features of the collagen network in

shoulder cartilage and knee cartilage are different. Considering these differences, it is

plausible that the findings of the studies done on knee cartilages are not directly

applicable to shoulder cartilage. Based on the literature review (Chapter 2), the main

research questions that guided this study are as follows:

1) How does the behaviour of fluid under different loading-rates affect the

mechanical behaviour of shoulder cartilage?

2) How do the cartilage constituents (collagen structure and proteoglycans)

affect the mechanical behaviour of shoulder cartilage under different loading-

rates?

3) Are the composition and microstructure of shoulder cartilage distinctly

different from that of knee cartilage? And what are the implications of these

differences for the functional behaviours of shoulder and knee cartilage?

1.3 RESEARCH AIMS AND OBJECTIVES

The main aim of the present study is to comprehensively investigate the factors

affecting the strain-rate-dependent behaviour of shoulder cartilage. Further, it also

aims to establish the fact that, due to adaptation to different mechanical

environments, cartilage tissues (e.g. knee and shoulder cartilage) will demonstrate

functional, microstructural and composition differences. The aims and objectives of

this study are outlined in Table 1.1.


Table 1.1: Aims and objectives Aims Objectives

To investigate the effect of solid–fluid interaction on the strain-rate-dependent mechanical behaviour of shoulder cartilage

• To investigate the significance of the rate-dependent fluid flow on the strain-rate-dependent mechanical behaviour of shoulder cartilage tissue

To investiage the role of cartilage constituents (i.e. proteoglycan and collagen) on the strain-rate-dependent behaviour of shoulder cartilage

• To investigate the role of proteoglycans in the strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage

• To investigate the role of superficial collagen and surface phospholipids in the strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage

• To assess whether proteoglycans or superficial collagen dominate the mechanical behaviour of kangaroo shoulder cartilage

To investigate the compositional, microstructural and biomechanical differences between shoulder and knee cartilage

• To investigate the differences in proteoglycan concentration and distribution in knee and shoulder cartilage

• To investigate the differences in the collagen network in knee and shoulder cartilage

• To investigate the contribution of proteoglycans and superficial collagen to the strain-rate-dependent behaviour of knee cartilage, and compare it with shoulder cartilage


1.4 RESEARCH SIGNIFICANCE, CONTRIBUTION AND SCOPE

Few studies have been conducted to investigate the mechanical behaviours of

shoulder cartilage tissue. This research contributes to the current knowledge by

improving the understanding of the deformation mechanisms underlying the strain-

rate-dependent behaviour of shoulder cartilage tissues. Through systematic

investigation of the factors affecting the strain-rate-dependent behaviour of shoulder

cartilage tissues, the present study informs the cartilage biomechanics and modelling

community about the physical mechanisms that should be considered in the future

modelling of shoulder cartilage tissue. Further, by investigating the effect of the

mechanical environment on depth-dependent proteoglycan concentration and

features of the collagen structure, the present study identifies the factors to be

considered when engineering artificial cartilage for low and high compressive load-

bearing joints such as the shoulder and knee. This has been achieved by analysing

both the load-bearing abilities (at low and high physiological strain-rates) of shoulder

and knee cartilage tissues with respect to the tissue composition and microstructure.

In this study, due to the unavailability of human shoulder cartilage, and due to

anatomical and biomechanical similarities with the human shoulder, kangaroo was

chosen as a model to study shoulder cartilage (as discussed in detail in Chapter 3,

Section 3.1). Through the introduction of kangaroo as a model, this study provides

researchers with a natural source for investigating how the mechanical environment

affects the cartilage tissue composition and structure. Unlike most other animal

models, the kangaroo shoulder joint experiences relatively less force than its knee

joint, similar to the human shoulder joint. Therefore, it is a suitable animal model for

investigating how the mechanical environment and joint differences affect the

structure, composition and function of cartilage tissues. Future research into the


development and degradation of upper and lower extremity joint cartilages using

kangaroo as an animal model would reveal new insights into the some of the area

still unclear about development process [18] of cartilage tissues.

Through the results of this research it has been possible to show that the

contribution of the main cartilage constituents (i.e. proteoglycans and the collagen

network) to strain-rate-dependent behaviour is different in the case of shoulder

cartilage and knee cartilage. It was found that the collagen network was the main

contributor to the behaviour of shoulder cartilage, while the proteoglycans were the

main contributor to the behaviour of knee cartilage. The experimental protocols used

in this study were similar to those in the literature [19-22]; however, to the best of the

author’s knowledge, the experimental approach implemented in the present study has

not been carried out before. In previous studies, numerical models have been used to

investigate the contribution of cartilage constituents to strain-rate-dependent

behaviour of knee cartilage [16]. However, the present study has been able to

experimentally illustrate the effect of the constituents on the strain-rate-dependent

behaviour of shoulder cartilage tissues. The findings of the experiments confirm the

results in the literature [16] on high weight-bearing knee cartilage, and also extend

the knowledge on low weight-bearing shoulder cartilage.

In addition, by thoroughly investigating the effect of fluid behavior on the

strain-rate-dependent behaviour of cartilage tissues, this study demonstrates the

importance of rate-dependent fluid flow in the mechanical behaviour of shoulder

cartilage tissues. The proposed strain-rate-dependent permeability function and the

numerical model will enable future researchers to numerically investigate how rate-

dependent fluid behaviour affects the mechanical behaviours of cartilage tissues.


1.5 THESIS OUTLINE

Chapter 1 of this thesis provided an introduction to the research background

including the research problem and research questions, followed by the aims and

objectives. Subsequently, an overview of the significance of the study and its

contribution to the field of biomechanics of cartilage tissues was provided.

In order to elaborate the motivation, philosophy, rationale and research design

behind the present study, Chapter 2 presents a review of the literature. This includes

a discussion on the importance of studying the shoulder joint by emphasising its

significant role in carrying out daily activities as well as the social and economic

burdens of shoulder osteoarthritis. The chapter then discusses the limited research on

shoulder cartilage tissues and the potential adaptation of articular cartilage tissues to

the local mechanical environment. Next, the structure of the articular cartilage is

presented with an emphasis on the importance of individual constituents and the

structural integrity of constituents in the long-term performance of cartilage. The

stress-processing mechanisms of the articular cartilage are discussed next by

presenting its functional load-bearing unit. This is followed by an elaboration on the

structure–function relationship of articular cartilage and the available cartilage

biomechanical models. Lastly, the chapter summarize the research gaps identified

through literature review.

Chapter 3 discusses in detail the research design and methodology used in the

study to explore the research problem. In so doing, the rationale behind the selected

animal model, tissue harvesting and preparation method, ultrasound thickness

estimation procedures along with the ultrasound speed determination is explained in

detail. In addition, the rationale behind the selected mechanical testing method and

indentation testing protocol is elaborated in detail. The chapter then discusses the


experimental methodology, followed by the numerical methods that elaborate the

model development and validate its suitability for investigating cartilage

biomechanics.

In Chapter 4, the strain-rate-dependent mechanical behaviour of kangaroo

shoulder cartilage is investigated using indentation testing. This chapter also presents

the stiffness variation with strain and strain-rate, followed by a discussion on

possible reasons underlying the observed behaviour. Subsequently, porohyperelastic

field theory is presented and a suitable hyperelastic model for the solid skeleton of

shoulder cartilage tissue is evaluated. Then, the mechanical parameters of kangaroo

shoulder cartilage tissue are compared with the parameters of human shoulder

cartilage reported in the literature. Further, the predictions of the porohyperelastic

cartilage models which includes the existing constant and strain-dependent

permeability models are compared with the experimental results and a new strain-

rate-dependent permeability model is introduced. Lastly, based on the results of the

comparison with the experimental data, the effects of the strain-dependent fluid

behaviour on the strain-rate-dependent behaviour of shoulder cartilage tissues are

discussed in detail.

In Chapter 5, the mechanism underlying strain-rate-dependent behaviour of

shoulder cartilage is further investigated by studying how proteoglycan and

superficial collagen affect the strain-rate-dependent mechanical behaviour of the

tissue. Firstly, tissue preservation methods are evaluated in order to choose a

preservation method for this particular study and then details of the enzymatic

degradation experimental protocols are presented. The effect of proteoglycan and

superficial collagen on the strain-rate-dependent tissue behaviour is discussed next

by evaluating their relative contribution to the mechanical behaviour of the tissue. In


addition, the effect of proteoglycan and collagen degradation on the long-term

functional behaviour of the tissue is discussed using numerical modelling.

Chapter 6 discusses the compositional, microstructural and biomechanical

differences between the kangaroo knee and shoulder cartilage. In so doing, firstly,

the sample preparation procedures, staining protocols, and microscopy and image

processing techniques employed are explained in detail. Then, the differences in

proteoglycan distribution and collagen structure in knee and shoulder cartilage are

discussed, followed by a discussion of their strain-rate-dependent behaviours.

Differences in the contribution of cartilage constituents to the mechanical behaviour

of the two tissues are elaborated next. Implications of the results for the numerical

modelling of cartilage and tissue engineering strategies are further discussed at the

end of the chapter.

Finally, in concluding, Chapter 7 presents the main conclusions of the research

conducted in this study, in addition to the study limitations. This chapter also

discusses future research directions in order to further understand the dynamic load-

bearing mechanisms of cartilage tissues.

1.6 RESEARCH FRAMEWORK

The research framework is presented in Figure 1.1.


Figure 1.1: Research framework

Introduction

Background Research problem

Research aims & objectives

Significance & contribution

Research framework

Litrature review

Introduction Articular cartilage

Shoulder cartilage

Biomechanical models of

articular cartilage

Summary & implications

Research design and methodology

Animal model for shoulder cartilage

Experimental methodology & materials

Numerical modelling methodology

Research schedule

Effect of fluid behaviour on mechanical behaviour of kangaroo shoulder cartilage Development of strain-rate-dependent permeability model Comparison of porohyperelastic model with constant, strain-

dependent, strain-rate-dependent permeability

Research schedule

Effect of collagen structure and proteoglycans on strain-rate-dependent behaviour of kangaroo shoulder cartilage Sequential constituent degradation and mechanical testing Comparison of the effect of constituent degradation on

mechanical properties

Comparison of kangaroo knee and shoulder cartilage Compositional and microstructural differences Contribution of collagen structure and proteoglycans Implications of mechanical behavioural differences between

knee and shoulder cartilage

Conclusions

Conclusion

Future work

4-6

3

2

1

7

Limitations

Articular cartilage biomechanics


Chapter 2: Literature Review

This chapter first explains the importance of investigating the characteristics of

shoulder cartilage (Section 2.1) and then reviews the literature on the articular

cartilage structure, function and its constituents (Section 2.2). Subsequently, the

static and dynamic load-bearing mechanisms of cartilage are reviewed (Section 2.3)

and research studies conducted specifically on shoulder cartilage are summarised

(Section 2.4). The biomechanical models of articular cartilages are thoroughly

reviewed (Section 2.5). Finally, the literature review is summarised and the research

gaps are identified (Section 2.6).

2.1 IMPORTANCE OF SHOULDER JOINT AND SHOULDER CARTILAGE

The shoulder joint is the most mobile joint of all human joints [4, 6]. It has a large

range of motion, more than any other major diarthrodial joint in the human body and

plays a significant role in performing a variety of physical activities essential for

daily human function. Its flexibility, stability and strength are provided by a complex

integration of soft and hard tissues (Figure 2.1). The rotator cuff tendons and

muscles, glenohumeral ligaments, and glenohumeral capsule provide stability and

flexibility to the shoulder joint, while the biceps tendons and muscles are responsible

for assisting the shoulder joint movements [6]. Smooth functioning of the shoulder

joint is predominantly facilitated by a thin articular layer placed between the

humerus and scapula, which is known as shoulder cartilage. The very nature of the

shoulder joint’s response to external forces is influenced by the characteristics of this

cartilage, which helps to distribute contact stresses [23, 24]. This in turn helps to

Chapter 2: Literature Review 13

maintain stability of the shoulder joint by facilitating uniform stress distribution in

the shoulder capsule [6, 25, 26].

Figure 2.1: Parts of the shoulder joint showing the humeral head, scapula, shoulder cartilage, and muscle and tendon structure of the rotator cuff [27].

Healthy long-term function of the shoulder cartilage can be directly or indirectly

influenced by the amount and frequency of the forces it experiences and the proper

function of the shoulder joint’s elements such as the labrum and rotator cuff muscles

[7, 28, 29]. Alterations in the joint’s anatomy or deficiencies in ligamentous and/or

capsular components can cause motion abnormalities and may lead to the

development of high focal contact stresses on the cartilage. High contact stresses can

deteriorate the cartilage tissues and eventually they can be affected by shoulder

osteoarthritis [30-33].

14 Chapter 2: Literature Review

2.1.1 Shoulder osteoarthritis and causes

Osteoarthritis is a degenerative disease that degrades the functional quality of

articular cartilage and eventually results in bone-to-bone contact in joints, leading to

chronic pain and disability [10-12]. It is the most common musculoskeletal joint

disorder accounting for 50% of the musculoskeletal disease burden [10-12]. The

economic and social costs of osteoarthritis are unprecedented, with Australia

spending nearly 5-billion Australian dollars per year for arthritis related health costs

in 2007. In terms of total financial costs (when productivity costs and other indirect

costs are accounted) this value mounts to more than 20-billion [34]. Osteoarthritis is

affecting nearly 15–20 million individuals worldwide [10-12] and is projected to

increase from three million to as many as one in four Australians by 2040 [35, 36] .

Osteoarthritis can be classified as primary or secondary osteoarthritis. Primary

osteoarthritis occurs without any predisposed reason and is known to be triggered by

aging, while secondary osteoarthritis occurs due to injuries, obesity, inactivity or

other similar causes [1, 2]. Due to the limited capacity of cartilage to repair, and its

aneural, alymphatic and avascular nature, if cartilage damage is of unmanageable

size, there is a greater possibility of an onset of tissue degeneration and eventual

osteoarthritis development.

Osteoarthritis in the shoulder joint accounts for 3% of all osteoarthritis and it

is also the third most common osteoarthritis-affected joint after the knee and hip

[14]. Degenerative changes, irregularities, delamination and eventual cartilage loss

will affect movement in the shoulder cartilage (i.e. roughness and stiffness on

movement will increase) and may additionally result in joint instability [37]. The

most common anatomical degenerative changes due to shoulder osteoarthritis are

contracture of the anterior aspect of the capsule, posterior shoulder subluxation, and


central and proximal wear of the articular cartilage of the humeral head [37, 38].

Details of the pathoanatomical degenerative changes in the shoulder joint due to

osteoarthritis are listed in Table 2.1.

Table 2.1: Pathoanatomical changes in shoulder osteoarthritis [37, 38]. Anatomical location or

position Pathoanatomical change

Humeral head

• Central cartilage erosion and flattening

• Central and superior sclerosis

• Peripheral osteophytes, especially inferiorly

• Subchondral bone cysts

Glenoid

• Cartilage loss, especially centrally and

posteriorly

• Sclerosis

• Peripheral osteophytes, especially along the

inferior border

• Subchondral bone cysts

Resting joint position • Posterior joint subluxation

Shoulder joint capsule • Anterior contracture

• Inferior enlargement

Shoulder osteoarthritis can occur due to initial traumatic events or associated

rotator cuff tears [39, 40]. It can also occur due to recurrent instability and

misalignments because of anterior dislocation and reduction, or repetitive

subluxation; all of which result in abnormally large compressions on the shoulder

cartilage [40, 41]. The population affected by shoulder osteoarthritis due to

instability in the shoulder joint is normally young and active [39]. Some patients with

shoulder instability have been diagnosed with post-operatively-developed shoulder

osteoarthritis [39, 42]. Studies also report that shoulder osteoarthritis occurs in

manual wheelchair users, athletes and construction workers [43-46]. Athletes such as


weightlifters, baseball players and racquet sports athletes are more likely to develop

shoulder osteoarthritis [40, 47], mainly due to loads and load distribution patterns on

the shoulder cartilage during dynamic movements of their shoulder [48, 49]. For

instance, there is a reported incidence of osteoarthritis as high as 33% among older

tennis players, which is higher than age-matched control subjects [50]. Studies also

report that repetitive tasks such as lifting may increase the possibility of osteoarthritis

occurrence in the shoulder [51, 52].

Non-surgical interventions such as medication and low weight-bearing

exercises are the first steps to relieve the pain, discomfort and immobility caused by

shoulder osteoarthritis [53-55]. If these treatments are proven unsuccessful, and if the

disease has reached a severe stage, then joint arthroplasty can be considered as an

option [55, 56]. However, with time, arthroplasty is known to cause problems such

as the loosening and wear of the artificial implants [53, 57]. Additionally, longevity

of shoulder implants is reported to be low compared to arthoplasty in hip and knee

[58-60]. The component radiolucency at a 12 year follow up can be high as 89% with

44% been definitive loosening of the implant [54, 60]. Further, shoulder arthoplasty

in younger and active patients has not been highly successful [61, 62]. Nevertheless,

efforts to improve the arthroplasty implants and surgical procedures are ongoing.

Surgical procedures for osteoarthritis treatment such as joint resurfacing

(involving abrasion, drilling, debridement techniques, microfracture techniques or

arthroscopic shaving) and biological auto-grafts are found to be unsatisfactory in the

long run because the fibrocartilages formed using these techniques are mechanically

inadequate to support the joint function in the long-term [63-66]. Joint cartilage

tissues affected by injuries are treated by autologous chondrocyte transplantation

with a considerable success rate in the knee [67, 68] and specific treatment


procedures for focal chondral defects in knee is well established [69, 70]. Shoulder

chondral defects are rarely reported and discovers several years after the original

incident when shoulder complications surface [13, 71]. Autologous chondrocyte

transplantation is relatively new for focal chondral defects in shoulder [71-73].

Nevertheless this treatment method has been reported ( 3 years and 9 years follow up

study) to be considerably successful with more than 90% of patients does not

requiring further treatment and surgery after the treatment [72, 74].

Considerable amount of research has also focused on bio-regenerative

approaches including the promotion of native tissue generation and biocompatible

artificial tissue generation [66]. Even though these efforts are successful to an extent,

matching the mechanical properties of native tissues and simultaneously ensuring

functionality in vivo remains a significant challenge [75-78]. Most research on

cartilage is conducted on knee and hip cartilages and, especially in the field of

cartilage biomechanics, research on shoulder cartilage is limited [79]. Most tissue

engineering efforts are also focused on repairing or engineering knee cartilage

tissues, probably due to the relatively lower occurrence of shoulder osteoarthritis

[14]. However, the facts mentioned earlier and the report by the Australian

orthopaedic association (AOA) that from 2008 to the beginning of 2014 there is

steady increase in the number of shoulder replacement imply the significant need to

carry out specific research on shoulder cartilage [15].

2.1.2 Adaptation of cartilage tissues in response to the mechanical environment

Kinematics and dynamics are important factors in regulating the composition,

microstructure and mechanical properties of biological tissues [80-84]. During

human development from childhood to maturity, the lower and upper extremity

joints undergo forces which are significantly different in magnitude and mode


(section 6.1). In addition, the upper extremity joints have different functional

requirements compared to the lower extremity joints, and hence are different in terms

of the anatomy and biomechanics [85]. The mechanical properties and the potential

material behaviour of cartilage tissues are regulated by the magnitude and mode

(compressive, tensile and shear) of the force experienced by individual joints. There

is evidence to suggest that the properties of cartilage tissue vary significantly from

one joint to another [86]. In this regard, the shoulder joint is subject to forces which

are significantly different in magnitude and mode compared to the lower extremity

joints such as the knee. Hence, it is believed that the shoulder cartilage possesses

properties and characteristics which are unique to it.

The majority of investigations on cartilage tissues have focused on

investigating the mechanical behaviour, microstructure and composition of lower

extremity cartilage tissues such as the tissues in the knee and hip. There are only a

few investigations that have specifically focused on mechanical behavior of upper

extremity cartilage tissues such as the shoulder cartilage (In section 2.4 studies on

mechanical behavior of cartilage tissues are summarized). Although not primarily a

weight-bearing joint, in daily work and sports activities that involve grasping, lifting

or throwing, the shoulder undergoes a variety of static and dynamic loads. The

highest static reaction force experienced by the shoulder joint is 44–90% of the body

weight during arm elevation of 60°–100°, with shear forces being almost 50% of

body weight at 60° of abduction [87-90]. During 30°–90° abduction and 60°–90°

external rotations, the resulting articular contact pressure is reported to be in the

range of 2.2–5.1 MPa [31]. However, under dynamic loading, depending on the arm

position and velocity, the joints can experience 2 to 3 times loading than under static

loading conditions [91, 92]. For example, during a throwing movement in adults and


professional baseball pitchers, compressive/distraction forces of 108% of body

weight and external rotational torques (causing shear stresses) in the range of 67–

92 Nm are generated [1, 93, 94]. For non-athletes and youth, these values can be 40–

50% lower [1]. The shoulder joint of a young baseball pitcher can experience

compressive/distraction forces of 49.8±8.3% (214.7±47.2N) of body weight and

external rotational torques up to 17.7±3.5 Nm [95]. Considering these facts and

based on the underlying philosophy that cartilage adapts based on external

mechanical stimuli, the present study investigates the mechanical properties and

material behaviour of shoulder cartilage under various loading-rates with the

objective of relating the mechanical behaviour of shoulder cartilage to its structure

and composition. The following sections elaborate on the general articular cartilage

structure, composition and function based on the findings reported in the literature.

2.2 ARTICULAR CARTILAGE

Diarthrodial joints experience a variety of mechanical loads under a range of

physiological loading-rates during daily activities. Articular cartilage, which is a thin

translucent tissue found at the bone ends of an diarthrodial joints, is predominantly a

mechanical biological tissue that has the ability to endure a lifetime of compression,

tension and shear forces at a variety of loading-rates, without any significant damage

to the tissue [96, 97]. Its superior mechanical properties and behaviour are due to the

structural organisation and properties of its constituents: water, a three-dimensional

collagen network and negatively-charged, highly-hydrated proteoglycan

macromolecules [98]. By composition, collagen and proteoglycan account for 30%

and 10% of the cartilage’s wet weight, while the water content ranges from 70–80%

of which 4–5% is bound water [99-101].


2.2.1 Articular cartilage proteoglycan

Proteoglycans are glycosylated proteins which are synthesised by eukaryotic

cells. They are found in almost all mammalian tissues in diverse structures and

composition, depending on the specific biological and mechanical function of the

tissue [102, 103]. Aggrecan, the main proteoglycan of the cartilage, is also the

largest proteoglycan in all biological tissues [104] , consisting of a hyaluronic acid

core bonded to aggrecan monomers. Aggrecan monomers are brush-like structures

with glycosaminoglycans (chondroitin sulfate and keratan sulfate) side chains

attached to the hyaluronic acid core protein (Figure 2.2). Aggrecan has

approximately 150 glycosaminoglycan chains attached to the core protein, which is

the highest among all proteoglycans. [102, 104, 105].

Figure 2.2: Articular cartilage proteoglycan aggregate

The physical and biological characteristics of proteoglycans are governed by

the physiochemical nature and structure of glycosaminoglycan chains and the core


protein. Glycosaminoglycans in cartilage, such as chondroitin sulfate, carry a high

negative charge and hence attract positively-charged ions and water molecules. This

accounts for unique swelling properties of cartilage, and hence its resilience to

compressive forces [100, 106]. Therefore, normal cartilage function is significantly

affected by the size of the proteoglycans, the number of glycosaminoglycan side

chains, and the concentration of proteoglycan aggregates [99, 107]. Osteoarthritis is

frequently characterised by the functional compromise of its aggrecan due to

cleavage of the glycosaminoglycan side chains or hyaluronic core protein. This

reduces the size of aggrecan, its water attraction ability, and its ability to aggregate

with other aggrecan [108]. Proteoglycan aggregates impede fluid flow when an

external load is applied on the tissue, resulting in the immediate rise of fluid pressure

and its gradual reduction with time when the water flows out. The rate of fluid flow

is controlled by the ability of the proteoglycan aggregates to impede flow, which

affects the compressive load-bearing ability of the tissue [109].

2.2.2 Articular cartilage collagen

Collagen is the building block of the supporting structure of the cartilage

extracellular matrix where the proteoglycan gel and other cartilage constituents

remain constrained. It accounts for two-thirds of the dry weight of adult cartilage

tissues. Collagen fibres are responsible for the tensile strength of the cartilage and,

together with proteoglycans, form an integrated tissue matrix [98]. Secreted by

articular cartilage cells, collagen-II accounts for more than 90% of all collagens

while the rest of the collagens are type XI (~3%) and IX (~1%). The typical triple-

helix structure of the collagen-II molecule is formed by three polypeptide α-chains

twisted in three directions. Collagen-II molecules bundle together in repeated

structures, 67 nm apart, to form collagen fibrils (Figure 2.3).


Figure 2.3: Collagen triple helix structure and assembly [110].

Collagen fibres are formed by assembling parallel collagen-II fibrils

surrounding a collagen-XI fibril and an outer layer of collagen-IX fibrils. Collagen

fibres are 30–80nm in diameter and approximately 100 nm apart within the

extracellular matrix [111]. Intra and inter-molecular cross-links between the fibril

and collagen network considerably contribute to the mechanical properties of the

cartilage matrix [112, 113]. Therefore, cross-linking molecules such as families of

matrilins and small leucine-rich proteins play an important role in maintaining the

mechanical integrity of cartilage tissues. Cross-linking not only imparts cohesive

strength to the tissue matrix but also helps to constrain the swelling of proteoglycans

in the extracellular matrix. There is evidence that proteins such as decorin and

matrilin together also link the collagen fibre network and proteoglycans [106, 111,

113].

2.2.3 Articular cartilage structure

Health of the cartilage is maintained by equilibrium between the rate of synthesis and

rate of degradation of the extracellular matrix components by articular cartilage cells


called “chondrocytes” [114-116]. Chondrocytes continuously synthesise

proteoglycans and collagens that are soaked in a physiological liquid environment

consisting mainly of water and mobile ions (Na+ and Cl- mostly). The concentration,

orientation and shape of the chondrocytes vary with the depth of the tissue, with the

highest concentration found in the surface layer. Chondrocytes found in the surface

layer are flat-horizontal in shape, while in the middle zone they are round shaped

(Figure 2.4).

Figure 2.4: Zonal variation of matrix components in articular cartilage [117]

In the deep zone, near to the tide mark, cells become vertically oriented, following

the direction of collagen fibres with the depth. Arguably, the depth-dependent

variation of chondrocytes and collagen structure is linked to the mechanical

environment, with high compressive load-bearing areas having a high cell volume to

synthesise more proteoglycans [109, 118]. The skeleton of the cartilage tissues,

which is arguably the collagen network, has a very low biological turnover. It is

responsible for the tensile strength of the cartilage, while cross-linking in the


collagen structure provides cohesive strength to the tissue [119]. Based on the

arrangement of fibres in the surface and deep zone, the cartilage matrix is often

classified into different zones (Figure 2.4). In the superficial zone or surface zone,

the collagen fibres are predominantly parallel to the articular cartilage surface. The

parallel fibre arrangement transits to a random arrangement in the transition zone and

runs radially in the deep zone, anchoring perpendicular to the tidemark in the

calcified zone near the subchondral bone [120].

Proteoglycan concentration has been also found to vary with the depth of the

cartilage [121, 122]. The reported typical variation in the concentration of

proteoglycans with cartilage depth is a skewed bell shape distribution with an

increase in concentration from a low value in the superficial zone to a maximum

value around the deep zone, followed by a decrease nearer to the tidemark. The high

affinity of proteoglycans to water and the proteoglycan-collagen interaction create a

three-component gel-like structure wherein the collagen structure with the

interconnected network constrains the swelling of hydrated proteoglycans (Figure

2.5). Arguably, the zonal architecture and proteoglycan distribution with depth

protect the chondrocytes from being damaged by external loads. For example, in the

early stages of osteoarthritis when proteoglycan levels have been observed to

decrease, the chondrocytes respond by increasing the synthesis of proteoglycans to

repair the tissue [123]. However, if further degradation occurs, especially affecting

the collagen network, the chondrocytes may fail to repair the tissue further. Thereby,

the tissue may become functionally incapable of responding to external loads and

that may lead to chondrocyte damage and eventual osteoarthritis [124].


Figure 2.5: Complex fibre and proteoglycan molecule arrangement; the proteoglycans are trapped in three dimensional collagen fibre network [125]

2.2.4 Articular cartilage collagen network architecture

The specialised collagen architecture of the articular cartilage significantly affects

the mechanical behaviour of cartilage tissues and is responsible for proteoglycan

entrapment. The current structural models of cartilage’s collagen architecture depict

an arcade-like structure (Figure 2.6(a)), where the collagens are parallel to the

cartilage surface [126]. The parallel collagen fibres change to a radial arrangement

in the deep layers of the cartilage and anchor perpendicular to the subchondral bone

[127, 128]. At the ultrastructural level, fibrils deviate from the radial direction

repeatedly in short ranges to form segmental obliquity (Figure 2.6(b)). Segmental

obliquity facilitates collagen cross-linking to form an interlocking collagen structure

that gives rise to a highly efficient entrapment system that enables the cartilage

matrix to contain swelling proteoglycans (Figure 2.6(c)). The degree of obliquity and


the number of collagen fibre interactions determine the amount of constraint on

proteoglycans and their swelling potential, which in turn is responsible for the load-

carriage properties of the cartilage [98, 119].

Figure 2.6: (a) Idealised fibre arrangement in articular cartilage – Benninghoff structure; (b) Typical segmental obliquity in collagen fibres observed; (c) Cross-linking and interlocking of collagen fibres facilitated by the segmental obliquity [129]

2.2.5 Articular cartilage load-bearing unit: Proteoglycan and collagen entrapment

The structure of the articular cartilage can be physically represented by the balloon-

string model of Broom and Marra [130] (Figure 2.7). Highly-packed, hydrated

proteoglycan aggregate macromolecules (Figure 2.7(b)) experience repulsive forces

due to proteoglycan–proteoglycan interaction and are constrained by the cross-linked

collagen meshwork (Figure 2.7(a)).


Figure 2.7 Three-dimensional network of fibres in articular cartilage generated from repeated cross-linking of string elements; (b) The balloons representing proteoglycans packed and constrained in the fibre network; (c) The complete balloon-string model showing upper tension diaphragm of the surface layer and fibre-proteoglycan arrangement [130].

The articular cartilage’s load-bearing functional unit is this system of entrapped

fluid-swollen proteoglycan molecules and the cross-linked collagen meshwork

(Figure 2.8). The negative charge in proteoglycan aggregates is neutralised by mobile

ions in the solution; and, due to the imbalance of mobile ion distribution, an osmotic

pressure is generated [98]. Due to the osmotic pressure, the cartilage swells and

enters a pre-stress state (Figure 2.8), enhancing its compressive load-bearing capacity

[98, 131]. The collagen fibres are predominantly tension-resisting structures, while

proteoglycans are highly deformable under direct compression. However, due to the

structural arrangement, these constituents together form a functional load-bearing

unit that can withstand a wide range of loading (Figures 2.7(c) and 2.8). Although

cartilage is mostly known as a compressive load-bearing structure, it cannot function

without the intrinsic strength of the matrix [98, 106]. Experiments have shown that a

reduction in fibre connections and removal of glycosaminoglycan tend to reduce the

compressive load-bearing ability [132, 133]. Therefore, this integrated system of

fibres and hydrated macromolecules is essential to create an efficient compression-

resisting system [98] that can enable cartilage to bear external loads.


Figure 2.8: The load-bearing functional unit of articular cartilage; the confining forces of the collagen network resist the osmotic swelling pressure of the proteoglycan and give rise to the intrinsic stiffness of the cartilage matrix [134]

2.3 ARTICULAR CARTILAGE BIOMECHANICS: STATIC AND DYNAMIC LOAD-BEARING MECHANISMS

Under static loading, the fluid inside the cartilage initially bears the stress (Figure

2.9(a)) which develops a hydrostatic excess pore pressure over and above the

osmotic pressure. Then, the pore pressure reaches a maximum value (Figure 2.9(b)).

However, as deformation progresses, the pores in the proteoglycan-entrapped

collagen structure close and this reduces the tissue’s permeability [135, 136]. The

increased resistance to flow, caused by pore closure, not only reduces the fluid

pressure but also gradually transfers the stress to the collagen meshwork (Figures

2.9(a) and (b)). The tissue’s deformation eventually stops when the solid skeleton is

able to fully resist the externally applied load. This stress-sharing and stress-transfer

mechanism is called “consolidation” and is also observed in porous materials such as

clay and soil [135].


Figure 2.9: (a) Mechanical analogy illustrating the stress-sharing stress-transfer consolidation mechanism; (b) Pore pressure variation, when the articular cartilage is statically loaded, illustrating how the fluid supports the external load, data adapted from [135].

Although cartilage can be considered as a compressive load-bearing tissue, in

vivo, the compression is localised; hence, the surrounding tissue is additionally

subjected to tension. Therefore, arguably, mechanical indentation tests are

physiologically close to the loading experienced by tissue in vivo, and hence were

used for experimentations in the present study. Acknowledging the stress-sharing and

stress-transfer mechanism, the tension-resisting superficial collagen fibres also

influence the tissue behaviour during indentation [137, 138]. However, in confined

compressions, arguably, superficial collagen does not significantly contribute to the

load-bearing function as there are no significant tensile stresses in the superficial

cartilage layer. Nonetheless, depth-dependent proteoglycan variation is known to


contribute to the load-bearing ability of tissue under both confined and unconfined

compression [139, 140].

Although the mechanisms underlying the static load-bearing of cartilage are

well understood, deformation mechanisms under different loading-rates and dynamic

loading are still under investigation [16, 79]. This is due to the difficulty of

monitoring time-dependent internal tissue behaviour under varying external loads.

Evidence in the literature indicates that the mechanical behaviour of articular

cartilage is strain-rate-dependent [16, 141-149]. According to experimental findings,

with increasing strain-rate, the stiffness of cartilage increases at the beginning and

then it approaches an asymptotic value [141, 142, 150] . The interplay between solid

and interstitial fluid contributes significantly to this behaviour, with 70%–80% of the

load being supported by the matrix at low strain-rates (10-4/s) [149], while the fluid

contributes to a similar percentage at moderately large strain-rates (10-2/s) [144, 149].

In order to explain the strain-rate-dependent behaviour of cartilage tissue, a

rheological model (Figure 2.10) has been proposed, with springs demonstrating the

progressive stiffening behaviour of the tissue with deformation [142, 151]. During

deformation, the articular cartilage exudes water out of the matrix. The rate of water

exudation is controlled by the tissue permeability. This role of water in the

deformation process is represented by a special fluid dashpot, Q, in Figure 2.10.

Immediately after applying the load, the dashpot is set in motion and the fluid is

exuded out of the matrix due to the increase in pressure difference. Dashpots D1 and

D2 model the frictional drag due to interaction between the fluid and solid

components during deformation. It is believed that when the strain-rate is increased,

the fluid exudation from the matrix becomes increasingly difficult due to the drag

forces [142].


Figure 2.10: Extended rheological analogy of cartilage matrix featuring σa, applied stress; kv stiffness of instantaneous spring; di (i=0,1,2,…), length of ith dent; ki (i=1,2,…), stiffness of ith spring; D1, instantaneous damping coefficient for unbound fluid; D2, damping coefficient relating to bound fluid; Di, general damping coefficient of unbound fluid in the dashpot; σeff, solid’s effective stress; Q, permeability coefficient of the matrix; O, active osmotic component [151].

Although it is known that solid–interstitial fluid interaction affects the cartilage

behaviour significantly, detailed investigations about its effect on the strain-rate-

dependent behaviour of shoulder cartilage are limited [79]. In particular, there are no

reported studies in the literature on the significant or insignificant nature of the

strain-rate-dependent fluid flow in regard to cartilage deformation behaviour.

Although studies [145, 149] suggest that the loading velocity affects the fluid

behaviour inside the tissue, scarce research has investigated the effect of loading-


rate dependent fluid behavior mechanical behavior of shoulder cartilage tissues.

Further, Oloyede and Broom [149] reported that the relationship between the

effective-matrix-stress and the pore pressure changes considerably when the strain-

rate is increased from 10-3/s to 10-2/s. They found a fundamental change in the

deformation mechanism when the strain-rate increased and claimed that this could be

due to fluid being locked/contained inside the tissue with the increase of loading

velocity. Based on these facts, it is anticipated that drag forces introduced by the

reduction of permeability and solid–interstitial fluid frictional interactions largely

contribute to the strain-rate-dependent behaviour and that the locking effect is mainly

due to the pressure drag forces and possibly inertia forces affecting the tissue

behaviour.

In addition, it has been stated that flow-independent matrix viscoelasticity

affects the strain-rate-dependent behaviour of cartilage tissue. For instance,

DiSilvestro and Zhu [146], investigated tissue behaviour from 10-2/s to 10-4/s and

stated that viscoelasticity governs the tissue behaviour at high strain-rates, while

fluid flow affects the tissue behaviour at low strain-rates. Although there is

experimental evidence for flow-independent viscoelasticity [152-154], the question

of whether the cartilage matrix truly possesses viscoelasticity is subject to ongoing

investigation [155, 156]. The effect of superficial collagen and flow-independent and

flow-dependent viscoelastic mechanisms in combination is also postulated to affect

the indentation tissue behaviour at large strain-rates [156]. On the other hand, direct

fluid pressure measurements inside the cartilage have shown that flow-dependent

drag forces mainly govern the apparent viscoelastic response of cartilage under

dynamic loading [157].


2.3.1 Articular cartilage biomechanics: The structure–function relationship

Acknowledging that the collagen network’s structure and depth-dependent

proteoglycan distribution are the result of the mechanical environment to which the

tissue is subject, we believe that tissue composition and structure have a significant

effect on the tissue behaviour. For example, the dynamic properties of cartilage

(extracted at high strain-rates) are considered to be governed by the collagen network

structure [20, 158]. Taking into consideration the cartilage structure and its

composition, Julkunen et al.’s [16] finite element (FE) model has shown that the

superficial collagen can considerably affect the tissue behaviour at high strain-rates.

Further, during fast loading, the collagen meshwork is shown to limit the shape

changes of the cartilage in unconfined compression [159]. In contrast, the

equilibrium properties of cartilage (extracted at very low strain-rates) are mainly

affected by proteoglycans [17, 20]. Similarly, proteoglycan concentration has been

found to correlate to the equilibrium properties of articular cartilage [160-162].

Chondrocytes dynamically synthesise the extracellular matrix (i.e.

proteoglycans and collagen) based on the external loading stimuli they receive [163-

165]. Therefore, proteoglycan composition and the structural features of the collagen

network may adapt to external mechanical stimuli, and hence may depend on the

local mechanical environment of the tissue [86, 166-171]. The proteoglycan content

of knee cartilage that bears high compressive loads is anticipated to be higher than

the proteoglycan content of shoulder cartilage that experiences low compressive

loads [168, 172, 173]. In addition, there may be differences in the distribution of

depth-dependent proteoglycan concentration and the features of the collagen

network. However, the studies that have investigated the structure–function


relationship of cartilage have predominantly focused on knee cartilage [16, 17, 20,

158].

Given the potential differences in composition and microstructure, it is highly

possible that the conclusions drawn for the structure-function relationship of knee

cartilage tissues may not be directly applicable to shoulder cartilage tissues. While

systematically investigating the mechanisms underlying the strain-rate-dependent

mechanical behaviour of shoulder cartilage, this study also investigates how the

structural features of the shoulder cartilage affect its strain-rate-dependent

mechanical behaviour. This will help to comprehensively understand the underlying

factors affecting the strain-rate-dependent behaviour of shoulder cartilage. Before

proceeding to investigate the shoulder cartilage, it was crucial to review the previous

studies conducted specifically on shoulder cartilage. These findings are summarised

in the following section.

2.4 CHARACTERISTICS OF SHOULDER CARTILAGE

Using stereophotogrammetric studies, the thicknesses of the humeral head cartilage

and glenoid cartilage are found to be 1.5–2 mm and 2–4 mm, respectively [8, 174].

Magnetic resonance imaging (MRI) and ultrasound studies have also shown that the

shoulder cartilage is thicker in the central part of the humeral head while it is thickest

in the periphery of the glenoid [175]

Cohen and Lai [176], Mow and Bigliani [28] and Huang and Stankiewicz [177]

are the only researchers who have investigated the mechanical behavior and

properties of shoulder cartilage tissue. The compressive properties such as the

aggregate modulus obtained in these studies have not shown any statistically

significant difference within or between the glenoid and humeral head cartilages [28,

177]: for humeral head cartilage, the Young’s modulus reported by Cohen and Lai


[176] and the aggregate modulus reported by Mow and Bigliani [28] and Huang and

Stankiewicz [177] are 0.46 MPa, 0.63-0.77MPa and 0.15MPa, respectively. The

tensile modulus of humeral head cartilage is reported to be significantly higher than

its compressive modulus, and is in the range of 4.23–5.81 MPa [178]. This is one of

the characteristics, known as tension–compression nonlinearity [179, 180], which

significantly affect the mechanical behaviour of cartilage tissues. Tension–

compression nonlinearity stems from the tension-resistive superficial collagen fibres

which impart a higher tensile modulus on the tissue compared to its compressive

properties.

There are no reported significant differences in permeability between humeral

head cartilage and glenoid cartilage. However, Huang and Stankiewicz [177]

reported significant differences in permeability values within different locations of

the humeral head cartilage, while Mow and Bigliani [28] reported no significant

differences. The average permeability values reported in these studies for the central

region of the humeral head cartilage range from 1.82x10-14m4/Ns [178] to 5.1x10-

15m4/Ns [28]. Although the aforementioned values are different from each other, the

average age of the subjects from which the specimens were harvested was similar

(p<0.05). The findings from these studies indicate that there are no significant

differences in the mechanical properties in humeral head cartilage and glenoid

cartilage. Therefore, the present study focused on the central load-bearing area of the

humeral head cartilage which is also where osteoarthritis-related changes mainly

manifest.


2.5 BIOMECHANICAL MODELS OF ARTICULAR CARTILAGE

Due to the remarkable load-bearing ability of articular cartilage, its susceptibility to

osteoarthritis, and the difficulty in experimentally investigating the internal tissue

behaviour, cartilage has been of interest to biomechanical modellers during the past

half-a-century. Biomechanical models have investigated the mechanisms underlying

the mechanical behaviour responses of normal and osteoarthritis-affected cartilages;

the role of cartilage components on tissue behaviour; and how the cartilage

composition and structure affect the tissues’ mechanical behaviour [181]. The main

challenge in modelling articular cartilage is identifying a suitable way to

conceptualise the tissue and finding ways to include structural features into the

models [113]. Biomechanical models of articular cartilage can be broadly divided

into three types: mixture models, Biot’s [182] theory-based models, and fibril-

reinforced composite models.

Mixture models for cartilages were first developed by Mow et al. [183] who

conceptualised the cartilage as a mixture of its constituents. These models consider

that the cartilage consists of distinctly different phases, namely, solid and fluid

phases. While these earliest mixture models explain the macroscopically-observed

confined compression data satisfactorily [183]. However, some limitations in model

predictions have been observed [184, 185] . In unconfined compression, the earlier

mixture models were unable to capture the typical, large stress relaxation behaviours

(ratio of peak force to equilibrium force can be high as 10) observed for cartilage

tissues, where they have a theoretical limit of 1.5 for the peak force to equilibrium

force ratio [186]. Accounting for the friction between cartilage–indenter interfaces

was not enough to improve the theoretical limits [187, 188]. Deviation of mixture

models in creep experiments was observed during the early stages of creep


deformation [160, 189]. To date, there have been numerous extensions to the original

mixture model to account for tissue anisotropy [176] , large deformations [190, 191],

viscoelasticity [192], swelling [193] and tension-compression nonlinearity [180].

These extended models have been able to improve the limitation of mixture models

and is able to explain the tissue behaviour under various loading conditions.

There were discussions in the late 1970s to early 1990s about whether the

conceptualisation of cartilage as a mixture is representative of the functional roles of

cartilage constituents [135, 194]. For example, collagen (which mainly resists

tension) and hydrated proteoglycans (which deform excessively under direct

compressive loads) are unlikely to function separately to form a remarkable

compressive load-bearing unit in the cartilage [98]. Based on these arguments, there

was debate about whether the conceptualisation of cartilage as a mixture was

acceptable [194]. Therefore, some researchers prefer to use to use Biot’s theory

[182] rather than mixture theory for cartilage. This is because, conceptually, Biot’s

theory does not consider cartilage to consist of two distinctly different phases.

However, it should be noted that mixture theory was reviewed by Simon [195], who

concluded that, mathematically, the mixture models are similar to the models based

on Biot’s theory.

Soulhat et al. [179] and Li et al. [185] introduced fibril-reinforced cartilage

models by conceptualising cartilage as fibril-reinforced composite materials that

distinctly distinguishing the role of fibrils and the non-fibrillar matrix (proteoglycan

and water). The main objective of the fibril-reinforced composite models is to

explain the large stress relaxations observed in the unconfined compression of

cartilage tissues and to understand the role of fibrils and non-fibrillar components.

Fibril-reinforced models have been extended to non-homogeneous models [196] with


depth dependent material parameters [197] and further extended to a 3D cartilage

model to include the realistic 3D collagen fibre orientation [198]. These models are

advantageous in explaining the large stress relaxations observed in cartilage and in

understanding the contribution of matrix constituents to the mechanical behaviour of

the tissue.

Acknowledging the advantages of the fibril-reinforced models, it is important

to mention some of the limitations and concerns about these models. One of the main

limitations of the fibril-reinforced models is the inability to represent collagen cross-

linkers and the dense collagen meshwork [113, 155]. . Furthermore, fibril-reinforced

models rely on seemingly non-physical parameters such as the Poisson’s ratio of the

proteoglycan gel [199]. The limitations of fibril-reinforced models have been

partially addressed by Wilson, van Donkelaar [200] and Wilson, van Donkelaar

[201]. Their models included a greater number of springs and paid more attention to

the interactions between the collagen and proteoglycans [199].

Another concern about the conceptualisation of cartilage as a fibril-reinforced

model arises from the experimental observation of Broom and Silyn‐Roberts [106].

They observed that proteoglycan itself has little influence on the cohesive strength of

the fibril matrix. Further, there are experimental findings supporting the argument

that there are no significant mechanical interactions between the proteoglycan gel

and the fibril matrix [202]. Considering these observations, it is unlikely that there is

a significant shear stress transfer between the fibril network and proteoglycans,

unlike in fibril-reinforced composite materials [98].

In the ABAQUS 6.12 commercial FE software (Abaqus 6.12, SIMULIA,

Rhode Island, USA), Biot theory based porous media models can be easily

implemented using built in software capabilities. Therefore, the present study


modelled cartilage as a porous media saturated with fluid, based on Biot’s theory

[182]. This theory was originally developed by Terzaghi [203] for the one-

dimensional consolidation of soils and was later generalised to three dimensions by

Biot [182]. Oloyede and Broom [135], using a series of experiments [131, 142, 204],

demonstrated that the theory is applicable to cartilage. The theory considers cartilage

to comprise an incompressible solid skeleton saturated with incompressible mobile

fluid. Under load, the fluid is able to exude; hence, the solid skeleton is deformed

due to volume loss.

2.6 SUMMARY AND IMPLICATIONS

Based on the above literature review, the following main points and research gaps

have been identified:

• A large number of studies have been conducted to investigate the behaviours

of lower limb cartilage tissues such as knee cartilages. However, scarce

research is available on one of the most important joint cartilages, namely,

shoulder cartilage. While the lack of studies on shoulder cartilage—the third-

most osteoarthritis-affected joint—is surprising, the growing incidence of

shoulder osteoarthritis and shoulder arthroplasty, as well as the increasing

numbers of people participating in sporting activities, suggest that it is crucial

to investigate the characteristics of shoulder cartilage.

• Evidence reported in the literature shows that biological tissues such as

cartilage adapt according to the mechanical loading environment. Although

not mainly a load-bearing joint, shoulder joint undergoes a variety of forces

during daily activities. These forces are both static and dynamic. Hence,

unique compositional, microstructural and biomechanical properties and

behaviours are expected in shoulder cartilage tissues, although these have


hitherto lacked attention. Furthermore, given that the shoulder cartilage

undergoes both static and dynamic loading, and that the individuals who are

most prone to shoulder osteoarthritis are those who perform dynamic

activities using the shoulder, it remains important to investigate the dynamic

loading behaviours of shoulder cartilage.

• To best of author’s knowledge, an investigation to identify the mechanisms

facilitating the strain-rate-dependent mechanical behaviour of shoulder

cartilage tissues has not been conducted previously. Therefore, it remains

important to understand the factors affecting the dynamic load bearing ability

of shoulder cartilage.

• The findings and conclusions on the structure–function relationship in

cartilage have mostly been based on investigations carried out on knee

cartilage. Considering the potential differences in composition and

microstructure in the knee and shoulder cartilage, it is highly likely that the

conclusions that have been drawn may not be directly applicable to shoulder

cartilage. This remains a significant gap in knowledge which could have

important implications for both the numerical modelling and tissue

engineering strategies catering for specific joint cartilages. Therefore, it is

important to investigate the structure–function relationship of shoulder

cartilage specifically.

• The existing literature on shoulder cartilage points out that there are no

significant differences between the properties of the cartilage layer in the

humeral head and glenoid. Therefore, in the current study, only the behaviour

of humeral head cartilage tissues was investigated.


• Cartilage can be modelled as a porous media saturated with fluid, based on

Biot’s theory. The theory considers cartilage to consist of an incompressible

solid skeleton saturated with incompressible mobile fluid which exudes under

the application of load.

• The main hypothesis of this thesis was: Due to the adaptability of biological

structures to mechanical loading, compositional and structural differences in

shoulder cartilage is anticipated in comparison to high weight bearing

cartilages and these differences is reflected in the factors affecting the

mechanical behavior of the shoulder cartilage. This main hypothesis is broken

down in to several hypotheses in the three studies conducted in this thesis.

Based on the identified research gaps, it can be stated that investigation into the

behaviour of shoulder cartilage remains an important research area. Hence, the

following chapters report this study’s investigation of the strain-rate-dependent

mechanical behaviour of shoulder cartilage tissues with the objective of

understanding the underlying mechanism and its relationship with the shoulder

cartilage structure.


Chapter 3: Research Design and Methodology

This study is based on the underlying philosophy that the structure of biological

tissues such as cartilage adapts to the external mechanical stimuli and that their

mechanical behaviour depends on the structure and composition of the tissue.

Therefore, we hypothesized that microstructural features and composition of

shoulder cartilage are different from cartilage tissues that are more frequently loaded.

Further, these differences should be reflected in the mechanical properties and

behaviour of shoulder cartilage.

This chapter presents the rationale for the research methodologies employed in

this study and describes the research design and methods adopted to achieve the aims

and objectives (as stated in Chapter 1, Section 1.3). Section 3.1 discusses the animal

model chosen for experimentation purposes. Section 3.2 elaborates on the

experimental methodology and explains the stages of the implemented research

methodology including the preliminary results that were required for the subsequent

stages of the study. Lastly, Section 3.3 presents the computational modelling

methodology used to investigate the research problems identified.

3.1 EXPERIMENTAL ANIMAL MODEL FOR SHOULDER CARTILAGE

Cartilage tissue obtained from the human shoulder joint would have been the most

suitable sample for the present investigation, since joint kinematics and dynamics are

regarded as important factors that regulate the mechanical properties of biological

tissues [81, 205]. However, human specimens which are usually diverse (in terms of

weight, age etc.) are not only difficult to obtain but their usage involves ethical and

Chapter 3: Research Design and Methodology 43

legal restrictions. On the other hand, animal models are more readily available and

involve fewer ethical and financial constraints [206].

In selecting a suitable animal model for shoulder cartilage research, the

shoulder joint of the animal model should be anatomically and biomechanically

similar to that of a human shoulder joint. Ovine, bovine, steer, canine and rat have

been previously used to investigate the mechanical properties of shoulder cartilage

tissue [207-209] . However, except for rats, the anatomy and biomechanics of the

shoulder joint in other animal models are different to that of a human shoulder [210].

This is because the quadruped animals use forelimbs for weight-bearing during

locomotion with minimal overhead activity. Their movements are largely restricted

to the sagittal plane. Humans are bipedal and do not use the shoulder much for

weight-bearing activities. Further, humans can additionally rotate and move in the

coronal plane, giving the shoulder more mobility [211]. These differences have

significant implications for the adaptation and architecture of shoulder cartilages

[210], and potentially for its mechanical properties and behaviour too.

Apart from non-human primates, macropods, rats and certain types of mice

(kangaroo mice, hopping mice etc.) have shoulder joints similar to that of humans.

Rat is one of the most commonly used animal models for shoulder research because

it is considered to have similar bone anatomy and overhead activity to that of a

human shoulder [210]. However, the small tissue thickness of its articular cartilage is

a disadvantage in carrying out macroscale mechanical testing. On the other hand,

there are ethical and economic concerns that limit the use of non-human primate

tissues for experimentations [210]. The shoulder joint of rare species such as tree

kangaroo also has a very similar anatomy and biomechanics to that of a human

shoulder [210, 211]. Recently, kangaroo has been postulated as a potential animal

44 Chapter 3: Research Design and Methodology

model to study upper limb joint cartilages [79, 168, 212-214] due to the significantly

lower amounts of loading experienced by the upper limb joints compared to the

lower limb joints, making it similar to humans. Considering these factors, kangaroo

was selected as the most suitable animal model for the shoulder cartilage research

conducted in this study.

3.2 EXPERIMENTAL METHODOLOGIES AND MATERIALS

3.2.1 Tissue harvesting and preparation

Visually normal [ICRS [215] macroscopic score=0] cartilage samples of 8 mm

diameter with 2–3 mm of subchondral bone intact (Figure 3.1(a)) were harvested

using a specially designed stainless steel puncher. The samples were obtained from

the central load-bearing area of the humeral head (Figure 3.1(b)), from adult red

kangaroos (approximately 5 years old), bought from an abattoir within 24 hrs of

slaughter. After harvesting, the samples were preserved in phosphate-buffered saline

(PBS)-inhibitor solution containing inhibitors of proteolytic enzymes (5 mM

benzamide-HCL and 5 mM EDTA) and antibiotics (200 mM L-glutamine 10000

units of penicillin and 10 mg/mL of streptomycin; Sigma-Aldrich, Castle Hill, NSW)

and were stored at -20 °C [216]. Before subsequent biomechanical testings, the

samples were thawed for approximately 30 minutes in PBS at room temperature (i.e.

approximately 27 °C) [217]. The samples went through a single freeze–thaw cycle so

as to ensure that their composition and structure were not affected by multiple

freeze–thaw cycles [216, 217].


Figure 3.1: (a) 8 mm diameter cartilage sample; (b) Specimen-harvested region (near the central area of the humeral head); (c) Bone was constrained using a stainless steel holder and submerged in physiological (0.15 M) saline solution; (d) Indentation testing on the sample

3.2.2 Evaluation of potential thickness measurement methods

Several methods are available to measure the thickness of cartilage tissues. Notably,

these methods can be broadly divided into destructive and non-destructive methods.

Destructive methods of thickness measurement include anatomical sectioning or

punch probes/biopsy [218], needle probe [219], optical [148], and

stereophotogrammetry [220]. In anatomical sectioning, a biopsy is obtained from the

place of interest before thickness is measured using a precision caliper or through

microscopic observation. In the needle probe method, a sample with subchondral

bone intact is fixed to a mechanical testing machine attached with a needle indenter

and is pierced at a point where the thickness measurements are of interest. In this

method, the cartilage surface and calcified bone interface are identified using the

force–displacement profile and the cartilage thickness is obtained by finding the

difference in measurements. In the optical method, the osteochondral cartilage

samples are imaged using a microscope and the subsequent thickness measurements

are analysed using these images. In the stereophotogrammetric method, the joint

cartilage surface and its underlying bone are imaged after dissolving the cartilage in a


5.25% sodium hypochlorite solution and the difference is considered to be the

cartilage thickness [220].

MRI, near-infrared resonance (NIR) and ultrasound are the main non-

destructive methods used to measure the thickness of cartilage. MRI is especially

used for in vivo measurements [221] and has not been frequently used to measure the

cartilage thickness of osteochondral plugs. Recently, NIR has been identified as a

potential method to measure cartilage thickness [222]. However, in this method, in

addition to the complex post-processing of NIR spectral data, extensive calibration

(requiring simultaneous NIR and needle probe measurements of a considerably large

number of samples (90–100)) of the specific tissue of interest is also required [109].

On the other hand, the ultrasound technique measures the thickness of the cartilage

based on the difference in the time taken for echoes to reach the sensor after

reflection from the cartilage surface and cartilage–bone interface; hence, it does not

require complex post-processing [223]. Therefore, in the present study where

thickness measurements were required before indentation testing, ultrasound was

chosen as the most suitable technique. However, for the thickness calculation using

ultrasound measurements it is necessary to know the speed of the sound in the

respective cartilage. The procedure employed for ultrasound speed measurements in

the kangaroo shoulder cartilage is elaborated in the next section.

3.2.3 Ultrasound speed in kangaroo shoulder cartilage tissues and thickness measurement

Ultrasound thickness measurement may incur errors due to the assumed value of

ultrasound speed in cartilage [224], which depends on tissue microstructure and

composition. In the present study, in order to calculate the speed of the sound in

kangaroo shoulder cartilage, the travel time of sound (based on the difference

between echoes from the saline–cartilage interface and osteochondral junction) was


recorded for the samples harvested from the central load-bearing area of the humeral

head. A 10 MHz, Ø3 mm plane-ended contact transducer (V129 Panametrics Inc.,

Massachusetts, USA) was used for the ultrasound measurements and a 3 mm

distance was set between the cartilage surface and transducer during these

measurements based on previously published results in our laboratory [225]. The

transducer, excited by a pulser-receiver (Model 5072PR) was connected to an

oscilloscope (Model PC 5204) that converts the analogue signal to digital. The

sampling frequency of the pulser-receiver was 50 MHz. The echoes from the surface

and subchondral junction reflections were recorded using PicoScope software (Pico

Technology Limited, Cambridgeshire, UK).

After ultrasound measurement, the samples were placed in a sample holder to

reduce the possible movement of the sample and were fixed to a high-resolution

mechanical testing machine called an Instron (Model 5944, Instron, Canton, MA,

USA). A custom-made needle indenter (needle probe) was attached to the load cell

of the machine for needle probe measurements. Then the needle probe was gently

lowered until it just touched the tissue surface and the sample was indented at 10

mm/min [219, 222] until the cartilage–bone interface was reached, as identified by

the load displacement curve (Figure 3.2(b)). Five needle probe measurements were

obtained within an approximate 3 mm diameter circular area (Figure 3.2(a)). The

measurements were averaged and plotted against the respective ultrasound travel

times for all the samples tested (n=43). Based on a previous study, 40–50 samples

were chosen for this testing [219]. The previous study observed a good linear

correlation between the needle probe and ultrasound measurements [219], whereby

the gradient of the plot gave the average speed of sound in the cartilage tissues.


Figure 3.2: (a) Needle probe measurement location in the sample; (b) A typical force–indentation curve during needle probe indentation – The curve is characterised by articular cartilage (AC) surface puncture due to piercing of the cartilage surface; the initial gradient of the curve significantly increases when the cartilage-calcified bone surface is reached

The ultrasound travel times plotted against the needle probe thicknesses for the

tested samples are shown in Figure 3.3. The two measurements showed a good

correlation for the tested samples (R2=0.9829, p<0.005). The slope of the curve

indicated that the average speed of the sound inside the kangaroo shoulder cartilage

is 1658.27 ms-1 (Figure 3.3). This value was taken for all the subsequent thickness

calculations for kangaroo shoulder cartilage in this research.

Ultrasound Measurement area

Needle probe measurement points

Sample surface

AC surface

AC surface puncture Tide mark

Estimated uncalcified cartilage thickness

(a) (b)


2x10-7 4x10-7 6x10-7

5x10-4

1x10-3

2x10-3N

eedl

e pr

obe

thic

knes

s(m

)

Ultrasound travel time(s)

Figure 3.3: Plot between ultrasound travel time and kangaroo shoulder cartilage thickness from needle probe measurements; the slope of the curve is the average ultrasound speed in the tissue

3.2.4 Biomechanical characterisation: Mechanical tests performed on articular cartilage

Indentation, confined compression and unconfined compression tests are commonly

used to assess the mechanical properties of articular cartilages [226]. In confined

compression, a cartilage sample without subchondral bone is tested with a porous

disc on top, after confining the perimeters of the sample in a confining chamber.

Using the confining configuration, the most commonly obtained measurements

include the consolidation measurements and equilibrium stress-strain measurements

of the tissue [135, 226]. In the consolidation measurement, the pore pressure

underneath the samples and the strain measurement are first obtained. Afterwards,

based on the effective stress principle, the effective stress-strain curve is obtained

and the solid skeleton properties of the cartilage are evaluated based on the curve

[135]. In the equilibrium measurement, the samples are compressed stepwise and

Needle probe thickness = 1658.27 x Ultrasound travel time R2=0.9829


allowed to relax after each compression in order to obtain the equilibrium stress-

strain curve. The aggregate modulus ( AH ), which is an indicator of solid matrix

stiffness, is obtained from the gradient in the linear region of the equilibrium stress-

strain curve. On the other hand, in unconfined compression, stepwise ramp

compression is employed on samples which are not confined in perimeter and

Young’s modulus of solid matrix ( sE ) is extracted from the linear part of the

equilibrium stress-strain curve [226]. Young’s modulus of solid matrix is related to

the aggregate modulus using Eq. (3.1), where sν is the solid matrix Poisson’s ratio:

As

sss HE

ννν

−−+

=1

)21)(1( (3.1)

Indentation tests, using porous and nonporous indenters, are commonly

performed on cartilage samples with the bone intact [189, 227]. Samples are

compressed stepwise and allowed to relax after each indentation and the subsequent

equilibrium stress-strain curves are used to obtain the mechanical parameters when

the porous indenter is used [146].

3.2.5 Critical evaluation of confined, unconfined and indentation mechanical tests

In the case of confined compression, it is difficult to fit the samples into the

confining chamber perfectly. If the sample cannot be perfectly fitted to the confining

chamber, frictional forces may act between the sample and the confining chamber

during compression [184]. This may affect the mechanical parameters measured,

especially when extracting dynamic properties [146, 226]. Additionally, the

mechanical parameter obtained may be affected by the interdigitation of the cartilage

surface and the pores of the disc during testing [184]. This may possibly damage the


tissue, given that interdigitation depends on the pore size and pore distribution,

which may not be uniform unless specifically controlled [160, 184, 228].

In both confined and unconfined compression tests, removing the sample from

the subchondral bone affects the integrity of the natural cartilage–bone system.

Further, if precision cutters are not employed during sample-shaving, the cartilage

may possibly be damaged, especially if the cartilage samples are thin. The natural

collagen architecture of cartilage is such that fibres are anchored perpendicular to the

underlying subchondral bone in the calcified zone. Disruption to the integrity of this

structure may affect the mechanical properties of the cartilage. Studies have reported

that Young’s modulus obtained from indentation tests is significantly higher than that

obtained from confined and unconfined compression tests, and this has been partially

attributed to the cartilage samples being removed from the bone [226]. Unconfined

compression tests on bone-intact samples can also be used to obtain the mechanical

properties of cartilage tissue. However, the geometrically complex behaviour of the

tissue at the periphery of the cartilage–bone interface makes it difficult to obtain an

analytical solution to this type of compression problem [179, 229].

Due to the above reasons, indentation testing can be considered a better

alternative to unconfined and confined compression tests. Indentation moduli have

also been identified to correlate well with Young’s modulus obtained from

unconfined compression or the aggregate modulus obtained from confined

compression [226, 230] . Although the size of the indenter affects the force–

displacement results, instant and equilibrium shear moduli are found to be

independent of the indenter radius [231, 232]. However, when using the porous

indenter, not only can it result in interdigitation but there are additional difficulties in

precisely implementing the indenter–cartilage interface boundary conditions in a


numerical model [184]. Moreover, Jurvelin and Kiviranta [233] stated that the

instant and equilibrium response should be the same for both porous and non-porous

indenters, since there is no water flow through the indenter in both cases [234].

Indentation using a non-porous indenter is shown to resemble the physiological

cartilage-to-cartilage contact during joint function [204]. However, during

indentation, friction between the cartilage and indenter interface may affect the tissue

behaviour, especially when a flat indenter is used. In addition, during repeated tests it

is also possible for the tissue to be damaged. In order to address these concerns,

synovial fluid can be employed on the indenter. By using an indenter with rounded

edges, both friction and potential damage to cartilage can also be reduced. Moreover,

indentation tests on cartilage have been widely used to obtain the mechanical

properties of tissues for the clinical diagnosis of osteoarthritis both in vitro and in

vivo, and therefore serve as an important method of tissue characterisation [230,

235-238]. Hence, in the present study, the indentation test was chosen to characterise

the kangaroo shoulder cartilage tissue. Details of the indentation test conducted in the

present study are provided in the following section.

3.2.6 Mechanical testing protocol

3.2.6.1 Physiological strain-rates and strains experienced by joints

A number of earlier studies have tested cartilage under different strain-rates. Radin

and Paul [141] tested cartilage from 2.7×10-3/s to 3.5×10-2/s and Lai and Mow [239]

loaded the cartilage from 3.3×10-5/s to 3.3×10-4/s. Investigating the cartilage

response for a wide range of strain-rates, Oloyede and Flachsmann [142] indented

cartilage from 10-5/s to 103/s. More recently, Langelier and Buschmann [148],

DiSilvestro and Zhu [146] and Li and Buschmann [145] studied cartilage in the

range of 10-4/s to 5×10-2/s strain-rates. To the best of the author’s knowledge, there


are no existing studies that have measured the physiological strain-rates experienced

by cartilage in vivo. However, the maximum physiological strain-rate measured by

Rubin and Lanyon [240] in a treadmill study in which strain gages were attached

directly to the radial and tibia mid shaft of dogs and horses was 8×10-2/s (when the

animals were galloping). In [241], load cells were implanted on the tibia of a rabbit

approximately 1 cm below the knee joint and strain-rates of 3×10-2/s were reported

when impulse loads were applied on limbs. Therefore, a strain-rate in the order of 10-

2/s can be considered as at the higher end of the physiological strain-rates. Also

strain-rates in the range of 10-5/s to 10-4/s are generally considered to be at the low

end of the physiological loading-rates [142].

The peak load of an impact on joints, which potentially causes tissue damage,

occurs in much less than a second after the initial application of the load [242, 243].

For example, motor vehicle impact accidents, which occur in milliseconds, generally

happen at around 103/s strain-rate [244]. Sub-impact loads occur in several seconds

(in the order of 1/s strain-rates), and may induce surface cracks and chondrocyte

death [242]. Further, from reported in vivo deformation data on the tibiofemoral

joint, physiological strains on average can go up to 30%, ranging from 10% to 40%

during daily activities [245, 246]. Based on the above information, in the current

study, strain-rates ranging from 10-4/s to 10-2/s were chosen to cover the

physiological low and high ends of strain-rates and cartilage was loaded up to 30%

strain to represent the average loading in joint cartilages.

3.2.6.2 Indentation testing

Before conducting mechanical testing, the subchondral bone underneath the cartilage

sample was properly fixed using a stainless steel holder (Figure 3.1(c)) to ensure that

the deformation data obtained in the testing were only related to the cartilage


deformation. The indentation testing was carried out at 10-4/s, 5x10-4/s, 5x10-3/s and

10-2/s strain-rates (Figure 3.1(d)). Depending on the thickness of the samples, the

speed of the indentation was adjusted in order to obtain the required strain-rate. The

samples were indented up to 30% engineering strain and a further limit of 3.5 MPa

was imposed on the amount of stress that the samples were subjected to, in order to

minimise potential damage to the tissues. A safe limit of 3.5 MPa for strain-rates

between 3×10-5/s and 7×10-1/s has been suggested to prevent damage to the cartilage

matrix [242, 247]. In addition, before and after every test, the sample surfaces were

microscopically examined (Leica MZ6, Leica Microsystems, Heerbrugg,

Switzerland) to check whether testing had induced any damage to the cartilage.

Although we rarely found damage to the tissue, testing on the specific sample was

terminated in the cases where damage was found.

The testing was done on a high-resolution Instron testing machine

(Model 5944, Instron, Canton, MA, USA) using a plane-ended polished indenter of 3

mm diameter with 0.1 mm radius rounded edge. An indenter with rounded edge was

chosen in order to reduce possible local damage to the cartilage due to stress

concentration at the indenter edges. Spherical indentation could also be used;

however, the theoretical analysis, especially the solid–fluid interaction analysis,

would become complicated since the contact area changes with the deformation of

the tissue. Additionally, it has been experimentally demonstrated that the contact of

the cartilage–solid indenter resembles cartilage–cartilage contact [204]. After each

test, the cartilage was unloaded and allowed to recover for 1 hr in PBS-inhibitor

solution at 4 °C prior to the next test.


3.2.6.3 Surface detection, zero-point determination

Identifying the point where the sample surface first touches the indenter (zero-point)

is important in order to accurately extract the mechanical properties from the force–

displacement results. This is especially relevant for soft material such as cartilage

where a small pre-load can have a significant deformation in the tissue, leading to

overestimation of the material’s properties [248, 249]. It is customary in cartilage

testing to apply a pre-load of 0.01N-0.05N to make sure that the sample is in contact

with the indenter [177, 250]. However, in the present study, the surface detection

method developed by Cao and Yang [251] as described by Kaufman and Klapperich

[248] was used to identify the cartilage surface before the indentation tests. This

involves carefully lowering the indenter using the ‘fine position controller’ in the

Instron machine until it just touches the cartilage surface (indicated by the positive

readings of the load cell) and then retracting a step backwards to make sure that the

indenter is just above the sample surface.

3.3 NUMERICAL MODELLING METHODOLOGY

3.3.1 Numerical modelling to investigate the physical mechanisms underlying the mechanical behaviour of cartilage: Initial model development

FE modelling has been widely used to investigate cartilage behaviour due to

experimental difficulties in probing the internal tissue behaviour. For instance,

inserting sensors inside the tissue will affect its structure and hence also affect the

natural behaviour of the tissue. Additionally, under dynamic loading conditions, the

measurement of fluid velocity, fluid pressure and collagen network stresses requires

sophisticated experimental set-ups, especially for small tissues such as shoulder

cartilage. In an earlier attempt to carry out an experimental investigation using MRI

in this study, to measure fluid velocity inside the tissue, it was found that facilities

are extremely expensive to acquire. Therefore, the most pragmatic method to


investigate the research problems in this study was to carry out a combination of

experimental and numerical investigations that complemented each other. The

following sections summarise the procedures employed to develop the numerical

model of cartilage, and the initial numerical studies that were carried out to confirm

the appropriateness of the modelling technique. The modelling in this study was

conducted in ABAQUS 6.12 commercial FE modelling software (Abaqus 6.12,

Simulia, Rhode Island, USA), which is widely used in developing biomechanical

models of cartilage tissues.

Cartilages undergo nonlinear lager deformations [177]. Hyperelastic material

models can be used to represent large deformation behaviour of cartilage tissues

[252]. However, there are no analytical equations available for indentation of

hyperelastic solids that could be used for the present study’s indenter geometry. In

section 3.3 an analytical equation for the indenter geometry used in this study is

developed. Before that, in order to check the appropriateness of boundary conditions

and mesh density of the initial numerical model an analytical relationship reported

[253] for the spherical indentation of isotropic linear elastic material is used in this

section..

The analytical relationship, which relates indentation force )(F to indentation

depth )(δ , for a linear elastic solid with thickness h , indented with a spherical

indenter (radius R ) is [253]

++

+−+−

−= 4

0

2304

030

2303

22

200

2

23

21

5316

154842

1)1(3

4χβ

πα

πα

χβπ

απ

χπα

χπαδ

vERF (3.2)

where hRδχ = , the constant 0α and 0β are functions (Eq. (3.3) and Eq. (3.4)) of

Poisson’s ratio )(ν and E is the Young’s modulus.


νννα

−+−

−=1

3442.14678.12876.1 2

0 (3.3)

νννβ

−+−

=1

5164.10227.16387.0 2

0 (3.4)

Eq. (3.2) above has been developed based on the assumption that, in order to

maintain the material lineally, the strain should not exceed 10%. Further, a constraint

of Rh 1.0≥ is suggested for the validity of Eq. (3.2). In the present study, we first

developed a numerical model for spherical indentation by representing the cartilage

as a linear elastic material. Then, the numerical model prediction was compared with

the prediction of Eq. (3.2) to confirm the appropriateness of the boundary conditions

in the model. The effect of mesh density on the model predictions was also

evaluated. All the details related to the model development are set out in the

following sections.

3.3.1.1 Model geometry

The geometry of numerical models were based on the dimensions of the individual

samples tested (Table 3.1). The maximum thickness of kangaroo cartilage measured

in this study was less than 1.5 mm. Therefore, the thickness value of the initial

cartilage model, that was used to obtain the mesh density and to check model

validity, was taken as 1.5 mm. Further, considering that the radius of the indenter

used in the present study was 1.5 mm, this value was taken as the radius of the

spherical indenter. The bone and indenter were assumed to be rigid throughout the

study due to the fact that the stiffness of the bone and indenter is several magnitudes

larger than the stiffness of cartilage tissues. A test simulation was performed and

indicated that representing both bone and indenter as rigid bodies did not affect the

simulation results. Young’s modulus of cartilage was taken as 0.5 MPa, which is a


typical average value for cartilage tissues [254]. The material was assumed to be

nearly incompressible for simplicity, and Poisson’s ratio was taken as 0.499 in

accordance with the ABAQUS 6.12 user manual [255]. It is noted that these

assumptions did not affect the subsequent conclusions made.

Table 3.1: Parameters of the model used for mesh, boundary and loading condition validations

Diameter of sample (mm) 8.0

h (mm) 1.5

Thickness of bone (mm) 3.0

R (mm) 1.5

E (MPa) 0.5

ν 0.499

3.3.1.2 Model mesh

Considering the geometry of the cartilage samples, the assumption of homogeneity

and isotropy, and the loading conditions used during mechanical testing an

axisymmetric model were employed. Cartilage was meshed with 4-node bilinear

axisymmetric quadrilateral (CAX4). The cartilage mesh and model are shown in

Figure 3.4(a). Model simulations for 800, 8000 and 22,400 elements were also

evaluated.

3.3.1.3 Boundary conditions of the model

The boundary conditions of the model were set according to the boundary conditions

to which the specimens were subjected during mechanical testing. The enforced

boundary conditions are summarised as follows:


• The interaction boundary condition between the indenter and cartilage was

specified as ‘frictionless’ using ABAQUS software options. This simulated

frictionless contact between the cartilage surface and indenter.

• The boundary between the cartilage and bone (highlighted in a red line in

Figure 3.4(a)) was simulated using the ‘Tie constraint’ boundary condition in

ABAQUS 6.12.

• During the experiment, the bone was constrained using a stainless steel

holder to ensure that the deformation was only caused by deformation of the

cartilage samples. Therefore, the displacement and rotation of the bone in all

directions were set to zero by fixing the reference point (RP) of the bone

(Figure 3.4(a)).

• Deformation in the ‘Z’ direction was allowed on the left symmetric plane of

the cartilage model.

• The indenter was prescribed with displacement at its RP in order to simulate

the indentation process. The amount of displacement was specified based on

the deformation to which the samples were subjected during the experiments.

In order to assess whether the model in Figure 3.4(a) could be further

simplified, the bone was replaced by a rigid constraint. This restricted the

displacement and rotation of the lower cartilage boundary in all directions

(highlighted in a red line in Figure 3.4(a)), while keeping all other boundary

conditions the same. The two model results were compared with each other as well

as with the theoretical prediction of Eq. (3.2).


Figure 3.4: (a) The model geometry, mesh, boundary condition and loading configuration of the cartilage–bone FE model; (b) Simplified FE model (without the bone) with mesh and boundary conditions – In this model, the bone is replaced by a rigid constraint (indicated by the red line) which restricts the displacement of the bottom plane of the cartilage

3.3.1.4 Solution methodology

The static stress analysis procedure in ABAQUS/Standard was used for the above

indentation problem. The procedure uses the Newton method to solve nonlinear

equilibrium equations. The initial time increment was set at 10-5/s, and the maximum

time increment was set at 0.1 s.

3.3.1.5 Comparison of the model results and the theoretical predictions

Figure 3.5(a) and Figure 3.5(c) show the results of the model simulation along with

its comparison with the theoretical prediction for 800, 8000 and 24,400 elements. It

was observed that the numerical results and the theoretical model conformed well,

with only a slight deviation at large deformation. Further, the two models (i.e. the

model with the rigid bone and the model with the rigid constraint) showed identical


force–indentation graphs (Figure 3.5(d)), implying that the proposed model

simplification could be carried out. Stress distributions were also observed to be

identical (compare Figure 3.5(a) and Figure 3.5 (b)).

Figure 3.5: (a) Stress distribution for cartilage on rigid bone indented to 10% strain; (b) Stress distribution for cartilage on rigid constraint indented to 10% strain; (c) Comparison of the numerical model’s result (force on indenter) with the theoretical prediction of Eq. (3.2) and mesh sensitivity data; (d) Comparison of elastic cartilage on rigid bone laminate model results and elastic cartilage-rigid constraint model results with theoretical model results

After confirming that the FE mesh and the model including the boundary

conditions are adequate, the spherical indenter was replaced with the geometry used

in the present study and the number of elements was evaluated to obtain model


accuracy of 10-2N for force measurements. The developed model mesh is shown in

Figure 3.6(a). Based on the results it was noted that, in order to obtain 10-2N level of

accuracy, 8000 to 12,000 elements were required (Figure 3.6(c)). Therefore, 9600

elements were considered as appropriate and were used for all simulations in the

study.

Figure 3.6: (a) Cartilage, indenter geometry (3 mm diameter with 0.1 mm fillet radius at the edge), the mesh, boundary condition and loading configuration based on mechanical testing carried on kangaroo shoulder cartilage samples; (b) Numerical result of elastic cartilage samples indented up to 30% engineering strain; (c) Variation of force on indenter based on mesh element number


3.3.2 Assessing the suitability of the porohyperelastic model for investigating the solid and fluid behaviour of cartilage tissues: The preliminary porohyperelastic FE model

In Chapter 2 it was explained that the poroelastic model based on Biot’s theory [182]

is an appropriate starting point for investigating the mechanisms underlying the

mechanical behaviour of shoulder cartilage tissues. Further, it was hypothesised that

the solid–fluid interplay governs the mechanical behaviour of the tissue. Since

cartilage generally undergoes large deformations, it was necessary to impart a

theoretical framework that extends Biot’s theory [182] to include large deformations.

Therefore, porohyperelastic field theory, an extension to Biot’s theory [182] (using

the hyperelastic solid skeleton to account for large deformation) proposed by Simon

[195] was chosen as the theoretical basis for the present study. This theory is

discussed in Chapter 4 in detail. The advantage of using Biot’s theory [182] is that it

can be directly implemented in ABAQUS 6.12 commercial software with a

hyperelastic solid skeleton to simulate large deformation behaviour. However, before

applying the model based on porohyperelastic field theory to investigate the research

problem identified in the literature review, it was necessary to check the

appropriateness of the model for investigating the solid and fluid behaviour of the

tissue. Therefore, a preliminary porohyperelastic model was first developed based on

experiments carried out by Oloyede and Broom [135] and then model

appropriateness was evaluated. Details of this preliminary model development and

comparison with the experimental data are set out in the following sections.

3.3.2.1 Model geometry

The static confined consolidation experiments of Oloyede and Broom [135] were

used for the development and validation of the porohyperelastic FE cartilage model

due to the availability of reported direct internal pore pressure measurements. The


thickness and diameter of cartilage samples based on the sample geometry in

Oloyede and Broom [135] were taken as 1.6 mm and 10 mm, respectively.

3.3.2.2 Model mesh and solution methodology

Due to the symmetric nature of the sample and the type of loading scenario, an

axisymmetric model was developed in order to reduce computational time. The

model was meshed with 9,600 4-node bilinear displacement and bilinear pore

pressure elements (CAX4P). Transient consolidation analysis with the ‘Full Newton’

solution procedure was used to solve the equilibrium equations. The transient

coupled pore pressure/effective stress analysis uses a backward difference operator to

integrate the continuity equation, and therefore it provides unconditional stability.

However, the only concern regarding time integration was accuracy. The minimal

time increment )( t∆ for saturated flows, such as in cartilage, to avoid any evident

oscillation is: [255];

2

2

)(16

)1(l

KE

Ekt

g

ww ∆∆

−

+>

βυg (3.5)

where wg is the specific weight of the wetting fluid, E is the Young’s modulus, k is

the permeability, wυ is the velocity of the pore fluid, β is the velocity coefficient

( 0=β for Darcy flow), gK is the bulk modulus and l∆ is a typical element

dimension. The initial time increment for transient consolidation analysis was set at

10-5/s and, considering Eq. (3.5), the maximum time increment was restricted by the

time scale of the problem solved.

3.3.2.3 Boundary conditions

The static confined consolidation experiments by Oloyede and Broom [135] were

simulated by applying a constant load (1.35 MPa) to the upper boundary in the


negative Z direction (Figure 3.7). Based on the experiment’s boundary conditions,

the ‘pore pressure (p)’ (p=0) boundary condition was enforced on the upper surface

to enable free fluid flow out of the cartilage. The displacement (U) boundary

condition on the right side of the model was set to allow deformation in the Z

direction, while sample deformation in the X direction was constrained. The

displacement at the bottom of the sample was set to zero to mimic the sample glued

to the base of the experimental rig.

Figure 3.7: Boundary conditions employed in preliminary porohyperelastic FE model

3.3.2.4 Initial conditions

The cartilage was considered to be fully saturated, and 80% of the tissue was

assumed to be filled with fluid that fully occupied the pores inside the tissue.

Therefore, the initial value (0e ) as the ratio of the volume of pores to the volume of

solid was set at 4.0. The void ratio was calculated by n

ne−

=1

, where n is the

porosity. Further, the initial pore pressure value was set at zero given that the

osmotic pressure of the tissue was not considered during the study [183].

3.3.2.5 Solid skeleton material model

To account for large deformation, the solid skeleton was modelled as an isotropic

hyperelastic material [256, 257]. The neo-Hookean model, which is the simplest

hyperelastic material model, was used for this initial model. However, it was later

found that the nonlinearity of the solid skeleton of kangaroo shoulder cartilage was


more accurately represented by the 2-term reduced polynomial hyperelastic model

(Chapter 4, Section 4.5.1.1). The isotropic elastic strain energy potential W of the

neo-Hookean model used in the present model is given by:

2

1110 )1(1)3( −+−= J

DICW (3.6)

where )(1 CtrI = is the first invariant of the distortional part FFC T= of the right

Cauchy deformation tensor FFC T= where FF 31−= J is the distortional part of

the deformation gradient F , and Fdet=J is the volume ratio.

Furthermore, 102C=µ , where µ is the shear modulus of the linear elasticity and

κ21 =D , where κ is the bulk modulus of the linear elasticity [79].

3.3.2.6 Strain-dependent permeability

The fluid flow was modelled based on Darcy’s law. The permeability ( k ) decreases

under strain application and can be represented by Eq. (3.7) [191, 258, 259].

Parameter 0k is the permeability of the tissue in an undeformed configuration and M

and m are dimensionless material parameters which were taken as 4.638 and 0.0848,

respectively [191]. Eq. (3.7) is expressed as follows:

−

++

= 1

e1e1

2Mexp

eekk

2

0

m

00 (3.7)

3.3.2.7 Solid skeleton material parameter identification

Young’s modulus was extracted from the initial gradient of the solid skeleton

effective stress-strain data reported in [135], by fitting it to a piecewise linear graph

as shown in Figure 3.8. For bovine cartilage, the Poisson’s ratio was taken as 0.2


according to a reported study [260]. The parameters 10C and 1D were calculated

from Eq. (3.8). The permeability at an undeformed state of the tissue was taken as

2.58x10-16 Ns/m4, in accordance with values reported in the literature [261]. The

material parameters that were used in the model are summarised in Table 3.2.

)1(410 ν+=

EC , E

D )21(61

ν−= (3.8)

Figure 3.8: Solid skeleton effective stress-strain curve fitted with a piecewise linear curve to

extract the solid skeleton material parameters

Table 3.2: Hyperelastic material parameters and permeability values used for the initial porohyperelastic FE model

10C (MPa) 1D (1/MPa) k (Ns/m4)

0.158 4.738 2.58x10-16

3.3.2.8 Model prediction

The pore pressure values obtained from the bottom ‘P’ point (Figure 3.7) and the

displacement values obtained from the compression platen of the model are shown in

Figure 3.9(a) and Figure 3.9(b), respectively. The model prediction indicated that

pore pressure and creep strain, although not perfect, followed experimentally


observed trends acceptably. The model using 400, 6400 and 14,400 elements did not

show any considerable differences in model prediction (Figure 3.10(a) and Figure

3.10(b)). These results demonstrated that the porohyperelastic model can be

considered as an initial model to investigate the solid and fluid behaviour of cartilage

tissues. Therefore, the model was used to investigate the mechanism underlying the

mechanical behaviour observed during the indentation experiments in this study.

The mechanical properties of cartilage tissues can be extracted using

indentation tests where experimental force–indentation data are fitted to a specific

analytical solution. As mentioned above, there are, however, limited analytical

solutions available for the indentation of hyperelastic materials. Especially for the

geometry of the indenter used in the present study, no analytical equations have been

reported. Therefore, for the 2-term reduced polynomial hyperelastic function, we

derived a force–displacement relationship for the indentation problem and used it to

extract the hyperelastic mechanical properties of kangaroo shoulder cartilage. The

methodology and background of the derivation are set out below.

Figure 3.9: (a) Pore pressure measurements compared with FE model predictions; (b) Creep strain measurements compared with FE model predictions


Figure 3.10: Mesh sensitivity analysis for (a) pore pressure predictions (b) creep strain prediction

3.3.3 Development of force–indentation relationship for the 2-term reduced hyperelastic model

The Hertz relationship [262] is the most widely known analytical solution for the

indentation problem of elastic solids which arises from indentation of infinitely thick

samples. Hayes and Keer [263] introduced a correction factor to account for the

finite thickness of samples, for infinitesimal deformation. Jurvelin and Kiviranta

[233] extended the values of the correction factors for large aspect ratios. Further,

Zhang and Zheng [264] considered the correction factors for large deformations and

friction between the indenter and the sample. The bond between the sample and

substrate has also been identified as an important factor when extracting mechanical

properties [265]. Considering the bond between the sample and the substrate, a

force–indentation relationship for spherical indentation was derived by Dimitriadis

and Horkay [253]. The main characteristic of these formulations is that the material

was considered to be linear elastic; hence, the typical nonlinear large deformation

responses of biological tissue cannot be adequately represented.

Based on the hyperelastic models that describe the nonlinear material

behaviour, analytical equations for force–indentation problems have been recently


reported [266, 267]. However, the available equations are only for spherical

indentation and do not consider the effect of samples bonded to substrates and hence

the effect of finite thickness on force–indentation results. Given this limitation, using

finite element analysis (FEA) and theoretical analysis, we introduced correction

factors to adjust the hyperelastic material parameters for the thicknesses and indenter

geometry encountered in this study. In doing so, given the inability of the neo-

Hookean and Mooney–Rivlin models to predict certain large strain behaviours [267],

the 2-term reduced polynomial hyperelastic function was considered as the starting

point. Chapter 4 (Section 4.5.1.1) presents the evidence that this 2-term reduced

polynomial hyperelastic model is the most appropriate model for kangaroo shoulder

cartilage as compared to neo-Hookean and Mooney–Rivlin models.

The strain energy potential (W ) of the reduced polynomial model is:

iN

i i ICW )3(1 10 −=∑ =

(3.9)

Here, the first strain invariant is 2221 zyxI λλλ ++= , where yx λλ , and zλ are stretch

ratios in the X, Y and Z direction. Assuming material incompressibility and the

uniaxial loading is in the X direction, then 2/1, λλλλλ === zyx . Therefore,

1

12

02 )32()1(2

−

=∑ −+−=iN

i iiC λλλλσ (3.10)

In the case of the 2-term reduced polynomial hyperelastic function 2=N .

Therefore, nominal stress ( λσ ∂∂= W ) is:

−+

−+

−= 321412 2

220210 λλ

λλ

λλσ CC (3.11)


where µ=102C and µ is the linear shear modulus; 20C is a nonlinear stiffness

parameter.

The force–indentation relationship obeying the constitutive relationship

(Eq. (3.10)) can be derived by firstly accounting for the sign conversion for the

nominal stress, that is, by replacing σ with *σ− for nominal stress in indentation.

This is because indentation exercises a compressive strain on the material while the

positive convention in Eq. (3.10) is for the tension. Additionally, the relationship

between indentation strain and stretch ratio is: *1 ελ −= . Incorporating these

relationships into Eq. (3.11) gives Eq. (3.12):

−−

+−+−

+

+−+−

= *

3*2*

*2*

*2*3*

20*2*

*2*3*

10*

13

12334

12332

εεε

εεεεε

εεεεεσ CC (3.12)

Assuming that the indenter–sample adhesive force is negligible, the average

nominal stress is equal to the mean contact pressure: 2* aF πσ = where F is the

indentation force and a is the contact radius. In the current formulation, the

indentation strain ( *ε ) is defined as rδε =* where δ is the indentation depth and

r is the indenter radius. Therefore, the following relationship between indentation

force and depth can be obtained:

−−

+−+−

+

+−+−

= 23

32

22

3223

2022

3223

103

2334

2332

rrr

rrrrrC

rrrrrCF

δδδ

δδδδδ

πδδ

δδδπ (3.13)

Here, 10C is related to Young’s modulus ( E ) and Poisson’s ratio )(ν

through)1(3 210 νπ −

=EC . The force indentation Eq. (3.13) accounts for the material

nonlinearity; however, it does not account for the finite thickness of samples.


Therefore, two correction factors, namely 1k and 2k , are introduced into Eq. (3.13) to

obtain the correct values for coefficients 10C and 20C . The modified equation is as

follows:

−−

+−+−

+

+−+−

= 23

32

22

3223

20222

3223

1013

2334

2332

rrr

rrrrrCk

rrrrrCkF

δδδ

δδδδδ

πδδ

δδδπ (3.14)

3.3.3.1 Relationship between correction factors and sample thickness

The above correction factors were obtained by calibrating Eq. (3.13) to a prediction

of the FE model which simulated the indentation of a flat cartilage sample using

indenter geometry in the present study (as discussed in Section 3.3.1 in relation to the

model development). In the FE model, the 2-term reduced hyperelastic polynomial

function was chosen as the material, with the values of the material parameters, 10C

and 20C , being 0.1 MPa and 0.1 MPa, respectively. The model was set up with

different thicknesses of 0.5, 0.55, 0.65, 0.7, 0.75, 1.0, 1.25 and 1.5 mm. The diameter

of the model was set to be 8 mm. In addition, it used an indenter with 3 mm diameter

and a rounded edge of 0.1 mm radius.

The force–indentation curves for 30% strain obtained from the FE model were

curve fitted to Eq. (3.14), using a custom-made nonlinear curve fitting code in

MATLAB R2014a (The MathWorks Australia Pty. Limited, NSW, Australia), in

order to obtain the 1k and 2k values for the respective thickness and indentation

depth. The dependency of the correction factors on the sample thicknesses is shown

in Figure 3.11, and can be represented by the following equations:

568.1

1 306.2−

=

rhk (3.15)


435

2 9580.

.−

=

rhk (3.16)

This variation of correction factors with was incorporated in Eq. (3.14) to

obtain the correct values of 10C and 20C based on the thickness of the individual

samples. Since Eq. (3.9) has been developed assuming material incompressibility,

Young’s modulus was calculated using )1(3 210 νπ −

=EC , assuming the Poisson’s

ratio to be 0.5.

Figure 3.11: Variation of correction factors k1, k2 with sample thickness

This chapter elaborated on the research methodology including the animal

model selection, thickness measurement methodology, mechanical testing procedure,

numerical model development, material model validation and hyperelastic

mechanical property extraction. In the following chapters, the results of the

mechanical experiments are reported and discussed along with the studies conducted

to understand the mechanisms underlying the strain-rate-dependent mechanical

behaviour of kangaroo shoulder cartilage.


Chapter 4: Effect of interstitial fluid on the strain-rate-dependent behaviour of kangaroo shoulder cartilage

4.1 INTRODUCTION

This chapter aims to characterise the strain-rate-dependent behaviour of kangaroo

shoulder cartilage (Section 4.2) using indentation testing at different strain-rates

(Section 4.4). After analysing the force–indentation curves and observing the

characteristic stiffness variation of the tissue with strain and strain-rate, it was

anticipated that the interaction between the solid and fluid components would be able

to fully explain the behaviour of the tissue (Section 4.3). Since the porohyperelastic

model developed in Chapter 3 (Section 3.3) is able to acceptably explain the solid

and fluid behaviour of cartilage tissues, we then evaluated the ability of the existing

constant and strain-dependent permeability models to capture the strain-rate-

dependent behaviour of kangaroo shoulder cartilage (Section 4.5). It was revealed

that the strain-rate-dependent tissue behaviour cannot be fully explained by these two

models. It is postulated that this inability is due to the rate-dependent fluid behaviour

that might be prevalent during rate-dependent loading. Therefore, the existing

porohyperelastic model was extended to incorporate strain-rate-dependent

permeability (Section 4.6) in order to comprehensively analyse the effect of fluid

behaviour on the solid–interstitial fluid interaction of the tissue. The results of the

investigation are presented and discussed (Section 4.7). The study in this chapter

resulted in a journal article named “Investigation of the mechanical behavior of

kangaroo humeral head cartilage tissue by a porohyperelastic model based on strain-

Chapter 4: Effect of interstitial fluid on the strain-rate-dependent behaviour of kangaroo shoulder cartilage 75

rate-dependent permeability” in the Journal of Mechanical Behavior of Biomedical

Materials [79].

4.2 AIMS AND OBJECTIVES

The research reported in this chapter aimed to:

1. Investigate the behaviour of kangaroo shoulder cartilage under different

strain-rates.

2. Compare the mechanical behaviour and biomechanical parameters of

kangaroo shoulder cartilage with the mechanical behaviour and

biomechanical parameters of human shoulder cartilage reported in the

literature.

3. Fully investigate the effect of interstitial fluid on mechanical behaviour of

kangaroo shoulder cartilage under different strain-rates.

4.3 HYPOTHESES

This part of the study explored two main hypotheses:

1) Solid–interstitial fluid interaction governs the strain-rate-dependent

mechanical behaviour of shoulder cartilage tissues.

2) The strain-rate-dependent fluid behaviour significantly affects the

mechanical behaviour of kangaroo shoulder cartilage.

4.4 STRAIN-RATE-DEPENDENT MECHANICAL BEHAVIOUR OF KANGAROO SHOULDER CARTILAGE

For experimentation, as previously mentioned in Chapter 3, firstly, 8 mm diameter

osteochondral samples were harvested from the central load-bearing area of the

humeral head cartilage of ten adult red kangaroos (approximately 5 years old).

Afterwards, the thickness of each sample was calculated based on ultrasound

76 Chapter 4: Effect of interstitial fluid on the strain-rate-dependent behaviour of kangaroo shoulder cartilage

measurements. Mechanical testing was conducted on osteochondral plugs where the

subchondral bone was constrained using the specially-designed apparatus. A 3 mm

diameter indenter with 0.1 mm fillet at the edge was used for indentation. Testing

was conducted by loading samples up to 30% engineering strain at four strain-rates:

10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s. After each test, the samples were unloaded and

allowed to recover for at least an hour in PBS-inhibitor solution at 4 °C. The details

of this experimental procedure were presented in Chapter 3 (Section 3.2.6).

4.4.1 Tissue stiffness: Piecewise linear regression method

The obtained force–indentation data were processed and nominal stress )(σ was

plotted against nominal strain )(ε (Figure 4.1). The stiffness at different strains was

extracted from the nominal stress-strain curves by fitting a piecewise linear curve to

the data points using the shape language modelling technique [268]. Available

MATLAB source codes [268] to implement shape language modelling can be readily

specified to extract the gradients of the stress-strain curves at a given strain value.

The piecewise linear regression fitted well to the stress-strain curves (R-

squared>0.9900; Figure 4.1). The obtained variation of stiffness with strain and

strain-rate is illustrated in Figure 4.2(b).

Figure 4.1: Piecewise linear curve fit to nominal stress-nominal strain data


4.4.2 Stiffness variation with strain and strain-rate

The characteristics of kangaroo shoulder cartilage are not reported in the literature.

Therefore, a suitable initial step was to compare the mechanical behaviour of

kangaroo shoulder tissues with the reported values and behaviour of human shoulder

cartilage tissues. To the best of the author’s knowledge, there are no reported data on

the strain-rate-dependent nature of human shoulder cartilage tissues. However, the

experimental trends observed in the present study (Figure 4.2(a) and Figure 4.2(b))

are consistent with the data reported for bovine patellar cartilages [142, 145, 146,

148]. According to the literature, with increasing strain-rate, the stiffness of cartilage

increases and then approaches an asymptotic value at large strain-rates [142,

150].Similar to the results in the literature, the experimental results (Figure 4.2(a)) of

the current study indicated that the mechanical behaviour of kangaroo shoulder

cartilage is strain-rate-dependent, with tissue being increasingly resistive to

deformation and loading-rates as implied by the increase in tissue stiffness with

strain and strain-rate (Figure 4.2(b)).

Figure 4.2 (a) Strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage indicated by nominal stress-strain data; (b) Stiffness variation with strain and strain-rate – Stiffness was calculated by force divided by the indentation area and by displacement divided by the cartilage’s original thickness


Repeated measures analysis of variance (ANOVA) showed that the amount of

strain and strain-rate applied on the cartilage significantly affected the tissue

response (p<0.005). Further, Tukey’s pairwise comparison test showed that the

stiffness values at all levels of strain and strain-rate were significantly different

(p<0.005). The stiffness values reported by Langelier and Buschmann [148] for

bovine patella cartilages under different strain-rates (5x10-4/s, 5x10-3/s and 5x10-2/s)

are higher than the stiffness values in the present study (p<0.05). Nonetheless, these

differences are reasonable due to the fact that patellar cartilage bears high

compressive loading compared to shoulder cartilage in vivo. Apart from that,

differences in species may also contribute to the differences. It is noted that, despite

tight control in sample selection and experimental set-up, a relatively large standard

deviation was observed in the experimental data. However, this does not seem

unusual when looking at the standard deviation in the reported experimental data for

human shoulder cartilage [177]. Therefore, the large standard deviation is most likely

due to inherent biological variations in the samples. Throughout the thesis, the

average data of the samples with the corresponding positive standard deviation is

illustrated in figures where necessary.

As mentioned in Chapter 2, upper limb cartilage tissue such as shoulder

cartilage has noticeably low modulus in compression than in tension, differing even

up to two orders of magnitude [178]. The reasons for and implications of these

differences are still under investigation [156]. Considering similar observations in

other tissues such as tendons and ligaments, which are primarily loaded in tension, it

is postulated that the lower compressive loading experienced by these tissues is the

primary reason for this difference [156]. This disparity between tensile and

compressive properties (tension–compression nonlinearity) may have significant


implications for the mechanical behaviour [179, 269] and the initiation and

progression of osteoarthritis [270].

Taking into account the considerable differences in compressive loading

experienced by knee and shoulder cartilage, in future, kangaroo may provide a

potentially suitable animal model to investigate the origins of the disparity between

the tensile and compressive properties and its effect on cartilage behaviour and

health.

4.4.3 Solid–fluid interaction and its effect on the strain-rate-dependent behaviour

As mentioned in Chapter 2, articular cartilage is a fluid-saturated tissue with water-

swollen proteoglycans constrained by a three-dimensional collagen meshwork. The

interplay between solid and interstitial fluid is known to contribute significantly to

the mechanical behaviour of cartilage tissues [149]. For example, investigations on

the strain-rate-dependent behaviour of bovine patellar suggest that 70–80% of the

load is supported by the collagen meshwork at low strain-rates (10-4/s) [149] while

the fluid contributes a similar percentage at moderately large strain-rates (10-2/s)

[144, 149]. There have been claims that the drag forces introduced by permeability

reduction and solid–interstitial fluid frictional interactions contribute largely to

strain-rate-dependent behaviour [142, 149]. Therefore, looking at the characteristic

stiffness variation with strain and strain-rate in the present study, it was anticipated

that the interaction between the solid and fluid components could fully explain the

behaviour of the kangaroo shoulder cartilage tissue.

The solid–fluid interaction of cartilage tissue is often investigated using FE

models due to experimental difficulties in investigating the tissue’s internal

behaviour [144-146]. The most commonly used FE models, as discussed in the

literature review (Chapter 2), are poroelastic models based on Mixture theory [183],


Biot’s theory [182] and fibril-reinforced models [179] or their extensions for large

deformation. In this study, we used the extension to Biot’s theory proposed by Simon

[195] , which accounts for the large deformation behaviour of the solid skeleton. This

theory is summarised in the following section.

4.5 POROHYPERELASTIC FIELD THEORY FOR SOFT BIOLOGICAL TISSUES

The governing equations of the porohyperelastic field theory proposed by Simon

[195], Kaufmann [271] and Ayyalasomayajula and Vande Geest [256] are

summarised in this section. Porohyperelastic field theory assumes that biological

tissues can be represented as a porous incompressible solid skeleton (s) statured with

an incompressible fluid (f). The solid skeleton is hyperelastic in nature. The fluid is

free to move relative to the solid depending on the solid deformation behaviour and

friction [271]. Further, the pores are assumed to be small. Therefore, the material can

be viewed as a continuum.

Further, the pores are assumed to be small. Therefore, the material can be viewed as

a continuum.

According to porohyperelastic field theory:

fs dVdVdV += (4.1)

where V is the volume of individual solid and fluid components. The porosity ( n )

and void ratio ( e ) is defined as:

)n(JdVdVn

f

0

1 11 −−== − ;0n is the initial porosity (4.2)

nn

dVdVe

s

f

−==

1 (4.3)


The deformation gradient ( F ) and the volume ratio ( J ) is given by:

I

iiI X

F∂∂

=χ (4.4)

)det(F=J (4.5)

where χ is the configuration map, which maps, at each time, t , points

),,( 321 XXXX = in the reference configuration to a point ),,( 321 xxxx = in space,

that is, ),( tXx χ= .

The governing equations when expressed using Lagrangian description are as

follows:

• Conservation of linear momentum

0=∂∂

I

iI

XT ( IiiI TT ≠ ) (4.6)

Here, T is the first Piola-Kirchhoff stress.

• Conservation of fluid mass (Darcy’s law)

−=

j

f

ijfs

i dxdkv π~ ; )(0 efkkij = (4.7)

Here, the velocity of the fluid relative to the solid sffs ννν −= and the

filtration velocity )(~ sffs n ννν −= . In Eq. (4.7), fπ and k are excess pore

fluid pressure and hydraulic permeability, respectively. In addition, given that

permeability is a function of deformation, it depends on the void ratio (the

relationship between k and e is mentioned in Section 4.3.1.2). The parameter

0k is the tissue permeability at an undeformed state.


• Conservation of total mass

Neglecting the inertial terms, the equation of the balance of mass is:

0])1[( =+− fs nndiv νν (4.8)

Hence,

0)]([)( =−+ sfs ndivdiv ννν (4.9)

Using the definition of filtration velocity:

0)~()( =+ fss divdiv νν (4.10)

• Effective stress principle

ijfeff

ijtotalij δσσ π−= ;

=01

ijδjiji

≠= (4.11)

ijfeff

ijtotalij HJSS π−= (4.12)

where total

ijσ , eff

ijσ are the total Cauchy stress and effective stress of the solid

skeleton, respectively. The corresponding components of the second Piola-

Kirchhoff stress are totalijS and eff

ijS . Here, H is the Finger strain which is

given by 11 −−= JkIkIJ FFH . The eff

ijσ is calculated from the drained effective

strain energy density function ( eW ) as follows:

TJj

effIJiI

effij FSFJ 1−=σ , T

JjIJiIeffij FJFS −−= σ1 (4.13)

ij

e

ij

eeffij E

WCWS

∂∂

=∂∂

= 2 (4.14)


The Green strain tensor )(21 ICE −= and FFC T= is the right Cauchy–

Green deformation tensor. The drained effective strain energy potential for

Isotropic hyperelastic material can be written as:

),,( 21 JIIWW ee = (4.15)

where 1

3/2

1 IJI −= , 2

3/2

2 IJI −= and )(1 CtrI = , )(2 CCtrI = .

According to the above theoretical framework, the FE model was initially

developed to explore the suitability of porohyperelastic modelling for investigating

the solid and fluid behaviour of cartilage tissue as set out in Chapter 3 (Section

3.3.2). The results indicated that the developed FE model is acceptable for studying

the solid and fluid behaviour inside the tissue.

4.5.1 Porohyperelastic FE model development for indentation test

After confirming the suitability of the modelling, the porohyperelastic FE model for

indentation tests was developed in ABAQUS 6.12, similar to the model developed in

Chapter 3. Axisymmetric elements were adopted to reduce the computational cost

based on the characteristics of the test sample and loadings. The FE mesh consisted

of 9600 4-node bilinear displacement and bilinear pore pressure elements. The

number of elements was decided based on the numerical tests performed earlier

(Chapter 3, Section 3.3.15). Large deformations and geometric nonlinearity were

considered in the calculation using the ‘NLGEOM’ option in ABAQUS 6.12.

Transient consolidation analysis with the ‘Full Newton’ solution procedure was used

to solve the equilibrium equations. The pore pressure (p) (p=0) boundary condition

was enforced on the upper surface of the portion—where the indenter does not touch

the cartilage surface—and on the right side of the cartilage so as to enable flow of


fluid through these boundaries. The surface-to-surface contact between the cartilage

and the indenter was modelled as frictionless.

The impermeable boundary between the indenter and cartilage does not require

special boundary conditions since it is a default boundary condition in ABAQUS

6.12 and has been previously used to model the contact between cartilage and rigid

indenters [185, 252]. Given that the stiffness of the indenter and bone is several

orders of magnitude higher than that of the cartilage, both were modelled as rigid

bodies. Preliminary investigation indicated that representing the bone and indenter as

rigid bodies did not affect the results of the simulations.

4.5.1.1 Solid skeleton material model

To account for the nonlinear large deformation, the solid skeleton was modelled as

an isotropic hyperelastic material. For isotropic hyperelastic materials, the decoupled

potential with linear bulk modulus (κ ) small or of the same order of magnitude to

that of the linear shear modulus (µ ) would impose compressibility on the material.

In fact, Simon and Kaufmann [257] and Ayyalasomayajula and Vande Geest [256]

also used similar formulations in their studies. Hence, this study used the decoupled

formulation by treating cartilage as an isotropic material. However, it is important to

mention that, in an anisotropic model, the use of the decoupled formulation would

generally yield inaccurate results [272, 273].

The lower-order material models such as the neo-Hookean or Mooney–Rivlin

were identified as incapable of representing the highly nonlinear stress-strain

behaviour observed during this study (Figure 4.3(a)). Higher-order models such as

the Yeoh model are considered more suitable for explaining the nonlinearity of

cartilage tissues [274]. However, the 2-term reduced polynomial hyperelastic model

gave an accurate description of the material behaviour for the cartilage samples


tested in this study (Figure 4.3(b)). Due to having few parameters, unlike models

such as the Yeoh model, the 2-term reduced polynomial model can be used to obtain

unique sets of material parameters. The hyperelastic material parameters were

obtained based on Eq. (3.14) developed in Chapter 3. The form of the 2-term reduced

polynomial model used in the present study is:

2

1

2

120110 )1(1)3()3( −+−+−= JD

ICICW e (4.16)

As mentioned earlier, here, eW is the isotropic elastic strain energy potential, 1I is

the first invariant of the distortional part C of the right Cauchy deformation

tensor C , and Fdet=J is the volume ratio. Furthermore, µ210 =C , where µ is the

shear modulus of linear elasticity, and 20C is a nonlinear stiffness parameter. In

addition, κ21 =D , where κ is the bulk modulus of linear elasticity.

Figure 4.3: (a) Experimental data from 10-2/s of a representative sample fitted to neo-Hookean, Mooney–rivlin and 2-term reduced polynomial incompressible hyperelastic functions; (b) R-squared values indicating the goodness of fit of neo-Hookean, Mooney–rivlin and 2-term reduced polynomial incompressible hyperelastic functions to the experimental data


4.5.1.2 Permeability variation with strain

Under compressive strain, the permeability ( k ) of cartilage decreases exponentially

(Eq. (4.17)) as mentioned earlier [191, 258, 259]. In Eq. (4.17), e is the void ratio

(i.e. the ratio of the volume of pores to the volume of solid), which is a quantity

representing dilatation, while 0e is the initial void ratio. The parameter 0k is the

initial undeformed state permeability and M and m are dimensionless material

parameters. The parameters 0e , M and m were chosen to be 4.0, 4.638 and 0.0848

[191], respectively, due to the extensive use of these values in the cartilage

literature. Eq. (4.17) is expressed as follows:

−

++

= 1

e1e1

2Mexp

eekk

2

0

m

00 (4.17)

During the study it was noted that the porohyperelastic model with strain-

dependent permeability was insufficient to capture the strain-rate-dependent tissue

behaviour (discussed in Section 4.7.2). It was postulated that the fluid behaviour

might significantly affect the tissue behaviour depending on the strain-rate/loading

velocity. Therefore, the permeability function that takes into consideration the effect

of the strain-rate was introduced, as detailed in the next section.

4.5.2 Permeability variation with strain-rate

The permeability of cartilage is not only dependent on strain, but is also a function of

applied pressure difference [259]. A higher pressure difference would result in

smaller permeability. This is due to the pressure drag forces that are developed when

the pressure difference is increased, which restricts the fluid movement [259].

According to Oloyede and Broom [149], as strain-rate increases, the pore pressure

inside the cartilage also increases. Therefore, an increase in pressure difference


inside and outside of the tissue is expected with an increase in strain-rate. This results

in a reduction of permeability. To the best of the author’s knowledge, a permeability

function that considers this phenomenon has not been reported to date. Nevertheless,

the following section re-analyses the data presented by Lai and Mow [259] and

Oloyede and Broom [149] and introduces a new mathematical relationship (Section

4.6) that represents the permeability variation with strain and strain-rate. In addition

to applied strain, the mathematical relationship illustrates that permeability decreases

with an increase in strain-rate.

The obtained permeability function, that is, the strain-rate-dependent

permeability, was included in the porohyperelastic framework and was compared

with the porohyperelastic models, which include constant permeability and strain-

dependent permeability, in order to comprehensively investigate the effect of fluid

behaviour on the sold-fluid interaction of kangaroo shoulder cartilage tissues.

Throughout the rest of this thesis, the porohyperelastic model with strain-dependent

permeability and the porohyperelastic model with strain-rate-dependent permeability

are referred to as the strain-dependent model and strain-rate-dependent model,

respectively.

4.6 EXTENSION OF POROHYPERELASTIC FIELD THEORY: STRAIN-RATE-DEPENDENT PERMEABILITY FUNCTION

Data from studies by Lai and Mow [259] and Oloyede and Broom [149] were used to

obtain the relationship along with certain approximations which are specified below.

Through experiments, Mow and Lai [96] found that permeability is a function of

strain and applied pressure difference ( P ). An exponential relationship for

permeability has been reported for infinitesimal strain [259]. This equation has been

further extended for large strains [191, 258].

The isotropic permeability tensor (k ) can be expressed as:


Ik k= (4.18)

where I is the unit tensor and k is the scalar valued permeability function.

The k can be represented by the following equation, where permeability is an

exponential function of J , the volume ratio [191, 275].

( )2/)1(exp 2 −= JaMk (4.19)

The data from Mow and Lai [96] can be fitted to Eq. (4.19) for each pressure

difference ( P ) (Figure 4.4(a)) to obtain the corresponding a and M values

depending on the applied strain and pressure difference. At a high value of P , due to

large pressure drag forces, fluid velocities become considerably small and hence the

fluid will be contained inside the tissue. This will reduce the tissue permeability to

almost zero. Therefore, at this pressure value, a and M will be almost zero. The

resulting variation of a vs M (Figure 4.4 (b)) can be approximated by a second-

order polynomial function in the form of Eq. (4.20), where α and β are empirical

constants:

2aaM βα += (4.20)

The P value at which coefficient a becomes almost zero is not available in

the literature. Therefore, we assumed this P to be a high physiological joint contact

pressure (e.g. contact pressure during high-speed running). Contact pressure inside

the knee during high-speed running (5-10.5 m/s) is approximately 3.5 times [91, 92]

t the static contact pressure. This assumes that the ground reaction forces are

proportional to the joint contact pressures. The reported static mean contact pressure

values in the knee are 2.75–3.79 MPa [276-278].


Therefore, P at which a becomes zero was taken as 13.625 MPa. The

variation of P vs a was approximated by a power relationship (Eq. (4.21) and

Figure 4.4(c)), whereg , δ and λ are empirical constants. In this derivation, we

have used simple functional forms that can represent the relationship between

different variables. Some researchers may prefer to use other functional forms which

are also correct. Eq. (4.21) is expressed as follows:

λg δ += Pa (4.21)

Figure 4.4: An exponential function (Eq. 4.19) fitted to Lai and Mow’s (1980) data; (b) Variation of coefficient M with coefficient a is approximated as a second-order polynomial function; (c) Variation of coefficient a with pressure difference (P) approximated as a power function

Re-analysis of Oloyede and Broom’s [149] data suggests that the internal pore

pressure of cartilage increases—under compression—with increasing strain and

strain-rate (Figure 4.5(a)). This increase in pore pressure values results in increased


pressure differences between the inside and outside of the loaded area of the tissue.

Assuming that the internal pore pressure is proportional to P , an approximate

relationship between P , the strain-rate and strain can be obtained (Eq. (4.22)):

2/1)1( DJP −= φ (4.22)

Here, φ is an empirical constant and D is the rate of deformation. The deformation

rate tensor, )(νD grad= (i.e. jiij xD ∂∂= υ ).

Combining Eq. (4.19) and Eq. (4.22), a mathematical relationship can be

obtained for permeability (Eq. (4.23)), where permeability is a function of strain and

strain-rate:

( )2/)1(exp)( 2 −+= Jaaak βα where λg δ += Pa (4.23)

The values of the empirical parameters obtained using the data of Lai and Mow [259]

and Oloyede and Broom [149] are: α =0.0827, β =0.1071, φ =350.27,λ =-6.399,

g =7.942, and δ =-0.0791. Based on the obtained parameters, we predicted the

variation of permeability in terms of strain and strain-rate as shown in Figure 4.5(b).

The permeability was found to be decreasing with both strain and strain-rate.

Figure 4.5: (a) Re-analysis of Oloyede and Broom’s [149] Variation of pressure difference (P) between the inside and outside of the tissue with strain-rate; (b) Variation of permeability with strain-rate as predicted by Eq. (4.23)


4.6.1 Material parameter identification

There were four material parameters, namely,10C ,

20C , 1D and0k , to be estimated

(assuming all of the above parameters are constant) in the current porohyperelastic

model. In order to obtain them, the following procedure was employed:

• Following the approach developed by Simon et al. [279], considering the

material as incompressible at the highest strain-rate (10-2/s), 10C and

20C were

obtained by fitting the force–indentation experimental data to Eq. (3.14)

derived in Chapter 3.

• Using 10C and

20C determined in the previous step, parameters 1D and

0k were obtained by fitting the experimental data on force–indentation at the

lowest strain-rate (10-4/s) to a porohyperelastic FE model, considering the

material to be compressible.

The obtained parameters were used to predict the strain-rate-dependent

behaviour of the cartilage tissues and were compared with the experimental results.

Based on the performance of the three porohyperelastic models—constant, strain-

dependent, and strain-rate-dependent—the effect of solid–interstitial fluid interaction

on strain-rate-dependent behaviour was evaluated.

4.7 RESULTS AND DISCUSSION

4.7.1 Biomechanical parameters of kangaroo shoulder cartilage

The 2-term reduced polynomial hyperelastic function fitted well to high strain-rate

data (R2=0.9890±0.0044, p<0.000). The obtained stiffness parameters (i.e. 10C

and20C ) were 0.0988±0.0622 MPa and 0.1482±0.061 MPa, respectively. The FE

porohyperelastic model also fitted well to the low strain-rate data

(R2=0.9855±0.0098, p<0.000). The obtained compressibility parameter ( 1/1 D ) and


the permeability (0k ) in an undeformed configuration were 0.0782±0.055 MPa and

1.32±0.98 x 10-14m4/Ns, respectively.

The hyperelastic material parameters for human shoulder cartilage tissues have

not been reported elsewhere. Nevertheless, considering the reported Poisson’s ratio

for shoulder cartilage tissue, which is approximately 0.15 [226, 280], Young’s

modulus (E) for kangaroo shoulder cartilage was estimated to be 0.454±0.286 MPa.

The calculated Young’s modulus (Eq. (4.24)) for human shoulder cartilage using

Huang et al.’s [177] and Mow et al.’s [28] modulus in uniaxial strain (HA) were 0.214

MPa and 0.624 MPa, respectively. Eq. (4.24) is expressed as follows:

υ)υ)((υ)E(H A 211

1−+

−=

(4.24)

The Young’s modulus of kangaroo shoulder cartilage was not significantly

different (p=0.109) from the value calculated in Mow et al.’s [28] study; however, it

was significantly different (p<0.05) from the value calculated in Huang et al.’s [177]

work. Nevertheless, the average value falls within the values calculated for human

shoulder cartilage. The average thickness of the kangaroo shoulder cartilage samples

obtained through ultrasound measurements was 0.72±0.10 mm. The reported average

thickness value for human shoulder cartilage is 1.44 mm [174], which is higher than

that of kangaroo cartilage (p<0.005). Considering the aforementioned differences in

thickness and potential differences in the tissue composition of different species we

would consider the average E value obtained in this study to be acceptable. The

permeability value of the kangaroo humeral head cartilage was relatively low, but

was not significantly different (p=0.145) from the value reported for the central

region of human humeral head cartilage, which is 1.82±1.27x10-14 m4/Ns [177].


The biomechanical properties and behaviour of kangaroo shoulder cartilage

were in general agreement with that of human shoulder cartilage, indicating that

kangaroo can be considered as a potential animal model for shoulder cartilage

research in the future. However, extensive experimentation (histological,

biochemical assessment etc.) to investigate the development and degradation of this

tissue is required in order to confidently use kangaroo as an animal model to

investigate the pathologies related to shoulder cartilage.

4.7.2 Comparison of constant, strain-dependent and strain-rate-dependent model predictions

The average experimental stress-strain data were compared with the porohyperelastic

FE prediction, for constant, strain-dependent and strain-rate-dependent models

(Figures 4.6(a), 4.6(b) and 4.6(c), respectively). In general, all the models were

sensitive to the effect of strain-rate, indicating the ability of the poromechanics

framework [182, 195, 281] to capture the strain-rate dependency. The models with

strain-rate-dependent and strain-dependent permeability outperformed (p<0.05) the

model with constant permeability at all strain-rates (Figure 4.6(d)). At intermediate

strain-rates, statistically significant differences (p<0.05) were identified between the

constant-permeability-model and the predictions of the other two models. This

difference was even more significant when a similar comparison was made at the

highest strain-rate (p<0.005), that is, at 10-2/s.

The predictions of the strain-rate-dependent model were better than the

predictions of the strain-dependent model at all strain-rates (Figure 4.6(d)). However,

statistical differences were not identified between the predictions of the strain-

dependent and strain-rate-dependent models at 5x10-3/s (p=0.179), although at 5x10-

4/s they were significantly different (p<0.05). Nevertheless, compared to the strain-

dependent model (R2=0.7937±0.1478), the strain-rate-dependent model


(R2=0.8915±0.0662) was significantly better at predicting the stress-strain variation

at the highest strain-rate (p<0.005).

Figure 4.6: Comparison of constant, strain-dependent and strain-rate-dependent model prediction to average (n=10) experimental data of the samples tested – (a) Constant permeability; (b) Strain-dependent permeability; (c) Strain-rate-dependent permeability; (d) Model predictions in terms of R-squared (R2) values and the corresponding significant differences among constant, strain-dependent and strain-rate-dependent models at individual strain-rates

4.7.3 Effects of strain-dependent and strain-rate-dependent permeability

In comparison with the model with constant permeability, strain-dependent

permeability takes into account the shrinkage of pores (Figures 4.7(a) and 4.7(b)) and

its concomitant effect on permeability during tissue deformation. Due to the

reduction in pore size (i.e. reduction of effective flow area) with deformation, it

becomes difficult for fluid to move out of the tissue. The reduction of tissue


permeability leads to an increase in solid–interstitial fluid frictional interactions. This

could be the reason why both the strain-dependent and strain-rate-dependent models

significantly outperformed the FE model with constant permeability (p<0.05) at all

strain-rates.

Figure 4.7: An ideal representation of part of a tissue with pores represented by circles (undeformed) and ellipse (deformed); (a) Constant permeability – Pore volume/effective fluid-flow area does not change; (b) Strain-dependent permeability – Pore volume/effective flow area is reduced due to application of strain (ε); (c) Strain-rate-dependent permeability – Large pressure differences due to suddenly applied load (Tt2<<<Tt1) result in larger drag forces; this will compact the tissue to reduce the pore size (indicated by the red hatched area), creating congestion for fluid particles to move through pores and, therefore, the fluid particles experience a reduction of pore size/effective flow area

As noted above, when the effect of strain-rate was considered, the effect of

solid–interstitial fluid interaction on strain-rate-dependent behaviour was more

significant. In two cases, namely, (b) (Figure 4.7(b)) and (c) (Figure 4.7(c)), the

tissue was deformed to a strain ε at a time Tt1 and Tt2 (<<<Tt1), respectively. In case

(c), due to the sudden application of strain, fluid may experience large pressure

differences in comparison to case (b). Due to this, in case (c), there will be a rush of

fluid to move away from the deformed areas to other parts of the tissue. Meanwhile,

due to high pressure difference there will be higher pressure drag forces inside the

tissue, leading to compaction of the tissue matrix [183, 239, 259]. The compaction of

the cartilage tissue matrix was theoretically predicted and explained by Lai and Mow


[259]. Due to tissue compaction, in addition to the effect of strain, the pore size also

further decreases; hence, fluid particles will experience a reduced effective flow area

(Figure 4.7(c)). The compaction coupled with the rush of the fluid to move out of the

deformed area creates more congestion for the fluid particles moving through the

pores in case (c), reducing the permeability as predicted by the strain-rate-dependent

permeability. Therefore, when the strain-rate is increased from low to high, at a

certain strain-rate, the pressure drag force may start to affect the tissue behaviour

significantly. This could be the reason why the strain-rate-dependent model

performed significantly better in capturing the experimental results at the highest

strain-rate tested (p<0.005) compared to the strain-dependent model. Therefore, in

addition to the effect of strain on permeability, in order to better explain the tissue

behaviour at high strain-rates—where pressure drag forces become significant—the

effect of strain-rate on permeability can be taken into account in future FE models.

4.7.4 Mechanisms underlying the strain-rate-dependent tissue behaviour

Based on the above observations, this section summarises the solid–fluid frictional

interactions and the pressure drag forces as some of the possible mechanisms

underlying the strain-rate-dependent behaviour of kangaroo shoulder cartilage

tissues.

Solid–fluid frictional interactions: In the present study, fluid was considered to be

inviscid, that is, its viscosity manifests itself only in the fact that there is a non-zero

resistance to fluid flow, which suggests that the permeability is not infinite.

However, since there is no other viscous effect, the fluid can only bear hydrostatic

Cauchy stresses (i.e. no viscous shear stress in the fluid). Therefore, the solid–fluid

frictional drag forces depend on the tissue permeability. The model with constant

permeability had a finite permeability value and was sensitive to strain-rate—thus,


indicating the presence of frictional interaction between the solid and fluid. The

reduction of permeability with strain will increase the magnitude of frictional

interactions. This was reflected by the increased sensitivity of the model with strain-

dependent permeability to strain-rates. Therefore, it was concluded that the frictional

interactions between solid and fluid can be stated as one of the mechanisms

facilitating the strain-rate-dependent behaviour.

Figure 4.8 : Comparison of pore pressure and velocity profiles at 10-2/s – (a) Strain-dependent permeabilty; (b) Strain-rate-dependent permeability; (c) Fluid velocity at the bottom left (point P) of the cartilage matrix

Pressure drag forces: The strain-rate-dependent model showed higher pore pressure

values than the strain-dependent model (Figures 4.8(a) and 4.8(b)). The smaller fluid

velocities observed in the former model reflected the effect of the higher drag forces

and generated due to the higher pressure difference (Figure 4.8(b)). Hence it can be

stated that that, at high strain-rates, the strain-rate-dependent permeability enhances

the fluid pressurisation. This enables the tissue to respond to large strain-rates more


effectively, such that excessive deformation of the tissue is minimised. Therefore, the

strain-rate-dependent fluid behaviour can be stated as one of the mechanisms that

support the load-bearing of cartilage tissue and is significantly prevalent at large

strain-rates.

4.7.5 Role of cartilage as a protective layer at large strain-rates

As mentioned previously (Section 4.7.3), at 5x10-3/s strain-rate, the strain-dependent

model prediction was not significantly different from the strain-rate-dependent

model, but when the strain-rate was increased to 10-2/s it became significantly

different. Similarly, Oloyede and Broom [149] observed a significant increase in the

effective stress of the cartilage solid skeleton in comparison to the pore pressure

increase when the strain-rate was increased from 10-3/s to 10-2/s. This is believed to

be due to the same phenomenon of the increase in pressure drag, which reduces the

fluid movement at high strain-rates. Also there is a possibility that inertia forces

might begin to affect the fluid behavior at very large strain-rates which could further

impede fluid movement inside the tissue. The ability of cartilage tissue to contain the

fluid inside can be attributed to its small pores that are in the range of 20–65 Å in

their undeformed state [100, 202, 282]. The pore size of the tissue in the undeformed

state was calculated based on the formulation described in the next section.

4.7.5.1 Pore size calculation based on permeability

The network of pores in the cartilage tissue determines the fluid behaviour and

permeability. The pore size can be considered as a microstructural parameter of the

tissue. In order to understand the fluid behaviour inside the tissue, the pore sizes

were calculated and matched with the tissue behaviour. The calculation was based on

Maroudas’s [100] study as summarised next.


Consider cartilage as a porous material, comprising of network of pores with an

average pore radius (r) and tortuosity (τ ). The path of the fluid movement due to

pressure difference ( dP ) in cartilage tissue is likely to be tortuous. The path of the

fluid movement in a porous structure is also likely to be tortuous. Therefore, the true

pressure gradient, accounting for tortuosity, can be written as:

e

e

dLdP

LL

dLdP

= , where P is the pressure (4.25)

Here, LLe is the ratio between the true path length and the Darcian length. Applying

the Poiseuille equation to the pore capillaries, the velocity of flow ( fv ):

e

f LL

ddPr

ddPrv

L 8L 8

2

e

2

−=

−=

ηη (4.26)

Here, η is the viscosity of the fluid. The velocity of the flow is related to the fluid

flux ( q ) and porosity or the fractional water content ( H ) by:

LL

Hqv e

f = (4.27)

Combining Eq. (4.26) and Eq. (4.27), the fluid flux is:

dLdP

LLHrq

e

22

8

−=

η (4.28)

By comparing Eq. (4.28) with Darcy’s law, the following equation for

permeability can be obtained:


ητ 81

2

2

=

Hrk ;LLe=τ (4.29)

In this study, the volume fraction of the water )(H , tortuosity of the flow path(τ ) and

fluid viscosity )(η were taken as 0.8, 1.4 and 10-3 Ns/m2, respectively, considering

the values reported in the literature [100].

Based on Eq. (4.28) in the above formulation, the pore size of the tissue in an

undeformed state was 154.55±46.1 Å. The pores which are 10–50 times the size of a

water molecule (approximately 3 Å) reduces further under deformation. Hence,

depending on the pressure gradient at different strain-rates, the movement of the fluid

inside will be reduced. This containment of fluid inside the tissue at large strain-rates

will provide protection to the cartilage and underlying bone by reducing the

excessive deformation of tissues. Therefore, the reduction of permeability with the

strain-rate plays an important role at high strain-rates. However, in the case of

osteoarthritis, for which the proteoglycan content is reported to be low, the pore size

of the tissue can be relatively high and thus can interrupt this phenomenon. This will

result in excessive deformation of the tissue in comparison to a healthy tissue, and

thus increase the risk of bone-to-bone contact and tissue damage.

4.7.6 Limitations of the strain-rate-dependent permeability model and possible improvements to the FE porohyperelastic model

It is important to assess the limitations and assumptions under which the

mathematical expression of strain-rate-dependent permeability has been formulated

and the possible implications of the assumptions. Currently, there are no practical

methods available to directly measure the fluid flow rates inside cartilage tissue

under different loading-rates. The indirect method, as employed in the present study,

is to use fluid pressure measurements inside the tissue under different strain-rates and


relate them to available static permeability measurements under different pressure

gradients. In the static permeability measurement, a pressure gradient is imposed on

already compressed cartilage and the amount of fluid outflow is measured at

equilibrium. When the tissue is compressed at a certain loading-rate, the fluid

pressure in the loaded area will increase and there will be a pressure gradient

between the loaded area and outside which happens on a timescale smaller than that

of static measurements. Additionally, during compression, fluid pressure in the

loaded area continuously changes and is non-uniform. Therefore, static permeability

measurements extracted at different pressure gradients do not represent the actual

conditions ideally and hence may affect the permeability values predicted by the

strain-rate-dependent permeability model. However, the extent to which the

assumptions affect the strain-rate-dependent model predictions requires more

investigations which could be potentially carried out in the future if a methodology

can be devised to measure the fluid velocities inside cartilage under different

loading-rates..

The strain-rate-dependent model did not fit well to the stress-strain response at

the highest strain-rate (10-2/s) and some low strain-rates such as 5x10-4/s. Although

the main focus of the present study was not to present a comprehensive FE model to

predict the experimental data, this can be stated as one of the limitations of the strain-

rate-dependent model. Given that in the present study we have fully evaluated the

isotropic fluid and solid behaviour, the model could be possibly improved by

incorporating anisotropic fluid behaviour, anisotropy of the collagen network and/or

the viscoelasticity of the tissue. Earlier studies have shown that fluid pressurisation is

enhanced by anisotropy of the elastic properties of the tissue [156, 283].

Furthermore, the anisotropy of cartilage permeability due to the glycosaminoglycan


network deformation [275, 284, 285] and the collagen fibre orientation [272, 286-

290] affects the fluid pressurisation at both small and large strains. Additionally, as

mentioned earlier, there is evidence that the flow-independent viscoelasticity of the

cartilage matrix affects the strain-rate-dependent behaviour of the tissue at small and

large strain-rates [146, 150, 156]. Hence, the lower stresses predicted by the strain-

rate-dependent model at low strain-rates, for example at 5x10-4/s, might be improved

by the inclusion of matrix viscoelasticity in the model.

4.8 CONCLUSION AND REMARKS

In this study, by introducing kangaroo as an animal model we have explored the

strain-rate-dependent mechanical behaviour and the underlying mechanisms of

shoulder cartilage. By introducing the strain-rate-dependent permeability model and

comparing the model’s predictions with constant and strain-dependent models, the

present study explored how the solid–interstitial fluid interaction facilitates the

strain-rate-dependent behaviour of shoulder cartilage tissues and its physiological

relevance. The following conclusions were made based on the results of the current

study:

• Kangaroo can be considered as potentially suitable animal model for future

biomechanical research on shoulder cartilage. This is because the

biomechanical properties and behaviour of kangaroo cartilage tissues are in

general agreement with that of human shoulder cartilage tissues.

• Further, the different loadings encountered by the upper and lower limb

cartilage of kangaroo provide a natural source for investigating how

mechanical forces affect the development, composition (e.g. proteoglycan

distribution) and structure (e.g. collagen architecture) of cartilage, and the

progression of osteoarthritis. In addition, experimentations on this animal


model may also have the potential to give insights into how tissue-

engineering strategies must be adjusted to develop joint-specific tissues.

• The mechanical behaviour of kangaroo shoulder cartilage is strain-rate-

dependent and nonlinear. Its solid skeleton behaviour can be adequately

represented by the 2-term reduced polynomial hyperelastic model. However,

lower-order material models such as the neo-Hookean and Mooney–Rivlin

models were found to be inadequate to explain the nonlinear solid skeleton

behaviour of the tissue.

• In addition to strain, permeability has a dependency on strain-rate: it

decreases when the strain-rate is increased.

• Both constant and strain-dependent models are sensitive to strain-rates.

Further, strain-dependent models were found to outperform the constant

permeability model. Therefore it can be said that solid–fluid frictional

interaction is one of the main reasons for strain-rate-dependency.

• This study found that both strain-dependent and strain-rate-dependent models

significantly affect the tissue behaviour. At high strain-rates, the latter model

becomes more significant than the former. Therefore, it can be concluded that

at high strain-rates in addition to solid–interstitial frictional fluid interaction,

pressure drag forces and possibly inertia forces begin to play a significant

role in the tissue behaviour.

• Based on an earlier study, where a transition of tissue behaviour was

observed at 10-2/s [149], we postulate that this phenomenon could be due to

the small pore size of the cartilage (in the order of 10-9m) and its size

reduction under deformation. The pores facilitate the ability of cartilage

tissues to contain the fluid within the matrix at large strain-rates, and thereby


to effectively reduce excessive deformation. This assists the tissues to

function as a protective layer for bone-ends during injurious loads at high

strain-rates.

• Based on the findings of this study, it can be concluded that FE models will

also benefit from the inclusion of strain-rate-dependent permeability to better

predict the cartilage response.

• Since all aspects of the isotropic fluid and solid behaviour were evaluated in

the present study, the model deviations at the highest strain-rate can be

attributed to the anisotropic solid, fluid properties and viscoelasticity of the

matrix.

The introduction of kangaroo as a model for shoulder cartilage investigation, the

mathematical expression for strain-rate-dependent permeability and the strain-rate-

dependent FE model employed in the present study provide insights and open new

avenues for investigating the mechanisms underlying the strain-rate-dependent

mechanical behaviour of cartilage tissues. However, since the FE model developed in

this study was unable to fully explain the tissue behaviour, the factors affecting the

strain-rate-dependent behaviour of kangaroo shoulder cartilage tissue were further

analysed as reported in the following chapter.


Chapter 5: Effect of proteoglycan and superficial collagen on the strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage

This chapter begins with a brief introduction to the investigations reported in the

literature on the role of cartilage tissue constituents on mechanical behaviour

(Section 5.1). The aims and objectives of this part of the study and the hypotheses are

then discussed (Sections 5.2 and 5.3, respectively). The experimental methodology is

set out (Section 5.4), followed by the results and discussion (Section 5.5). Lastly, the

conclusions and recommendations for follow-up studies are provided (Section 5.5).

The study in this chapter resulted in a journal article named “Physical mechanisms

underlying the strain-rate-dependent mechanical behavior of kangaroo shoulder

cartilage” in the Journal of Applied Physics letters [214].

5.1 INTRODUCTION

In Chapter 4 it was noted that the porohyperelastic model with strain-rate-dependent

permeability was unable to capture the tissue behaviour at the highest strain-rate

tested. Further, we concluded that the differences identified between the

experimental data and FE model prediction could, to an extent, be due to anisotropy

of the solid skeleton. Meanwhile, the literature has indicated that superficial collagen

considerably affects the tissue behaviour at large strain-rates [16]. Therefore, in order

to comprehensively understand the factors affecting its mechanical behavior of

kangaroo shoulder cartilage, it is important investigate how the cartilage extracellular

matrix components affect the strain-rate dependent behaviour. Hence, the

Chapter 5: Effect of proteoglycan and superficial collagen on the strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage 107

investigations in this chapter focused on the effect of cartilage constituents (i.e.

proteoglycans and collagen network) on the strain-rate-dependent mechanical

behaviour of kangaroo shoulder cartilage tissue.

The dynamic properties of cartilage (extracted at high strain-rates) are known

to be governed by the structure of the collagen network [20, 158]. Based on an FE

model that considered the cartilage structure and composition, Julkunen and Jurvelin

[16] showed that superficial collagen can considerably affect the tissue behaviour at

physiologically high strain-rates (10-1/s in their study). In contrast, the equilibrium

properties of cartilage (extracted at very low strain-rates) are mainly affected by

proteoglycans [17, 20]. It is also well accepted that the compressive properties of

cartilage are governed by the hydrated proteoglycans constrained by the collagen

network [98]. However, the extent to which the superficial layer and proteoglycans

affect the strain-rate-dependent behaviour of shoulder cartilage tissues has not been

investigated thoroughly.

While conclusions from the above studies have been made for knee cartilage in

particular, we believe they cannot be generalised to all joint cartilages due to possible

differences in the composition and microstructure of tissues which are regulated by

the different mechanical environments experienced by the tissues. Chondrocytes

dynamically synthesise the extracellular matrix (i.e. proteoglycans and collagen)

based on the external loading stimuli they receive [163-165]. Therefore,

proteoglycan composition and structural features of the collagen network potentially

adapt to external mechanical stimuli, and hence depend on the local mechanical

environment of the tissue [86, 166-171]. The conclusions of reported studies [16, 17,

20, 158] which are predominantly for knee cartilage should therefore be evaluated in

the context of the specific tissue being studied. As shoulder cartilage experiences

108 Chapter 5: Effect of proteoglycan and superficial collagen on the strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage

considerably less compressive loading, it was postulated in this study that the

collagen network (including the superficial layer) plays a more significant role in

facilitating the strain-rate-dependent behaviour of the shoulder cartilage than

proteoglycans. In order to test this belief, we carried out a series of experiments

which involved simultaneous artificial degradation of cartilage constituents

(proteoglycan and superficial collagen) and mechanical testing.

Artificial degradation through enzyme treatment is commonly used to model

proteoglycan loss and superficial collagen damage [20, 22]. The main advantage of

artificial degradation is that the level of damage to the tissue can be controlled by

enzyme concentration, enzyme type and the duration of the exposure [22]. Hence,

gradual degradation of the constituents and simultaneous assessment of the

mechanical properties can give direct insight into the contribution of proteoglycans

and superficial collagen to the strain-rate-dependent behaviour. Since enzymatic

treatments have also been used to mimic some of the characteristics of osteoarthritis

(e.g. superficial collagen degradation and proteoglycan depletion) [19, 291], the

results of this study can also assist to evaluate the effect of osteoarthritis on the time-

dependent behaviour of shoulder cartilage tissues. Because the surface lipid layer of

cartilage is also known to be affected during the early stages of osteoarthritis [292] ,

we also performed an experiment to assess the effect of surface layer on time-

dependent tissue behaviour. Since damage to the superficial collagen may also affect

the surface lipid layer, this experiment helped to further confirm the contribution of

the superficial collagen to tissue behaviour.


This part of the study was mainly focused on achieving the following objectives:


1) Investigate the role of proteoglycan in the strain-rate-dependent mechanical


2) Investigate the role of superficial collagen and surface lipid layer in the

strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage.

3) Assess whether the proteoglycan or the superficial collagen dominates the

strain-rate-dependent mechanical behaviour of kangaroo shoulder cartilage.

5.3 HYPOTHESES

As mentioned in the introduction to this chapter, this part of the study aimed to test

the following two main hypotheses:

1) Superficial collagen plays a more significant role in facilitating the strain-

rate-dependent behaviour of the shoulder cartilage than proteoglycans.

2) The contribution of superficial collagen to tissue behaviour at high strain-

rates is significantly larger than at small strain-rates.

5.4 EXPERIMENTAL METHODOLOGY

Indentation on a cartilage sample at four strain-rates (10-4/s, 5x10-4/s, 5x10-3/s and

10-2/s) requires one day for completing the testing procedure. However, during the

experimental design stage of this study, it was noted that each sample testing can

take more than a day to complete. Therefore, it was essential to design the

experimental procedure in such a way that ensured the least possible effect on the

tissues due to sample preservation. There were two methods for preserving the

samples. The first method would be to preserve the samples in a PBS-inhibitor

solution at 4 °C until the experimentations were completed. The second method

would be to immediately freeze the samples after harvesting in a PBS-inhibitor

solution and then to thaw the samples in PBS at room temperature (24–27 °C) for 30

minutes before mechanical testing. However, these methods may affect the


mechanical properties of the tissue. Therefore, in order to assess the effect of the

preservation method on the mechanical properties of the tissue, preliminary studies

were conducted as mentioned in the next section.

5.4.1 Assessment of tissue preservation methods: The PBS-solution at 4 °C vs the multiple freeze–thaw method

5.4.1.1 Effect due to preservation of sample in PBS-inhibitor solution at 4 °C

Ten visually normal (ICRS [215] macroscopic score=0) cylindrical kangaroo

cartilage plugs of 8 mm diameter with 2–3 mm subchondral bone were harvested

from the near central load-bearing area of the humeral head. The thicknesses of the

samples were estimated using ultrasound measurements. Then, indentation testing

was carried out on individual samples using a plane-ended, polished indenter of 3

mm diameter with a rounded edge of 0.1 mm radius at four different strain-rates: 10-

4/s, 5x10-4/s, 5x10-3/s and 10-2/s. The samples were indented up to 25% engineering

strain throughout the study and the same experimental procedures described in

Chapter 3 (Section 3.2.6) were used. After mechanical testing, the samples were

divided into two groups. The initial experimental design indicated that three days

were required to complete the study on the proteoglycans (Section 5.4.2.1 presents

the details on the proteoglycan study). Therefore, samples from the first group were

kept for three days in a PBS-inhibitor solution at 4 °C prior to subsequent mechanical

testing, while samples from the other group were kept for one week. Based on the

force–indentation results, the mechanical properties were extracted by fitting to Eq.

(3.14) in Chapter 3 and the effect of the preservation at 4 °C on mechanical

properties was assessed (Figure 5.1).


Figure 5.1: (a) Mechanical properties after 72 hrs in PBS-inhibitor solution at 4 °C; (b) Mechanical properties after 1 week in PBS-inhibitor solution at 4 °C

5.4.1.2 Effect of sample preservation methods: Multiple freeze–thaw cycle

In order to assess the effect of freeze–thaw cycles on the mechanical properties and

behaviour of kangaroo shoulder cartilage, mechanical tests were conducted on five

samples immediately after harvesting from the central load-bearing area of the

humeral head. Then, the samples were put in containers filled with PBS-inhibitor

solution and frozen at -20 °C overnight. The following day, the frozen samples were

thawed for 30 minutes in the PBS solution at room temperature (24–27 °C), after

which the mechanical tests were conducted. This entire procedure was repeated

thrice in the next three days. Samples were tested at one strain-rate (10-2/s); based on

the literature, this was considered enough to ascertain the effect of the freeze–thaw

cycles on the mechanical properties of the tissue [217]. After testing, Young’s

modulus was extracted from the force–indentation results and the effect of the

multiple freeze–thaw cycles on the tissue properties was assessed (Figure 5.2).


Figure 5.2 : Mechanical property change due to multiple freeze thaw cycles

The results (Figure 5.1(a)) of the above experiments indicated that the

mechanical properties were not significantly affected by keeping the samples at 4 °C

in PBS-inhibitor solution for three days (p>0.1). However, the samples that were

kept in the PBS-inhibitor solution for one week (Figure 5.1(b)) showed a significant

decrease in mechanical stiffness at small strain-rates (i.e. at 10-4/s and 5x10-4/s)

(p<0.05). It is noteworthy that these results are similar to findings in previously

reported studies on other cartilage tissues [217]. The samples that went through the

multiple freeze–thaw cycle (i.e. four times) also did not show (Figure 5.2) any

significant change in mechanical properties (p>0.2). On the one hand, some studies

have reported that multiple freeze–thaw cycles may degrade the biomechanical

properties and composition of cartilage [293-295]. On the other hand, some studies

have stated that the decrease in mechanical properties is due to the thawing

procedure employed [217]. It has also been suggested that the sample size and

species may influence the subsequent effect of freeze–thaw cycles [217].

Considering the lack of consensus on this issue in the literature, the multiple freeze–

thaw cycle method was not used in this study to preserve the tissues. Instead, the first


preservation method which kept the cartilage sample in PBS-inhibitor solution at 4

°C was chosen.

5.4.2 Proteoglycan, superficial collagen degradation and surface delipidisation

Visually normal cartilage plugs (ICRS macroscopic score=0) of 8 mm diameter were

harvested from the central load-bearing area of the humeral head. After obtaining the

thickness values using ultrasound measurements, before and after the proteoglycan

and collagenase degradation, the samples were subjected to mechanical testing under

four strain-rates (10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s) to check how the progressive

degradation of the cartilage components affects the strain-rate-dependent mechanical

behaviour and the properties of the tissue. The results of the five samples tested

earlier (i.e. the samples tested after being kept in PBS-inhibitor solution for 72 hrs at

4 °C) were considered as the control test for these studies. Hence, additional control

studies were not conducted.

5.4.2.1 Proteoglycan degradation: Trypsin-PBS (phosphate buffered saline) solution

Several enzymes such as trypsin, chondroitinase ABC, cathepsin D and elastase have

been used to remove proteoglycans from cartilage tissues. Chondroitinase ABC [19,

296] and trypsin [291, 297-300] are the most commonly used enzymes for this

purpose. Chondroitinase ABC acts on proteoglycans to degrade chondroitin 4-

sulfate, chondroitin 6-sulfate and dermatan sulfate, and hyaluronate slowly. Trypsin

can cleave peptides on the C-terminal side of lysine and arginine residues of

proteoglycans. For the present study, trypsin was chosen to degrade the

proteoglycans due to its availability and extensive use in cartilage-related research.

Firstly, 100 ml of 0.01M PBS (P4417-100TAB, Sigma-Aldrich, Castle Hill,

NSW, Australia) solution (pH 7.4) which contained 1 ml of L-glutamine–penicillin–


streptomycin solution was mixed with 0.1 mg trypsin (from bovine pancreas, T1426,

Sigma-Aldrich, Castle Hill, NSW, Australia). The obtained 0.1 mg/mL trypsin–PBS

solution was then diluted to make 0.05 mg/ml. After the first cycle of mechanical

testing on a cartilage sample, it was treated with 0.05 mg/ml of trypsin under 37 °C

for 1 hr in an incubator. Afterwards, the sample was removed from the solution for

further mechanical tests (Figure 5.3). The cartilage sample was again treated for 1 hr

in trypsin before indentation testing and then again for 2 hrs before testing in order to

gradually degrade the proteoglycans, followed by mechanical testing to assess the

effects of 2 hrs and 4 hrs of trypsin–PBS treatment on the mechanical properties and

behaviour of the tissue. All samples (n=10) were tested as above and were always

preserved in PBS-inhibitor solution at 4 °C throughout the experiment.

Figure 5.3: Steps in sequential trypsin treatment (0.05 mg/ml) and mechanical testing on kangaroo shoulder cartilage samples

Treatments of cartilage samples for 1 hr, 2 hrs and 4 hrs in trypsin have shown

the need to remove the proteoglycans gradually in a wavefront manner through the

depth of cartilage [22, 301]. Noticeable variation in the amount depleted has also

been observed depending on the initial proteoglycan concentration [22]. In order to

investigate the manner in which the above-mentioned trypsin treatment degrades the

proteoglycan in kangaroo shoulder cartilage, a preliminary histological study was

conducted. Three cartilage samples were harvested from near the central load-

bearing area of the humeral head of adult red kangaroos. The samples were

cryosectioned to 10 μm and were stained for proteoglycans using 0.1% safranin-O


(details of the cryosectioning procedure and staining protocol are set out in Chapter

6, Sections 6.4.1 and 6.4.2). Then, the samples were subjected to 1 hr, 2 hrs and 4 hrs

of trypsin treatment according to the above-mentioned protocol. After each trypsin

treatment, the samples were cryosectioned and stained in safranin-O in order to

assess the proteoglycan depletion. The safranin-O stains proteoglycan in red/orange

colour (Figure 5.4(a)) and the stain intensity is proportional to the concentration of

proteoglycans.

The results of the histology study indicated that treatment of the samples for

one hour in trypsin removed almost all the proteoglycans in the superficial zone and

in part of the middle zone (Figure 5.4(c)). Further treatment for one hour removed a

substantial amount of proteoglycans in the deep zone (Figure 5.4(c)) while 4 hrs of

trypsin treatment removed almost all the proteoglycans (Figure 5.4(d)). The gradual

removal of proteoglycans in the form of a wavefront was also observed (as can be

seen in a comparison of Figures 5.4(a), (b), (c) and (d)). These results are consistent

with the reported findings in previous studies [22, 301].

The selective removal of primary proteoglycans through trypsin treatment for a

smaller period of time (<8 hrs) has been reported not to affect the structural

appearance of the collagen network [302]. There is limited evidence to suggest that

selective proteoglycan removal significantly affects the collagen network [21, 112,

302]. However, there is a possibility that trypsin may attack collagen molecules

which are already cleaved. This is most likely to be minimal due to the small

exposure time (≤ 4 hrs), but the inability to control the effect of trypsin specifically

should be noted as a possible limitation of this study.


Figure 5.4: Safranin-O staining of cryosectioned samples harvested from near the central load-bearing area of the humeral head – (a) Untreated sample; (b) 1 hr trypsin-treated sample; (c) 2 hr trypsin-treated sample; (c) 4 hr trypsin-treated sample

5.4.2.2 Superficial collagen degradation: Collagenase solution

Collagenase isolated from clostridium histolyticum is commonly used to

degrade the collagen of cartilage tissues. Studies commonly use 30 U/ml

concentration of collagenase solution for 24 hrs [237] to partially disrupt the

superficial collagen or for 40–44 hrs [19-21] to significantly damage it. It has been

identified that this collagenase treatment results in minor proteoglycan loss in the

superficial zone and middle zone of cartilage, possibly due to the diffusion of the

proteoglycans through the damage to the collagen network [19, 20]. However, some

studies have reported that proteoglycan depletion is histologically not visible when

treated with collagenase for 40 hrs [303].


A 3KU bottle of collagenase (from Clostridium histolyticum, C0773, Sigma-

Aldrich, Castle Hill, NSW, Australia), 100 ml of 0.01M PBS solution (pH 7.4), and 1

ml of L-glutamine–penicillin–streptomycin solution were mixed together to make 30

U/ml collagenase solution in the current study [19-21]. After the first cycle of the

mechanical tests, samples (n=12) were immersed in this collagenase solution and

placed in an incubator at 37°C for 44hrs. After the first cycle of mechanical tests, the

samples (n=12) were immersed in this collagenase solution and placed in an

incubator at 37 °C for 44 hrs. After this treatment, further mechanical tests were

carried out to assess the effect of the collagenase on the mechanical properties and

behaviour of the tissue (Figure 5.5). Since testing required more than one day, all the

samples were preserved overnight in PBS-inhibitor solution at 4 °C.

Figure 5.5: Steps carried out to investigate the effect of superficial collagen on the strain-rate-dependent behaviour of kangaroo shoulder cartilage

In order to check the effect of collagenase treatment on proteoglycans, a histological

study was also conducted on the cryosectioned samples harvested from three

kangaroo humeral heads. Safranin-O staining was conducted before (Figure 5.6(a))

and after collagenase treatment (Figures 5.6(b), (c) and (d)) and did not show a

noticeable effect on the proteoglycans. However, in order to further confirm these

results, an alcian blue test was conducted to detect any proteoglycans leaching out of

the matrix due to the collagenase treatment. Details of the alcian blue test are

presented in the next section.


Figure 5.6: Safranin-O staining of (a) untreated samples; (b), (c), (d) collagenase-treated samples 1, 2, 3, respectively

5.4.2.3 Alcian blue test: Effect of collagenase treatment on proteoglycans

Five kangaroo cartilage samples harvested from the central load-bearing area of the

humeral head were incubated at 37 °C for 44 hrs in 1 ml of 30 U/ml collagenase

solution. Afterwards, 0.1 ml of alcian blue (1% alcian blue in 3% acetic acid, PH 2.5)

was added to that solution and was kept for 24 hrs to settle the precipitate. At low pH

and in the presence of glycosaminoglycans, alcian blue forms a compound and

precipitate [304]. The resulting samples were then treated with 1 ml of 0.05 mg/ml

trypsin–PBS solution for 4 hrs. Afterwards, 0.1 ml of alcian blue was added to the

solution and the solution was kept for 24 hrs for the precipitate to settle so as to

check the amount of proteoglycans left after collagenase treatment. In addition, 1 ml

distilled water mixed with 0.1 ml of alcian blue served as the control for the

experiment. Results of the experiment are shown in figure 5.7. Based on the

experiment, it was confirmed that only a small amount of proteoglycans was


removed by collagenase treatment while a majority of the proteoglycans were still

intact in the tissue matrix (as can be seen by a comparison of Figures 5.7(a), 5.7(b)

and 5.7(c)).

Figure 5.7: (a) Alcian blue 0.1 ml mixed in 1 ml of distilled water (control test); (b) Alcian blue 0.1 ml mixed in the resulting solution after a cartilage sample being digested in 1 ml of 30 U/ml collagenase for 44 hrs; (c) Sample after digesting in collagenase was treated in 1 ml of trypsin–PBS solution (0.05 mg/ml) for 4 hrs and then mixed with 0.1 ml of alcian blue

5.4.2.4 Removal of surface lipids: Chloroform, methanol mixture

There are several methods to remove lipids from the surface of the cartilage tissue.

They include mechanical, enzymatic and chemical delipidisation. The mechanical

delipidisation involves carefully wiping the cartilage surface with emery cloth,

sandpaper or glasspaper [292]. The uncertainty of grit size and the rate of removal of

the lipid layer make it difficult to control the amount that is delipidised in the

process. Enzymatic delipidisation uses enzymes to remove the surface lipids by

specifically hydrolysing the phospholipid chains [305, 306]. Although this method

selectively removes the lipids from surfaces, it is not commonly used to delipidise

the surface of cartilages.

Chemical delipidisation is the most common method of removing lipids from

the cartilage matrix and surface. Reagents such as ethanol [307], propylene glycol


[307], chloroform [307, 308] and Folch [309-311] have been used to remove lipids

from both the matrix and on the surface. However, the Folch reagent, which is a

mixture of chloroform and ethanol in 2:1 ratio has been proposed to remove lipids

quickly. Therefore, it reduces the tissue exposure time to the chemical, resulting in

fewer risks associated with compromising the integrity of the cartilage matrix [292,

306, 311]. Given this advantage, the Folch reagent was used in the current study to

remove the surface lipids from the cartilage surface and to subsequently assess its

effect on the strain-rate-dependent mechanical behaviour of cartilage tissues.

It has been established that carefully wiping the cartilage surface (for 20–30

minutes) using a Folch reagent will significantly remove the surface lipid layer [312].

Therefore, the surfaces of the kangaroo cartilage samples (n=9) harvested from near

the central load-bearing area of the humeral head were wiped continuously for

approximately 30 minutes using Kimwipes soaked in Folch reagent. Before and after

delipidisation, the samples were subjected to mechanical testing (Figure 5.8)

following the same protocols as before. The mechanical properties were extracted

from the force–indention curves and the effect of surface delipidisation on the strain-

rate-dependent mechanical behaviour was assessed.

Figure 5.8: Steps carried out to investigate the effect of surface lipids on the mechanical behaviour of kangaroo shoulder cartilage


5.4.3 Statistical data analysis procedure

The mechanical behaviour and properties of normal, proteoglycan-degraded and

collagenase-degraded tissues were statistically compared. The repeated measure

ANOVA was used to identify the statistical significance of the treatments, while

Tukey’s pairwise comparison test was employed to compare the individual levels of

treatments. The random effect model shown in Eq. (5.1) was used for the statistical

analysis with the variable ‘sample’ as the random factor. Minitab Version 16.1.1

(2010 Minitab Inc.) was used for statistical analysis. The statistical significance is

reported at both 95% (p<0.05) and 99.5% (p<0.005) confidence intervals. Eq. (5.1) is

expressed as follows:

Y= Sample + Strain + Strain-rate + Exposure-time + Sample*Strain +Sample*Strain-

rate +Sample*Exposure-time + Strain*Strain-rate +Strain*Exposure-time + Strain-

rate*Exposure-time (5.1)

In the above model, ‘Exposure-time’ is the amount of time the samples were

subjected to the chemical (i.e. trypsin–PBS for 1 hr, 2 hrs and 4 hrs, collagenase for

44 hrs, and Folch reagent for 0 hr). ‘Strain-rate’ had four levels (10-4/s, 5x10-4/s,

5x10-3/s and 10-2/s). Six levels (0%, 5%, 10%, 15%, 20%, 25%) were chosen for

‘Strain’.


The responses of typical cartilage samples before and after 4 hrs of trypsin treatment

(Figures 5.9(a) and 5.9(b)), 44 hrs of collagenase treatment (Figures 5.9(c) and

5.9(d)) and chloroform/methanol treatment (Figures 5.9(e) and 5.9(f)) are shown


with the corresponding hyperelastic coefficients extracted using Eq. (3.14) (Chapter

3).

Figure 5.9 : Effect of mechanical behaviour when (a) normal sample is (b) treated in trypsin (0.05 mg/ml) for 4 hrs, and when (c) normal sample is (d) treated with collagenase (30 U/ml) for 44 hrs, and when (e) normal sample is (f) treated with Folch reagent to remove surface lipids

Samples from post-trypsin and post-collagenase treatments showed a reduction

in stiffness while no such difference was revealed in samples from post-


chloroform/methanol treatment. The effects of these treatments are detailed in the

following sections. The sample thicknesses calculated using ultrasound

measurements were 0.76±0.16 mm (n=10), 0.78±0.10 mm (n=12) and 0.63±0.01 mm

(n=9) for the trypsin treated, collagenase treated and surface lipid-removed cartilage

sample groups, respectively.

5.5.1 Effect of proteoglycan degradation on strain-rate-dependent behaviour and mechanical properties

5.5.1.1 Effect on tissue stiffness and nonlinearity

As shown above in Figure 5.9, for a typical sample, trypsin treatment reduced the

ability of the tissue to withstand external compressive loads. This was observed in all

strain-rates and was further confirmed by the variation of Young’s modulus with

exposure time to trypsin (Figure 5.10(a)). As shown, the Young’s modulus, which is

an indicator of matrix stiffness, reduced gradually with the progressive removal of

proteoglycans. This was observed at all strain-rates.

The decrease in stiffness was statistically significant for 1 hr, 2 hrs and 4 hrs of

trypsin treatment when compared with normal tissue (p<0.05). Except at 10-4/s

strain-rate, the stiffness of the 1 hr- and 2 hr-treated samples was not statistically

different (p>0.05). Nonetheless, the stiffness of the 1 hr-treated samples was

considerably lower (p<0.05) than the normal tissue samples. This indicated that a

considerable amount of proteoglycans might have been removed from the samples

during the first hour of trypsin treatment. The stiffness reduction from 2 hrs to 4 hrs

compared with 1 hr to 2 hrs was high but not statistically significant (p>0.05).

The nonlinear stiffness parameter 20C , which is an indicator of the nonlinearity

of the stress-strain behaviour of cartilage, reduced gradually with the progressive

degradation of proteoglycans (Figure 5.10(b)). However, the decrease in 20C was not

statistically significant at the smallest (10-4/s) and largest strain-rates (10-2/s) tested


when compared with untreated samples. Nevertheless, significant differences were

observed at intermediate strain-rates (p<0.05). The results indicated that the

nonlinearity of the tissue response may not have been affected by the proteoglycan

degradation at the smallest and highest strain-rates. The reason for this behaviour has

not been reported in the literature and remained unclear in this study; therefore, it

requires further investigation. However, the observations might be related to small

fluid velocities at the smallest strain-rate and the fluid containment effect at large

strain-rates. Overall, the gradual reduction of stiffness with removal of proteoglycans

confirms the already-established belief that proteoglycans directly affect the

compressive load-bearing function of cartilage tissues.

Figure 5.10: Effect of 1 hr, 2 hrs and 4 hrs of trypsin treatment (0.05 mg/ml) on (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates

5.5.1.2 Effect on tissue permeability and pore size

In order to check the increase in pore size after removal of proteoglycans,

permeability was extracted for normal and 4 hr trypsin-treated tissues by curve fitting

a porohyperelastic model to experimental force–indention data at the lowest strain-

rate. The results showed that the permeability increased from 1.38±0.83×10-14 m4/Ns

to 3.03±1.43×10-14 m4/Ns due to proteoglycan degradation (p<0.005), similar to the


results in previously reported studies [20]. Based on Eq. (4.28) in Chapter 4, these

permeability values corresponded to pore sizes of 160.38±37.49 Å and 238.96±48.00

Å, respectively, which represents an increase of 1.48 times.

It was presumed that complete removal of proteoglycans would considerably

reduce the ability of cartilage tissues to respond to varying rates of loads, and hence

would completely remove the strain-rate-dependent nature of cartilage tissues. This

was based on the anticipation that the complete removal of proteoglycans will

increase the pore size of the tissue to an extent where solid–interstitial fluid frictional

interactions are considerably reduced. However, even after 4 hrs of trypsin treatment,

which removed almost all the proteoglycans, the strain-rate-dependent behaviour was

observed in the tested samples. This may be because the dense collagen meshwork is

still able to sustain the pore sizes in cartilage to such an extent that the solid–

interstitial fluid frictional interaction is able to facilitate the tissue’s ability to respond

to varying rates of loads, or it could also be due to the viscoelasticity of the collagen

network.

5.5.1.3 Role of proteoglycans in strain-rate-dependent behaviour

One of the objectives of the current study was to investigate the contribution of

proteoglycans to the tissue behaviour at individual strain-rates. The result of the

histological study described in Section 5.4.2.1 indicated that 4 hrs of trypsin

treatment resulted in almost complete removal of proteoglycans from kangaroo

shoulder cartilage. Therefore, the percentage reduction of Young’s modulus and the

nonlinear stiffness parameter at individual strain-rates due to proteoglycan

degradation (after 4 hrs of trypsin treatment) were calculated and compared. The

percentage decreases in Young’s modulus were 36.5±22.8%, 35.0±21.3%,

39.4±17.0% and 33.1±14.0% for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates,


respectively. These values indicated that complete removal of proteoglycans reduced

the Young’s modulus of the tissues more or less to a similar extent at the different

strain-rates tested. The statistical analysis indicated that the percentage decreases in

Young’s modulus at each strain-rate were not significantly different from each other

(p>0.05). For the tested strain-rates of 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s, the

reduction of the nonlinear stiffness parameter was 33.5±30.8%, 48.2±24.9%,

46.8±28.2% and 23.2±35.7%, respectively. Reductions of 20C at the lowest and

highest strain-rates were smaller than at intermediate strain-rates. However,

statistically significant differences were only identified between the highest and

intermediate strain-rates (p<0.05).

Previous studies have stated that the proteoglycans of cartilage tissue are

responsible for the equilibrium compressive properties (extracted at very low strain-

rates) of the tissue [20]. Further, compositional-based FE models specifically

focusing on the strain-rate-dependent behaviour of cartilage have shown that, at

small strain-rates (10-3/s), proteoglycans contribute more to the mechanical

behaviour of the tissue [16]. However, in the present study, irrespective of the strain-

rate, proteoglycans seem to have similar contribution to the compressive load-

bearing properties of the cartilage tissues, thus confirming the important role of

proteoglycans in tissue behaviour at both low and high strain-rates.

5.5.2 Effect of superficial collagen degradation on strain-rate-dependent behaviour and mechanical properties

5.5.2.1 Effect on tissue stiffness and nonlinearity

Similar to the trypsin treatment, treating kangaroo shoulder cartilage samples in

collagenase for 44 hrs also reduced the ability of the tissue to withstand external

loading at all strain-rates (Figures 5.9(c) and 5.9(d)). Figure 5.11(a) presents the

reduction of tissue stiffness due to collagenase treatment indicated by the decrease in


Young’s modulus. In general, stiffness of the tissues decreased at all strain-rates

tested, with the difference being statistically significant compared to untreated tissues

(p<0.005). Unlike in the case of trypsin treatment, where significant reductions in the

nonlinear stiffness parameter were only evident at intermediate strain-rates (5x10-4/s

and 5x10-3/s), 20C showed a statistically significant reduction at all strain-rates

(p<0.05) (Figure 5.11(b)).

Figure 5.11 : Effect of 44 hr collagenase treatment (30 U/ml) on (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates

Collagenase treatment for 40–44 hrs is known to significantly degrade the

superficial collagen [19-21, 237]. Longer exposure time may affect deep zone

collagen. However, the difficulty in exactly controlling the effect of collagenase on

the collagen network can be considered as a possible limitation of this study.

Nevertheless, the results of the histology (Section 5.4.2.2) and alcian blue (Section

5.4.2.3) experiments confirmed that only a small amount of proteoglycans was

removed by collagenase treatment, while the majority of the proteoglycans were still

intact in the tissue matrix, which is similar to the results of previously reported

studies [19, 303]. Therefore, it can be said that the reduction of the tissue’s stiffness

to a large extent is indeed due to the degraded superficial collagen. Overall, the


results indicated that the stiffness and nonlinearity of the kangaroo shoulder cartilage

were compromised due to superficial collagen degradation.

5.5.2.2 Effect on tissue permeability and pore size

The results of the present study indicated the tendency of the strain-rate-dependency

to reduce with collagen disruption. The inverse FEA method was used to fit the

force–indentation curves at the smallest strain-rate to a porohyperelastic model to

find out the permeability. It was found that, due to collagenase treatment, the

permeability increased from 1.36±0.41×10-14m4/Ns to 4.19±2.79×10-14m4/Ns.

These permeability values corresponded to pore sizes of 162.16±22.32 Å and

270.22±94.96 Å, respectively—an increase of 1.69 times. The increase of

permeability due to collagenase treatment has also been reported previously [20]. It

is highly possible that the collagen disruption increases the interspaces between

collagen fibrils and hence the pore size of the tissue. Therefore, the collagen

disruption and the increase in pore size compromise the tissue’s ability to respond to

varying strain-rates, as observed in this study.

5.5.2.3 Role of superficial collagen in strain-rate-dependent behaviour

The decrease in stiffness due to collagenase treatment has been reported in numerous

studies [19-21, 137]. However, there are limited studies on the effect of superficial

collagen on the strain-rate-dependent behaviour of shoulder cartilage. There are

reported numerical studies stating that the superficial collagen affects cartilage tissue

behaviour at large strain-rates much more than at small strain-rates [16]. However,

most of these studies have been conducted on knee cartilage. Due to the differences

in the mechanical environments experienced by knee cartilage (high magnitude and

frequent compressive loads) and shoulder cartilage (low magnitude compressive

loads), it is likely that the collagen network (including the superficial layer) plays a


more significant role than proteoglycans in shoulder cartilage. Further, considering

that the porohyperelastic model with strain-rate-dependent permeability was unable

to predict the tissue behaviour at the highest strain-rate tested (10-2/s), it was thought

that the collagen network might be playing a larger role in determining tissue

behaviour at high strain-rates. Further, for knee cartilage, there is evidence that the

effect of superficial collagen on tissue behaviour increases with strain-rate

[16].Therefore, one of the objectives of the present study was to check the

contribution of superficial collagen to the mechanical behaviour and properties of the

kangaroo shoulder cartilage at individual strain-rates.

To do so, the percentage decrease in Young’s modulus for 44 hr collagenase

treatment, which potentially would have greatly degraded the superficial collagen,

was assessed. The percentage decreases in Young’s modulus were 53.0±29.6%,

55.4±28.3%, 55.4±25.4% and 55.7±16.3% for strain-rates of 10-4/s, 5x10-4/s, 5x10-3/s

and 10-2/s, respectively. The differences in the percentage decreases of Young’s

modulus between the strain-rates were statistically insignificant (p>0.1). This

indicated that the superficial collagen more or less had an equal effect on the tissue

behaviour at all strain-rates. The decreases in the nonlinear stiffness parameter were

0.72±13.9%, 65.8±26.3%, 58.3±31.9% and 70.2±24.0% for the above strain-rates.

Although there were differences in the percentage decreases in the Young’s modulus

and nonlinear stiffness parameter for different strain-rates, these were not identified

to be statistically different (p>0.05). This indicated that the superficial collagen

affected the kangaroo shoulder cartilage behaviour more or less to the same extent

for all the strain-rates tested.

However, the aforementioned result differs from the findings reported in the

literature. As mentioned before, it has been reported that, at high strain-rates, the


superficial collagen content and collagen network architecture influence the tissue

behaviour considerably more than at low strain-rates [16]. These different findings

could be mainly due to the differences of the specific joint cartilages studied:

previous studies have used bovine knee cartilage, while this study used kangaroo

shoulder cartilage. In terms of microstructure and composition, there are noticeable

differences between shoulder and knee cartilage tissues (as discussed in detail in the

next chapter). Therefore, the FE model parameters (water volume fraction, fixed

charge density, collagen volume content, superficial and deep zone thickness) used in

the literature can be different from the parameters necessary for shoulder cartilage.

Therefore, it is our belief that the conclusions made through numerical models

should be evaluated according to the relevant tissue investigated (i.e. whether it is

knee or shoulder cartilage).

Superficial collagen degradation, in addition to collagen, may remove the

surface lipids of the tissue as well. Therefore, it was necessary to evaluate the effect

of surface lipids on tissue behaviour in order to confirm that the effects mentioned

above were mainly due to the superficial collagen degradation. The findings of the

succeeding study can also inform the research community about the role of surface

lipids in the strain-rate-dependent behaviour of the tissue.

5.5.3 Effect of surface phospholipid removal on strain-rate-dependent behaviour and mechanical properties

A comparison of Figures 5.9(e) and 5.9(f) above, for typical cartilage samples, seems

to suggest that the removal of surface phospholipids has a minimal effect on the

tissue’s ability to withstand external loading. This can be further identified by

comparing the average Young’s modulus of normal and surface lipid-removed

samples (Figure 5.12(a)). In general, stiffness of the cartilage matrix was reduced by

a small amount due to surface lipid removal. However, these differences were


statistically insignificant (p>0.05). Similarly, the nonlinear stiffness parameter was

also reduced due to the removal of the surface lipids. However, in this case,

statistically significant differences were only identified at 5x10-4/s and 10-2/s strain-

rates (p<0.05) (Figure 5.12(b)). The statistically insignificant differences imply that

the removal of surface lipids does not adversely affect the strain-rate-dependent


Figure 5.12: Effect of surface lipid removal on (a) Young’s modulus; and (b) the nonlinear stiffness parameter of kangaroo shoulder cartilage for 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-rates

Previous studies [307, 308] have reported that the stiffness of cartilage could

reduce at low strain-rates (1.3x10-4/s) and increase at high strain-rates (10/s) when

lipids are removed from the tissue. These studies used a slightly different

methodology where cartilage was delipidised by immersing the specimen in a

reagent solution followed by a vacuum-drying process to evaporate the reagent.

During this method there is a high possibility for lipids inside the cartilage matrix as

well as on the surface to be removed. In addition, there are possible changes in the

tissue matrix due to the dehydration process. To a large extent, this could be the main

reason for the differences observed in the present study and other reported studies.


5.5.4 Comparison of the effect of proteoglycan and superficial collagen on strain-rate-dependent behaviour

Acknowledging the fact that each cartilage constituent plays an important role in the

cartilage behaviour, we specifically analysed their effect on the strain-rate-dependent

indentation behaviour of kangaroo shoulder cartilage tissues. In order to compare the

effects of complete removal of proteoglycans (Figure 5.13(a)), severe disruption to

the superficial collagen (Figure 5.13(b)) and removal of surface lipids (Figure

5.13(c)), normalised force vs indentation plots were considered.

The force–indentation graphs indicated that the ability of the cartilage to

withstand external loading was reduced more when the superficial collagen was

significantly degraded than in the case of complete removal of proteoglycans

(compare Figure 5.13(a) and Figure 5.13(b)). The effect of surface lipid removal on

the tissue behaviour was small (Figure 5.13(c)). Interestingly, when the effects of 4

hr trypsin treatment and 44 hr collagenase treatment were compared, it was noted

that the latter treatment reduced tissue stiffness more at all strain-rates (p<0.05)

(Figure 5.14(a) and Table 5.1). The percentage decrease in the nonlinear stiffness

parameter was also significantly higher in response to superficial collagen disruption

rather than proteoglycan degradation (p<0.05) (Figure 5.14(b)). Therefore, it can be

concluded that the contribution of superficial collagen to tissue behaviour in

kangaroo shoulder cartilage is higher than the contribution of proteoglycans. This is

understandable considering that chondrocytes are able to synthesise the extracellular

matrix according to the mechanical inputs the tissue receives. Hence, the larger and

more frequent the compressive forces, the higher the proteoglycan composition and

the greater its role in the tissue behaviour. Given that the shoulder joint experiences

low magnitude compressive loads (as discussed by comparison to knee joint in

Chapter 6, Section 6.1), the stimulation of chondrocytes by compressive forces is


also rather low. Thus, compared to knee cartilage, shoulder cartilage may comprise a

small amount of proteoglycans. This implies that the collagen architecture may play

a significantly larger role in determining shoulder cartilage tissue behaviour, which is

confirmed by the results of the present study.

Table 5.1: Young’s moduli (MPa) of 4hr trypsin-treated and 44 hr collagenase-treated kangaroo shoulder cartilage at four strain-rates

Strain-rates 10-4/s 5x10-4/s 5x10-3/s 10-2/s

0 hrs in trypsin (n=12) 0.040 ± 0.016

0.078 ± 0.445

0.360 ± 0.261

0.523 ± 0.299

4 hrs in trypsin 0.026 ± 0.014

0.048 ± 0.026

0.194 ± 0.076

0.328 ± 0.131

0 hrs in collagenase (n=10)

0.10 ± 0.045

0.217 ± 0.125

1.023 ± 0.580

1.412 ± 0.485

44 hrs in collagenase 0.043 ± 0.025

0.084 ± 0.049

0.377 ± 0.214

0.633 ± 0.341

These findings were further reinforced by the observation that 44 hrs of

collagen degradation more or less had an equal (p>0.1) effect on the tissue behaviour

at all strain-rates tested, while similar observations were also made for 4 hrs of

proteoglycan degradation (Figure 5.14(a)). These findings are contrary to reported

findings on knee cartilage. In investigating knee cartilage behaviour from 10-3/s to

10-1/s, Julkunen et al. [16] reported that, compared to low strain-rates, superficial

collagen substantially contributed to the tissue behaviour at the higher strain-rates

(10-1/s). However, in their study, proteoglycan contribution (approximately 37.2%) to

the tissue behaviour at 10-1/s was still much higher than the superficial collagen

contribution (14.7%).


Figure 5.13: Effect on average normalised force–indentation curves due to (a) 4 hrs of trypsin (0.05mg/ml) treatment, i.e. proteoglycan completely removed (n=12); (b) 44 hrs of collagenase treatment, i.e. severe disruption to superficial collagen (n=10); and (c) surface phospholipid removal (n=9)

On the contrary, by calculating the average percentage decrease in Young’s

modulus (Figure 5.14(a)) at the strain-rates tested, the results of the present study

showed that the contribution of the superficial collagen and proteoglycans to the

tissue behaviour of shoulder cartilage was 54.88±1.11% and 35.99±2.3%,

respectively. This difference in the observations in the current study and in the

literature is reasonable because the previous studies focused on knee cartilage that is

most likely structurally and compositionally different from shoulder cartilage. When

the proteoglycan content of kangaroo shoulder and knee cartilage was analysed (as

discussed in the next chapter), noticeable differences were identified. As mentioned


before, the collagen network plays a dominant role in the mechanical behaviour of

shoulder cartilage, to an even larger extent than proteoglycans. Therefore, a finding

that collagen has an equally dominant effect on the mechanical behaviour of shoulder

cartilage at all strain-rates is justifiable.

In cartilage, water-swollen proteoglycans are constrained by the three-

dimensional collagen network to form the functional load-bearing unit of cartilage.

Any disruption of the collagen network reduces its ability to constrain the

proteoglycans, compromising the matrix integrity and in turn its ability to act as an

effective load-bearing unit. In addition to the reduction in tissue stiffness, superficial

collagen disruption and proteoglycan degradation also increased the tissue

permeability (p<0.005). It was noted that the collagen disruption affected the

permeability more than the proteoglycan degradation (p<0.005). In the case of

proteoglycan degradation, the increase was 2.19 times; in the case of collagen

network disruption, it was 3.04 times. Therefore, the significant reduction in strain-

rate-dependency observed when the collagen network was disrupted—even more

than in the case of proteoglycan degradation—confirmed the importance of the

collagen network in facilitating the strain-rate-dependent behaviour of cartilage.

Assuming that the effect of collagenase and trypsin treatments on the tissue are

independent, the collagen disruption and proteoglycan degradation in total

contributed to approximately 89–95% (Figure 5.14(a)) reduction in tissue stiffness.

This implies that the total removal of proteoglycans and significant disruption of

superficial collagen would render the kangaroo shoulder cartilage almost incapable

of responding to varying rates of external loads. Although dominated by the collagen

network, this shows the important functional interdependency of collagen and


proteoglycans in facilitating the strain-rate-dependent behaviour of shoulder

cartilage.

As mentioned in Chapter 2, it is known that in cartilage tissues the value of the

modulus in tension is several times higher than in compression. This is more

pronounced in upper limb cartilage tissues compared to lower limb cartilage tissues.

The results of the current study, through the indication of the considerably high

contribution of superficial collagen in determining the cartilage behavior, indicated

the importance taking this tension-compression nonlinearity into consideration when

modelling shoulder cartilage tissues.

Figure 5.14: Percentage decrease in (a) Young’s modulus and (b) nonlinear stiffness parameter of kangaroo shoulder cartilage due to complete removal of proteoglycans (4 hrs of treatment in 0.05 mg/ml trypsin) and severe disruption to superficial collagen (44 hrs of treatment in 30 U/ml collagenase)

5.5.5 Effect of proteoglycan and superficial collagen degradation on long-term functional load-bearing ability of the tissue

In order to understand the changes in the internal tissue behaviour when

proteoglycans and superficial collagens are degraded, the porohyperelastic FE model

which was validated for internal pore pressure measurements was employed (Chapter

3, Section 3.3.2). Based on the FE model predictions, as shown in Figure 5.15, for


the strain-rate of 10-4/s, the hydrostatic excess pore pressure noticeably decreased

due to degradation of the proteoglycans and superficial collagen. The reasons for

these results are the decrease in elastic properties and increase in permeability when

the tissue is degraded. The fluid is less capable of contributing to the load-bearing

function in the case of superficial collagen degradation as compared to proteoglycan

degradation. Therefore, there will be more burden on the collagen network when the

superficial collagen is degraded, resulting in the collagen network being further

damaged and eventually dysfunctional.

Figure 5.15: Variation of pore pressure with strain for 4 hr trypsin-treated and 44 hr collagenase-treated samples

The model parameters used for simulating the behaviour of tissue after proteoglycan

and collagen degradation is shown in Table 5.2. The stiffness parameter 10C was

calculated based on the percentage reduction of Young’s modulus due to 4 hrs of

trypsin treatment and 44 hrs of collagenase treatment (i.e. 35.99% and 54.88%,

respectively). Similarly, the permeability values were calculated based on the

increase in permeability due to trypsin treatment for 4 hrs (2.19 times) and due to

collagenase treatment for 44 hrs (3.06 times). The nonlinear stiffness parameter 20C

used for the simulation was assumed to be small (i.e. 0.01 MPa), considering the


linearity of the stress-strain response data [135] used to validate the FE model and

was maintained constant throughout the simulations. It is noted that these

assumptions did not affect the results and conclusion of this study.

Table 5.2: FE model parameters for normal, 4 hr trypsin-treated and 44 hr collagenase-treated samples

Normal tissue

Proteoglycan-

degraded tissue (4

hrs in trypsin)

Collagen-degraded

tissue (44 hrs in

collagenase)

10C (MPa) 0.158 0.101 0.0554

20C (MPa) 0.01 0.01 0.01

1D (1/MPa) 4.738 7.403 13.536

k (Ns/m4) 2.58x10-16 5.64x10-16 7.73x10-16


Considering the results reported in Chapter 4, we carried out a systematic and

comprehensive study to investigate the effect of the cartilage constituents on the

strain-rate-dependent behaviour of kangaroo shoulder cartilage. In doing so,

enzymatic degradations of proteoglycans and superficial collagen along with

simultaneous indentation tests at different strain-rates were conducted. The removal

of proteoglycans increased the pore size of the tissue. The exposure of the tissue to

trypsin was limited to 4 hrs in order to reduce the possible effects on the collagen

network and was identified as enough to remove almost all the proteoglycans. The

collagenase treatment was limited to 44 hrs in order to significantly degrade the

superficial collagen and this was found to remove only a small amount of

proteoglycans from the tissue. The following remarks and conclusions can be made

based on the results of the current study:


• Neither of the tissue preservation methods (i.e. preservation of the tissue at 4

°C in PBS-inhibitor solution and freeze–thaw methods) affected the

mechanical properties and behaviour of the tissue significantly. However,

considering reported concerns about the freeze–thaw method, preservation of

the tissue at 4 °C in PBS-inhibitor solution was chosen as the preservation

method for the current study.

• Proteoglycan depletion and superficial collagen disruption substantially

compromised the tissues’ ability to respond to and withstand external

compressive loading at different strain-rates. This would increase the risk of

bone-to-bone contact.

• Proving the direct role of proteoglycans in facilitating the compressive load

bearing ability of the tissue, the removal of proteoglycan using 1 hr, 2 hr and

4 hr trypsin treatments gradually reduced the tissue stiffness at all strain-rates.

• Total proteoglycan degradation increased the permeability of kangaroo

shoulder cartilage by 2.19 times and the pore size by 1.48 times. Even after

most proteoglycans have been removed (4 hrs of trypsin treatment), the

kangaroo shoulder cartilage demonstrated strain-rate-dependent behaviour.

This could be due to dense collagen meshwork is been able to keep pore sizes

such that solid-interstitial fluid frictional interactions are able to facilitate the

strain-rate-dependent behavior.

• Similarly, even after severe disruption to the superficial collagen network (44

hrs of collagenase treatment), the strain-rate dependency was still a

characteristic of the tissue. In this case, the permeability increased by 3.04

times and the pore size by 1.69 times.


• The effect of surface lipids on the strain-rate-dependent mechanical

behaviour of kangaroo shoulder cartilage was found to be small and

statistically insignificant. Additionally, superficial collagen disruption was

found to remove only a small amount of proteoglycans while keeping the

majority intact. These two results together confirmed that the main reason for

the reduction of tissue stiffness due to collagenase treatment is the disruption

to superficial collagen.

• Superficial collagen degradation had the largest effect on strain-rate-

dependency compared with complete removal of proteoglycans. Therefore, it

was concluded that the contribution of superficial collagen is higher than the

proteoglycans in facilitating the strain-rate-dependent behaviour.

• Superficial collagen was found to contribute evenly to tissue behaviour at all

strain-rates, thus confirming the importance of superficial collagen in

governing the mechanical properties and behaviour of kangaroo shoulder

cartilage at both low and high strain-rates.

• The above two findings are different to the conclusions reported in the

literature on knee cartilage. In previous studies, the superficial collagen is

reported to contribute less than proteoglycans to the mechanical behaviour.

Furthermore, the contribution of superficial collagen is reported to be

considerably large at high strain-rates when compared to its contribution at

low strain-rates. These differences can be attributed to the potential

compositional and microstructural differences in the two types of tissues (i.e.

knee cartilage and shoulder cartilage). An investigation into the differences in

these two types of tissues is discussed in the next chapter.


• Based on porohyperelastic modelling, it was revealed that collagen disruption

leads to faster shoulder cartilage damage than when proteoglycans were

depleted. This is due to interstitial fluid being less capable of supporting

external loads.

The investigations reported in this chapter gave insights into the role of

proteoglycans and the collagen network in the strain-rate-dependent mechanical

behaviour of kangaroo shoulder cartilage. Further, the results of the experiments

pointed to the differences in knee and shoulder cartilage as the reason for the

different results in the present study and in the literature. Nevertheless, to further

investigate and confirm this conclusion, the compositional and macrostructural

differences in knee and shoulder cartilage were studied as discussed in the next

chapter.


Chapter 6: Compositional, microstructural and biomechanical differences in kangaroo shoulder and knee cartilage

This chapter begins with a brief introduction to the forces experienced by shoulder

and knee cartilage tissues (Section 6.1). The aims and objectives of this part of the

study as well as the hypothesis are presented (Sections 6.2 and 6.3, respectively). The

methods and materials used are set out in detail (Section 6.4), followed by the results

and discussion (Section 6.5). Lastly, the chapter presents the conclusions and

remarks based on the results obtained in the study (Section 6.6).

6.1 INTRODUCTION

Anatomically different knee and shoulder joints undergo forces which are

significantly different in magnitude and mode due to the bipedal nature of humans.

For example, the shoulder joint experiences compressive forces of 44–90% body

weight during arm elevation of 60°–100°, with shear forces being almost 50% body

weight at 60° of abduction [87-90]. In comparison, the knee joint experiences

compressive forces of 50% to 600% body weight during flexion angles of 0°–90° in

static joint positions [313]. These differences are more prominent when dynamic

movements are considered where joint can experience 2-3 times loading than in the

static loading conditions [91, 92]. A professional baseball pitcher’s shoulder joint

experiences at minimum compressive/distractive forces of 108% BW and generates

external rotational torques (causing shear stresses) in the range of 67-92 Nm [1, 93,

94]. On the other hand, during normal walking and jogging, the knee joint

Chapter 6: Compositional, microstructural and biomechanical differences in kangaroo shoulder and knee cartilage143

experiences compressive forces of 300% body weight to 700% body weight,

respectively [313].

Arguably, the mechanical properties and mechanical behaviour of cartilage

tissues are regulated by the magnitude and mode of forces experienced by the tissue.

Given the considerable differences in forces experienced by the two joints, it is

expected that the shoulder cartilage is compositionally and microstructurally

different from the knee cartilage. This could perhaps be the main reason why the

conclusions made in the earlier part of this study (Chapter 5) are different from the

findings of studies in the literature that focused mainly on knee cartilage. The animal

model used throughout this thesis, namely, kangaroo, experiences considerably

different magnitudes of load in the lower limb joints compared to the upper limb

joints due to its bipedal-hopping locomotion. Therefore, kangaroo as an animal

model provides a unique avenue for investigating the effect of joint loading on the

composition and microstructure of cartilage. Following on from the investigation

reported in Chapter 5, the objectives of this part of the study are presented in the next

section.


The main aims and objectives of this part of the study were:

1. To investigate the differences in proteoglycan concentration and distribution

between knee and shoulder cartilage.

2. To investigate the differences in features of the collagen network of knee and

shoulder cartilage.

3. To investigate the contribution of proteoglycan and superficial collagen to the

strain-rate-dependent behaviour of knee cartilage and compare the findings

with shoulder cartilage.

144 Chapter 6: Compositional, microstructural and biomechanical differences in kangaroo shoulder and knee cartilage

4. To relate the mechanical behavioural differences of knee and shoulder

cartilage to compositional and microstructural differences.

6.3 HYPOTHESIS

The main hypothesis in this part of the study was: Compositionally and

microstructurally, the shoulder cartilage and knee cartilage are distinctly different

from each other and these differences are reflected in the biomechanical behaviour of

the tissues.

6.4 METHODS AND MATERIALS

In the present investigation, histological and polarised light microscopy (PLM)

studies on kangaroo knee and shoulder cartilage were conducted. Further, knee

cartilage was subjected to sequential proteoglycan and collagenase degradation along

with mechanical tests under different strain-rates. The results of these mechanical

tests on knee cartilage were compared with the results on shoulder cartilage

presented in Chapter 5. The mechanical tests and histological studies were carried

out on separate samples. This is because, in between consecutive mechanical

testings, the sample size and geometry should be maintained, while histological

studies require a biopsy to be taken. The preservation of the sample geometry and

dimensions is especially important for the meaningful extraction of mechanical

properties from force–indentation data. The following section describes the sample

preparation methods along with details of the histological and PLM studies.

6.4.1 Cryostat tissue sectioning: Tissue preparation for histological studies

Biopsy samples were obtained from three fresh, adult kangaroo knee and shoulder

joints. For shoulder joints, the biopsy sample was taken from near the central load-

bearing area of the humeral head, while for knee joints, the samples were harvested


from the medial and lateral sides of the femoral condyle and tibial plateau (2 samples

from each location). Then, a cryostat was used to reduce the sample thickness to a

suitable size (10 μm) for histological and PLM studies. Firstly, the temperature of the

cryostat with mounting metal chucks inside was set to -20 °C to -22 °C. Then, the

samples were placed inside the metal chuck and immediately embedded and frozen

in an optimal cutting temperature medium. The samples were embedded such that the

cryostat blade was parallel to the articular surface. The embedded samples were

cryosectioned and 10 μm specimens were then collected carefully on microscope

slides and left to dry in an oven at 30 °C for one week before histological staining.

This procedure made the samples stick to the slide and reduced the possible loss of

the sample during staining.

6.4.2 Safranin-O staining protocol

Safranin-O, which is a cationic dye, binds to positively-charged glycosaminoglycan

in a one-to-one ratio. The negatively-charged carboxyl or sulphate group in

glycosaminoglycan helps to form the bonding with the positively-charged dye

molecules [314, 315]. Therefore, safranin-O is considered to be a suitable dye for

the histochemical quantification of proteoglycans in cartilage tissues [314]. Hence,

in accordance with the standard safranin-O staining protocol, the prepared slides

were fixed in 95% alcohol for 30 seconds and left to dry in air. Then, the specimens

were hydrated in distilled water and rinsed in 1% acetic acid for 15 seconds. Staining

was conducted by immersing the slides for 5 minutes in a 0.1% safranin-O solution.

Following this, the slides were dehydrated with 95% alcohol for 6 dips and 100%

alcohol for 8 dips. During the dehydration, the metachromatic dye-dye bonding is

destroyed to form an orthochromatic bonding. Therefore, stain intensity can be

directly related to proteoglycan concentration [314, 315].


6.4.3 Proteoglycan quantification: Optical absorbance measurements

In accordance with the protocol developed by Moody and Brown [22] and validated

by Afara and Singh [301], the Beer–Lambert law of optical absorbance was used to

quantify the proteoglycans in the present study. As mentioned, since one safranin-O

molecule binds to one negatively-charged chondroitin 6-sulphate or keratan sulphate

[316], the stain intensity directly corresponds to the proteoglycan concentration;

hence, digital densitometry techniques can be applied to quantify the proteoglycan

concentration.

In the present study, by comparing the digital images of unstained and stained

tissue samples, proteoglycan concentration was quantified based on safranin-O stain

intensity. The unstained samples were imaged using a Nikon Labophot-POL

microscope illuminated by a 6V, 20W halogen lamp. The images were captured

using a Nikon DS-Fi1 5-megapixel CCD camera (Nikon Instruments, Sound Vision

Inc.) at 2560x1960 resolution. After safranin-O staining, images were again taken

while maintaining the same sample position and orientation as for the unstained

samples so that the obtained images could be matched with the images of the

unstained samples. All the settings including the shutter speed and light intensity

were kept unchanged during the image capture.

6.4.3.1 Image processing

The Beer–Lambert law of optical absorbance which relates the stain intensity to the

absorbance is used as the principle for image processing. This law states that the

amount of visible light absorbed by a substance, which is the absorbance (A), is

linear proportional to the concentration (C) of the substance and the length of the

path on which the light has travelled. The light absorbance by a sample is related to

the light transmittance (T) through the sample by the following equation:


logTA −= where 0IIT = (6.1)

Here, 0I is the initial light intensity and I is the light intensity after

transmittance of light through the sample. In this study, absorbance values were

taken as a measure of proteoglycan concentration by implementing Eq. (6.1) above

in ImageJ 1.48v software (National Institute of Health, USA). Firstly, both the

stained and unstained images were opened in ImageJ and converted to 32-bit images.

The unstained converted image was copied and pasted on the stained image using the

“paste control-blend” function. Afterwards, the images were matched manually and

the pixel values were divided using the “paste control-divide” function. Then, the

logarithm to the base-10 was taken at each pixel using the “log” function in ImageJ

and was multiplied by -1 to obtain the absorbance of safranin-O. The image was

adjusted for brightness/contrast afterwards by setting the minimum and maximum

displayed values to 0 and 3, respectively (image-adjust-brightness/contrast-set) in

accordance with the methodology proposed by Moody and Brown [22]. Next, the

scale measurements were adjusted based on the size (in pixels) of the picture and

corresponding distance in millimetres using the “analyse-set scale” function.

Thereafter, absorbance profiles were obtained from the cartilage surface to bone

which correlates to proteoglycan variation with depth in cartilage.

6.4.4 Sample preparation for PLM measurements

Superficial collagen fibres are parallel to the articular surface and their direction

depends on the joint location. The pin-prick test is a standard test that is widely used

to identify the fibre directions in the surface layer of cartilage tissues. The linear-

markers being formed during the pin-prick test are known as split line directions. The

tensile properties are the highest parallel to the split line direction and are


significantly lower in the perpendicular direction of the split lines [317]. Hence,

arguably, the split line direction indicates the predominant fibre direction in the

superficial cartilage layer. The sample thickness, location and orientation of

harvested samples are known to affect the PLM measurement [318, 319].

Birefringence values obtained through PLM measurements are an indication of tissue

anisotropy and affected by the orientation of harvested samples (i.e. whether or not

the sample’s direction is parallel to the split line direction). Therefore, in the present

study, before harvesting the samples for PLM measurements, the split line directions

were identified in three separate shoulder and knee joints using the pin-prick test.

Pin-prick tests were performed by piercing the cartilage surface

perpendicularly using a sharp needle tip dipped in Indian ink. Then, excess ink was

washed away using PBS to observe the predominant fibre directions on the surface of

the cartilage tissues (Figure 6.1). Considering the split line directions, the samples

were harvested such that the longitudinal directions of the samples were parallel to

the split line directions. The samples were harvested from near the central load-

bearing area of the humeral head and from the medial and lateral sides of the femoral

condyle and tibial plateau, and then cryosectioned to 10 μm specimens as described

above in Section 6.4.1.


Figure 6.1: Split line directions identified through the pin-prick test performed on (a) femur; (b) tibia; (c) humeral head; and (d) glenoid of kangaroo knee and shoulder joints

6.4.5 Collagen quantification: PLM measurements

The PLM is widely used to investigate the anisotropic nature of biological tissues

[320, 321]. In principle, when polarised light travels through an anisotropic material

the light is refracted into two polarised wave components, namely, the ordinary wave

and the extraordinary wave. This phenomenon is called double refraction, and the

optically anisotropic materials that demonstrate this characteristic are said to be

birefringent. Depending on the direction of propagation inside the material of

interest, the velocities of these wavefronts would vary. When these out-of-phase

wavefronts are re-combined, the features of the resulting wavefront are considered to

be indicators of material anisotropy.


Electrical fields, vibrating in planes perpendicular to the transmitted direction

of natural light, can be restricted to one plane using filters. The resulting wave that

occurs due to the restriction is referred to as polarised light. In PLM, a filter called

the “polariser” is responsible for converting the natural light to polarised light. The

ordinary and extraordinary wavefronts, created after the polarised light is projected

onto the material, are combined together using a second polariser called the

“analyser”. When these two filters are perpendicular to each other (i.e. cross-

polarised), there would be no resulting wavefront. This is indicated by a dark view

through the microscope eyepiece. When PLM is in cross-polarised configuration, and

when supposedly anisotropic material placed on the circular microscopy stage is

rotated, the sample will be illuminated depending on the anisotropic characteristics

of the material. For cartilage specimens, the maximum illumination or contrast can

be seen when the axis perpendicular to the cartilage surface makes 45° with the axis

of the microscope.

In this study, a Nikon Labophot-POL microscope was used for the PLM

measurements. While the polariser, analyser and λ/4 wave plate in place, the

exposure time, gain, focus and contrast were first adjusted to obtain a clear image.

Then, the sample was placed on the rotatable stage with the articular surface facing

the microscope. The rotatable stage was positioned to 0° and the cross-polarised

configuration was checked before proceeding further. The sample was then rotated in

intervals of 45° from its original principal direction and images were taken in order

to have a comparative idea of the anisotropy of the tissue. The obtained images were

analysed using ImageJ software to obtain a quantitative value for the transmittance of

light through the samples and hence an indicator of the fibre directions with depth.



6.5.1 Differences in proteoglycan concentration with depth in knee and shoulder cartilage

For the samples harvested from knee and shoulder joints, the variations of

proteoglycan concentration with cartilage depth and location based on the optical

absorbance measurements are shown in Figure 6.2. For the lateral femur (LF), medial

femur (MF) and lateral tibia (LT) cartilages, with depth, proteoglycan concentration

increased to a maximum value of approximately 20–30% of tissue depth and

decreased afterwards. In contrast, for the medial tibia (MT), proteoglycan

concentration increased with depth, while for the humeral head (H) cartilage

apparent increase or decrease in proteoglycan concentration were not identified

(Figure 6.2(a)), therefore can be considered as homogeneous compared to

proteoglycan variation in knee cartilage. The findings on proteoglycan distribution

with depth for MT cartilage is similar to the findings on canine MT cartilage reported

in a previous study [322]. To the best of the authors’ knowledge, depth-dependent

proteoglycan variations for other locations in the knee and humeral head cartilage

have not been specifically reported in the literature. Nonetheless, we believe that the

proteoglycan variation with depth must be related to the patterns and magnitudes of

loads experienced by the specific tissue. Therefore, specific investigations need to be

carried out in future research in order to identify the relationship between load

magnitude, pattern and depth-dependent proteoglycan distribution. This could be

invaluable for fine-tuning tissue engineering strategies for cartilage tissues.

The areas under absorbance curves (which can be taken as an indicator of the

amount of proteoglycans in tissue [301]), showed that the LF, MF and LT cartilages

had a higher amount of proteoglycans, while in H and MT cartilages the amount was

low (Figure 6.2(b)). Proteoglycan content in the knee cartilage, at all four locations,


were significantly higher than in the shoulder cartilage (p<0.005). Statistical power

analysis indicated that sample size, n=3, is even sufficient (Power=0.9928) to

differentiate concentration differences of 0.05 absorbance units. The safranin-O

staining for LF, MF, LT, MT and H cartilages, shown in Figure 6.2(c), also reflected

these results, in addition to the proteoglycan distribution shown in Figure 6.2(a).

Figure 6.2: (a) Variation in proteoglycan concentration (indicated by light absorbance by safranin-O) with depth for samples harvested from four locations of knee cartilage (i.e. lateral femur, medial femur, lateral tibia, medial tibia) and from central humeral head in shoulder joint; (b) Area under absorbance curve, i.e. proteoglycan content in LF, MF, LT, MT and H; (c) LF, MF, LT, MT and H cartilage stained by 0.1% safranin-O indicating the proteoglycan variation with depth


These results together explain the anticipated reasons for the differences

observed in the findings on kangaroo shoulder cartilage in Chapter 5 and the reported

studies in the literature for knee cartilage. In other words, chondrocytes synthesise

the cartilage matrix based on the mechanical stimuli the tissue receives: the higher

the magnitude and frequency of compressive forces, the higher the amount of

proteoglycans in the tissue. Due to the higher amount of proteoglycans in knee

cartilage, it can also be postulated that its contribution to the tissue behaviour is

considerably higher than in shoulder cartilage. This, in fact, could be the case for

the results discussed later in this chapter (Section 6.5.3). In the following sections,

we further prove this by showing the collagen structural differences and their

possible implications for the mechanical behaviour differences in knee and shoulder

cartilage.

6.5.2 Differences in collagen network of knee and shoulder cartilage

The PLM images of samples harvested from the MF of a kangaroo knee joint are

shown in Figure 6.3(a). At 0°, when the articular surface of the samples was facing

the microscope, confirming the cross-polarised configuration, the light did not reach

the eyepiece and thus appeared completely dark. When the sample was rotated in 45°

increments, sequential bright and dark images were observed (Figure 6.3(a)). This

was similar for samples harvested from the LF, LT and MT. However, there were

differences between the samples harvested from the knee and humeral head which

are discussed later.

In images that appeared bright (e.g. the image at 45° in Figure 6.3(a)), the

superficial zone was brightly visible, followed by a dark zone which was the

transition or middle zone of the cartilage. The large bright zone that appeared next to


the middle zone was the deep zone or radial zone of the cartilage. These

characteristic images are typical for cartilage samples exposed to a polarised light

and have been reported frequently in the literature [320, 321]. The dark appearance

in the transitional zone was due to the random orientation of the fibres. However, in

the superficial zone and radial zone there were definitive predominant directions of

fibre arrangements parallel to the cartilage surface and perpendicular to the

subchondral bone, respectively.

Figures 6.3(b) and 6.3(c) show the gray value of the polarised light transmitted

through the samples after converting the PLM images to 32-bit images in the ImageJ

software. The image analysis gave a quantitative indication of the birefringence or

anisotropy of the cartilage samples. As observed in these graphs, to the upper end of

the graph there is an initial dip in transmitted light values, which is the top of the

cartilage surface. As shown (Figures 6.3(b) and 6.3(c)), for the ease of image

comparison, relative distance has been normalised so that its value at the start of the

subchondral bone is set to unity. A comparison of Figure 6.3(b) and Figure 6.3(c)

clearly indicates that the first set of samples (0°, 90°, 180° and 270° angles) did not

transmit light, while the second set (45°,135°,225° and 315° angles) showed a

definite variation in transmitted light from surface to bone.

Similar to reported studies, based on the graphs in Figure 6.3(c) it can be

observed that the maximum contrast or brightness was for images taken at 45°. In

these images, the initial peak is related to the brightness observed in the superficial

collagen layer. This peak drops to a relatively low value and gradually increases to a

higher value, as seen in the plateau region of the graphs. This variation corresponds

to the change from random fibre configuration (dark appearance) in the transition

zone to a radial configuration in the deep zone, which is the brightest under polarised


light. Similar fibre orientation variations were observed for samples from the rest of

the locations of the knee, while differences were observed for shoulder cartilage as

discussed next.

Figure 6.3: Typical images of cartilage when exposed to polarised light – The dark image at 0° angle corresponds to the cross-polarised configuration; in a sequence of every 45°, bright images are visible indicating the polarised light has been transmitted through the samples; (b) For 0°,90°, 180° and 270° angles, the light transmittance through the samples is literally uniform; (c) For 45°,135°, 225° and 315° angles, the variation in light transmitted through depth corresponds to the zonal arrangement of cartilage fibres (These results are for typical samples harvested from a medial femur of kangaroo knee cartilage)

Figures 6.4(a) and 6.4(b) show the PLM images for LF, MF, LT, MT and H

cartilage and their respective birefringence profiles with depth. Although there seem

to be apparent differences such as the size of the transitional zone and the brightness

of the superficial layer, the birefringence profiles of the knee cartilage samples, in

general, were similar (Figure 6.4(b)). In contrast, the PLM images of the shoulder

cartilage samples (H in Figure 6.4(b)) were characterised by a bright superficial layer

followed by a dark region up to the subchondral bone. Therefore, it seemed that the


fibres in the region, after the superficial layer of the H cartilage, were randomly

oriented and there seemed to be no apparent radial zone. In order to further confirm

this finding, 10 μm samples were stained with standard picrosirius-red staining

protocol and imaged using a confocal laser microscope (Nikon A1R confocal, Nikon,

Japan) with a 40x Nikon oil-immersion objective lens. For picrosirius-red staining,

samples were stained in 0.1% picrosirius red (Sirius red F3B and saturated picric

acid) for 90 minutes.

Figure 6.4: (a) PLM images obtained from four locations of kangaroo knee (LF, MF, LT and MT) and from the central humeral head; (b) Depth-dependent light transmittance profiles of the samples (i.e. LF, MF, LT, MT and H)

Figure 6.5(a) shows the confocal images taken near the subchondral bone of a

typical sample harvested from the humeral head of a kangaroo shoulder. Although


not definitive, the fibre direction was observed to be perpendicular near the bone

(indicated by the red arrow in Figure 6.5(a)). However, careful observation showed

that the fibre arrangement in the top portion of Figure 6.5(a) seemed to have already

changed to a random arrangement (the black arrow in Figure 6.5(a)). This random

fibre arrangement and the transition of fibres from a perpendicular arrangement to a

random arrangement are clearly visible in Figure 6.5(b) and Figure 6.5(c),

respectively. Therefore, it seems that only a small deep zone of perpendicular fibres

is present in shoulder cartilage, while the transitional zone is noticeably high. This is

arguably due to the lower compressive forces experienced by the shoulder cartilage.

The PLM images in Figure 6.4(a) show that the deep zone was clearly visible

in all the samples harvested from four locations in the knee joint. In contrast, the

deep zone of the shoulder cartilage was not visible in the PLM images, while the

confocal images confirmed that the deep zone of the shoulder cartilage was

considerably small. The size of the deep zone was largest in the MF and tended to

vary with location. Therefore, the results altogether pointed to the conclusion that the

fibre arrangement might have adapted to the magnitude, frequency and mode of

forces experienced by the tissue. Given this, it is highly possible that MF cartilage is

the largest compressible load-bearing cartilage in kangaroo knee, while the

magnitude and frequency of the compressive loads on shoulder cartilage might be

considerably small. By considering and comparing the PLM and confocal images

obtained for both shoulder and knee cartilage it can be confidently concluded that the

superficial layer is the most prominent feature of the shoulder collagen network and

hence may considerably affect the mechanical behaviour.


Figure 6.5: (a) Confocal image of a typical cartilage sample harvested from the kangaroo humeral head indicating the region (red arrow) near the calcified bone where fibres are perpendicular to the bone – in the same image, near to the top (black arrow), the transition from perpendicular fibres to a random fibre arrangement can be observed; (b) Confocal image enlarged from top region of image (a) indicating random fibre arrangement; (c) Transition from near perpendicular to random fibre arrangement is shown in this enlarged figure taken from the transitional area of image (a)


6.5.3 Comparison of strain-rate-dependent mechanical behaviour and biomechanical properties of knee and shoulder cartilage

In order to compare the mechanical behaviour and properties of knee and shoulder

cartilage and to investigate the proteoglycan and superficial collagen contributions to

the strain-rate-dependent behaviour of knee cartilage, a similar mechanical testing

procedure employed for shoulder cartilage (Section 5.4) was conducted on knee

cartilage. In other words, 8 mm diameter osteochondral cartilage samples (2–3 mm

subchondral bone) harvested from the MF were tested at 10-4/s, 5x10-4/s, 5x10-3/s and

10-2/s strain-rates. The MF was chosen for this study based on the above results of

the PLM and histological studies. The PLM study indicated that the collagen

architecture of MF cartilage is structurally different from the shoulder cartilage and

that proteoglycan concentration profiles with depth in the MF cartilage is

inhomogeneous. It is believed that the conclusions made in the follow-up study based

on MF cartilage would not change had the tests been performed on samples taken

from the LF, LT and MT of the knee. This is because, in the previous sections, it was

shown that collagen network of samples from all four locations had similar

anisotropic and inhomogeneous nature.

The harvested MF samples were subjected to 25% engineering strain where

thickness was estimated based on the average ultrasound speed reported for knee

cartilage in the literature, which is 1627 m/s [323]. Next, the samples were incubated

in 0.1 mg/ml trypsin–PBS solution at 37 oC for 4 hrs to completely remove the

proteoglycans and were tested again at the aforementioned four strain-rates.

Subsequently, the proteoglycan-removed samples were also treated with 30 U/ml

collagenase for 44 hrs to severely degrade the superficial collagen. Afterwards, the

mechanical testings were conducted again. The objective was to quantify the

contribution of proteoglycans and superficial collagen to the mechanical behaviour


of kangaroo knee cartilage and to compare the findings with the conclusions made

for shoulder cartilage. The same experimental protocols described in Chapters 4 and

5 were followed in these testings too.

6.5.3.1 Contribution of proteoglycans to the strain-rate-dependent behaviour of kangaroo knee cartilage

The results indicated that kangaroo knee cartilage was strain-rate-dependent (Figure

6.6(a)). The average thickness (1.04±0.23 mm) of the knee cartilage samples (n=9)

was significantly larger than the average thickness (0.72±0.13 mm) of the tested

shoulder cartilage samples (n=51) (p<0.005). The reasons for this difference in

thicknesses can be attributed to the different forces experienced and differences in

joint congruence in knee and shoulder joints [324]. The average stiffness of the knee

cartilage (n=9), indicated by the Young’s modulus, was also higher than that of the

shoulder cartilage (n=51) at all four strain-rates tested (p<0.05). Statistical power

analysis indicated that sample size, n=10, is sufficient (Power=0.8049) to

differentiate between mean stiffness of shoulder and knee cartilage.

Trypsin treatment reduced the stiffness of the knee cartilage significantly at all

strain-rates as indicated by the decreases in Young’s modulus (p<0.005) (Figure

6.6(c)). Although the treatment degraded the ability of the tissue to respond to strain-

rates, it still demonstrated the strain-rate-dependency (Figure 6.6(a)), similar to

observations made on the shoulder cartilage in Chapter 5. For comparison purposes,

variations of normalised force with indentation are shown for both knee and shoulder

cartilage when the proteoglycans were completely removed (Figure 6.6(a) and Figure

6.6(b)). The results clearly indicated that the removal of all proteoglycans had much

more effect on the knee cartilage at all strain-rates compared to the shoulder

cartilage. This was further demonstrated when the percentage decreases in Young’s

modulus due to trypsin treatment for knee and shoulder cartilage were compared


(Figure 6.6(d)). In other words, the percentage decrease in Young’s modulus for the

knee cartilage was 83.7±5.9%, 85.0±3.6%, 64.7±15.4% and 53.6±19.5% for 10-4/s,

5x10-4/s, 5x10-3/s and 10-2/s strain-rates, respectively. For the shoulder cartilage,

however, it was approximately in the range of 35–40%, as reported in Chapter 5 and

demonstrated in Figure 6.6(d). Further, this percentage decrease in Young’s modulus

of the knee cartilage was significantly higher than for the shoulder cartilage

(p<0.005). These results suggest that proteoglycans in the knee cartilage play a

relatively larger role in the mechanical behaviour of tissue than the proteoglycans in

the shoulder cartilage. These results are reasonable and not surprising considering

that knee cartilage bears more compressive load than shoulder cartilage. Hence, the

amount and concentration of proteoglycans are higher in the knee cartilage, and

hence the contribution of the proteoglycans to the mechanical behaviour of the tissue

is higher.

It was intriguing to note that the percentage decreases in Young’s modulus at

the lowest two strain-rates (i.e. 10-4/s and 5x10-4/s) were considerably larger than at

the highest two strain-rates (i.e. 5x10-3/s and 10-2/s), with a difference of

approximately 25%. Further, the percentage decrease in Young’s modulus at 10-4/s

was significantly different to the percentage decrease in Young’s modulus at 5x10-3/s

and 10-2/s (p<0.05). However, no significant differences in the percentage decrease

in Young’s modulus were identified at the two lowest strain-rates (p=0.512).

Moreover, the percentage decrease in Young’s modulus at 5x10-4/s was significantly

different to the decreases at 5x10-3/s and 10-2/s (p<0.005). Additionally, the

percentage decreases in Young’s modulus at the two highest strain-rates were not

significantly different either (p=0.403). Together, these results confirmed that


proteoglycans play a more significant role in tissue behaviour at low strain-rates (10-

4/s) than at large-strain-rates (10-2/s) in knee cartilage tissues.

Figure 6.6: Normalised force vs indentation graphs for: (a) normal and trypsin-treated (in 0.1 mg/ml for 4 hrs) knee cartilage; (b) normal and trypsin-treated (in 0.05 mg/ml for 4 hrs) shoulder cartilage; (c) the effect of complete removal of proteoglycan (due to 0.1/mg/ml trypsin treatment for 4 hrs) on Young’s modulus of kangaroo knee cartilage; (d) Comparison of percentage decrease in Young’s modulus due to complete removal of proteoglycans for kangaroo knee and shoulder cartilage

These results on kangaroo knee cartilage are remarkably consistent with the

conclusions found in previous studies in the literature [16, 19]. As mentioned in

Chapter 5, it has been noted in the literature that the equilibrium properties (extracted

at very low strain-rates) of cartilage are governed by proteoglycans, while the

dynamic properties (extracted at high strain-rates) are governed by the collagen

network. Hence, with an increase in strain-rate, the proteoglycan contribution


decreases and the collagen network begins to considerably affect the tissue

behaviour. This is, however, different for shoulder cartilage where the proteoglycans

equally contribute to the tissue behaviour at small and large strain-rates. Further,

based on the findings in the literature [16] and the above-mentioned findings (Figure

6.6) it was speculated that mechanical testing on knee cartilage tissues in which the

proteoglycan had been completely removed and which had been treated in

collagenase for 44 hrs to degrade the superficial collagen would show that superficial

collagen contributions at low and high strain-rates are different. The results of this

testing are discussed in the following section.

6.5.3.2 Contribution of superficial collagen to the strain-rate-dependent behaviour of kangaroo knee cartilage

Collagenase treatment for 44 hrs reduced the tissue stiffness at all strain-rates and the

differences were statistically significant compared with the stiffness after trypsin

treatment (p<0.005) [6.7(a)]. The results further indicated that the contribution of

superficial collagen at low (10-4/s and 5x10-4/s) and high strain-rates (5x10-3/s and

10-2/s) were statistically different and that the contribution increased with the strain-

rate (Figure 6.7(b)). The superficial collagen contributions were 6.5±6.2%,

4.8±2.9%, 13.8±12.4% and 14.6±7.2% at 10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s strain-

rates, respectively. The superficial collagen contribution values reported in the

literature for bovine cartilage are 3.6%, 6.6% and 14.8% for 5x10-4/s, 5x10-3/s and

5x10-2/s strain-rates, respectively [16]. Although these values are smaller than the

values in the present study (perhaps due to the different tissue used), the finding on

the increased superficial collagen contribution with strain-rate is similar to the

findings in the literature.

The superficial collagen contributions at the two lowest strain-rates (10-4/s and

5x10-4/s) were not significantly different (p=0.538). Likewise, the contributions were


not significantly different at the two highest strain-rates (5x10-3/s and 10-2/s)

(p=0.449). However, the contribution of superficial collagen to tissue behaviour was

significantly low at 10-4/s when compared with the contribution at 10-2/s strain-rate.

Probably due to high standard deviation at 5x10-3/s, the statistical differences were

not identified when the superficial collagen contributions at 10-4/s and 5x10-3/s were

compared (p=0.058). Nevertheless, the superficial collagen contribution at 5x10-4/s

was significantly different from the contribution at the two highest strain-rates

(p<0.005). Therefore, as expected, it can be stated that with an increase in strain-rate

the superficial collagen begins to considerably affect the knee cartilage behaviour,

thus confirming the results reported in both the previous section (Section 6.5.3.1) of

this study and the literature.

Figure 6.7: Percentage decrease in Young’s modulus after complete proteoglycan-removed samples were treated for 44 hrs in collagenase; (b) Contribution of superficial collagen to tissue behaviour at four strain-rates (10-4/s, 5x10-4/s, 5x10-3/s and 10-2/s)

The mechanical test results confirmed that there were definite differences in

the mechanical properties of the knee and shoulder cartilage. Even though the

responses of both cartilage types were more or less similar, especially in terms of

strain-rate-dependency, the contributions of the underlying components (in


particular, collagen and proteoglycans) were different. The results of the present

study not only further cemented the conclusions drawn in Chapter 5 but also

confirmed the importance of superficial collagen and collagen architecture in the


6.5.4 Significance and implications for numerical modelling and tissue engineering

6.5.4.1 Implications for tissue engineering strategies

The composition and structural features of the collagen network and hence the

mechanical properties depend on the magnitude and pattern of loading experienced

by the cartilage tissue. The results of the present study demonstrate that the

proteoglycan distribution with depth and the features of the collagen network in knee

and shoulder cartilage are noticeably different. The magnitude and pattern of loading

seem to affect the size of the superficial, transitional and radial zones. Hence, it is

plausible that the mechanical and biological characteristics of these zones are linked

to the stress, strain, and fluid flow in these zones as also postulated by earlier studies

[18, 325].

Therefore, joint-specific cartilage tissue generation would require approaches

that are catered to the specific tissue of interest so as to achieve the compositional

and structural features that are appropriate to it. Nonetheless, replicating a tissue

similar to the characteristics of the native tissue (e.g. the distribution of proteoglycan

concentration with depth and the arcade-like collagen network) remains a significant

challenge in the tissue engineering field. The findings of the present study suggest

that it is important to include procedures that signal to the (new) growing tissue the

mechanical forces it will experience in the future. As a result, the tissue will be able

to facilitate its growth to a status (or to an extent) where it is able to withstand

external forces specific to the joint.


6.5.4.2 Joint-specific differences in the prevalence of osteoarthritis

Osteoarthritis does not affect all joints equally. It is more prevalent in the hip, knee,

spine and metatarsophalangeal and interphalangeal joints [169]. Although

degenerative changes happen in ankle, wrist, elbow and shoulder joint cartilage, they

do not progress to a disease state as frequently as in the hip and knee. The reasons

why some joints are more affected by osteoarthritis than others still remain elusive

[169, 326]. The most common example for this is the difference in progression of

osteoarthritis in the knee and ankle [169, 327]. Although loaded more heavily than

the knee, the initiation and progression of osteoarthritis in the ankle has been

identified to be less frequent than in the knee. Anatomical differences such as joint

congruence and stability are suggested as the reasons; however, these do not fully

explain the differences [169]. Extensive studies [326-328] have concluded that ankle

chondrocytes respond quickly to damage with higher proteoglycan synthesis and are

also metabolically more active in terms of degradation compared to knee

chondrocytes. This is an indication that ankle cartilage has a higher capacity to repair

than knee cartilage. Ruling out the genetic difference between knee and ankle

chondrocytes, through a series of experiments it has been concluded that the

difference in native extracellular matrix of the two tissues is the main factor affecting

the chondrocyte metabolism [169]. Hence, it is important to investigate the

differences in the native matrix of joints that have different susceptibilities to

osteoarthritis. Therefore, this study, which compared the shoulder and knee

extracellular matrix, can be considered as a necessary step towards identifying

plausible reasons for differences in osteoarthritis initiation in different joints.

6.5.4.3 Implications for numerical modelling

Modelling cartilage tissue requires an understanding about the relationship between

its structure and the respective biomechanical functions. Most numerical models


available in the literature are for knee cartilage tissues. Only limited investigations

have been carried out to explore the structure–function relationships of shoulder

cartilage. As indicated by the results of the present study, the conclusions drawn for

knee cartilage cannot be directly generalised to other cartilage tissues, such as

shoulder cartilage, which are loaded differently. Therefore, in modelling joint-

specific cartilage tissues, differences in the collagen structural feature and

composition should be acknowledged. For example, the results in the current study

indicated differences in the proteoglycan distribution in kangaroo knee and shoulder

cartilage. Additionally, differences in the anisotropy of collagen network in knee and

shoulder cartilage in terms of the size of the superficial, transitional and deep zones

as well as differences in fibre directions in individual zones were also observed.

These differences are likely to be important in developing numerical models and

could significantly affect model predictions.


In this chapter, we mainly investigated the compositional, microstructural and

biomechanical differences between knee and shoulder cartilage with the objective of

explaining the different results observed in Chapter 5 and in reported studies in the

literature. Additionally, we investigated how the microstructure and composition of

the kangaroo shoulder and knee cartilage affect the mechanical behaviour of the

tissue. The implications of the results of these investigations for the numerical

modelling of cartilage and tissue engineering strategies were also discussed in this

chapter. The following conclusions can be made from the results of the study:

• High and frequent weight-bearing knee cartilage showed a clear depth-

dependent proteoglycan distribution as opposed to the shoulder cartilage (a

low weight-bearing cartilage) where there were no apparent trends in


proteoglycan distribution with cartilage depth. In addition, the proteoglycan

content in the knee cartilage was higher than in the shoulder cartilage.

• Proving that the magnitude and frequency of loading affects the structural

feature of the collagen network, knee cartilage showed a distinctly different

collagen structure than shoulder cartilage. A prominent deep zone, where

collagen is anchored perpendicular to the subchondral bone, was observed in

the knee cartilage. Differences in the size of the superficial, transitional and

deep zones were also identified in the samples taken from different locations

of the knee.

• Superficial collagen appeared to be the most prominent feature of the

collagen network of shoulder cartilage. The confocal images confirmed that

the size of the deep zone in shoulder cartilage was small and the transitional

zone was considerably large.

• Proteoglycan contribution to knee cartilage behaviour was significantly larger

than collagen contribution at all strain-rates tested. However, as mentioned in

chapter 5, results for shoulder cartilage were different where collagen

contribution on the tissue behavior was larger than proteoglycans.

• In congruence with the findings in the literature, this study was able to

conclude that proteoglycans significantly affect the knee cartilage behaviour

at low strain-rates; hence, the equilibrium properties of knee cartilage tissues

would be governed by proteoglycans.

• The effect of superficial collagen on the knee cartilage behaviour increased

with increasing strain-rate, reaching a considerably high value (~15%) at the

highest strain-rate tested. However, unlike in the knee cartilage, no trend was

evident in the superficial collagen contribution with an increase in strain-rate.


• Together, these results confirmed the findings in Chapter 5 and the reported

studies in the literature [16], demonstrating the significant contribution of

superficial collagen on the strain-rate-dependent behaviour of shoulder

cartilage.

• Based on the results, it is important to control tissue engineering strategies in

order to generate joint-specific tissues. The findings are useful for the

numerical modelling of shoulder cartilage tissue.


Chapter 7: Conclusions

7.1 CONCLUSIONS

This research explored the factors affecting the strain-rate-dependent behaviour of

kangaroo shoulder cartilage by systematic experimental and numerical studies. New

knowledge on the mechanical behaviour of kangaroo shoulder cartilage was

developed by introducing: 1) a porohyperelastic model with a strain-rate-dependent

permeability function; and 2) an experimental approach to investigating the effects of

cartilage constituents on cartilage mechanical behaviour. In addition, by introducing

kangaroo as a model, the present study has comprehensively compared shoulder and

knee cartilage with the objective of investigating the relationship between cartilage

structure and mechanical behaviour in the context of the strain-rate-dependent

behaviour of cartilage tissues. The findings of this research inform the cartilage

modelling community about extracellular matrix features and the underlying factors

that need to be considered when modelling low and high weight-bearing cartilage

tissues such as the shoulder and knee, respectively. In addition, this research informs

tissue engineers about what might be the most important features to consider when

engineering a cartilage tissue for low and high compressive load-bearing joints such

as the shoulder and knee, respectively.

Based on this research, it can be concluded that kangaroo is a suitable model

for future biomechanical research on shoulder cartilage. The biomechanical

properties and behaviour of the kangaroo shoulder cartilage tissues were in general

agreement with that of human shoulder cartilage tissues. Further, the different

loadings encountered in the kangaroo’s upper and lower limb cartilage provide a

natural source for investigating how mechanical forces affect the development,

Chapter 7: Conclusions 171

composition (e.g. proteoglycan distribution) and structure (e.g. collagen architecture)

of the low and high load bearing cartilages and the progression of osteoarthritis in

low and high load bearing joints. Future experiments using kangaroo as a model are

promising for gaining insights into tissue engineering strategies that are necessary to

develop joint-specific cartilage tissues.

The findings of the present study indicate that the mechanical behaviour of

kangaroo shoulder cartilage is strain-rate-dependent. Its solid skeleton behaviour was

adequately represented by the 2-term reduced polynomial hyperelastic model in this

study’s experiments, while lower-order material models such as the neo-Hookean

and Mooney–Rivlin models were not adequate. Based on the formulation of the

strain-rate-dependent permeability model, it was found that the permeability and

strain-rate are negatively correlated (i.e. permeability is reduced when the strain-rate

is increased). The strain-dependent and strain-rate-dependent models affected the

tissue behaviour considerably at all strain-rates tested, while at high strain-rates the

latter became more significant. Therefore, in addition to solid–interstitial frictional

fluid interaction, the pressure drag forces and possibly the inertia forces begin to play

a significant role in tissue behaviour at high strain-rates. Therefore, it was concluded

that strain-rate-dependent permeability is one of the mechanisms governing the

strain-rate-dependent behaviour of cartilage tissues. Computational models have the

potential to benefit from the inclusion of strain-rate-dependent permeability in terms

of better prediction of cartilage response to external loads, especially at high strain-

rates. Since all aspects of isotropic fluid and solid behaviour were evaluated in the

strain-rate-dependent model, the model deviations at the highest strain-rate can be

concluded to be a result of the anisotropic solid properties and fluid behavior of the

tissue.

172 Chapter 7: Conclusions

Proving the direct role of proteoglycan in facilitating the compressive loads,

the progressive removal of proteoglycans reduced the tissue stiffness gradually at all

strain-rates. Proteoglycan depletion and superficial collagen disruption substantially

compromised the ability of the tissues to resist external compressive loading at

different strain-rates, increasing the risk of bone-to-bone contact. Total proteoglycan

removal and severe degradation of superficial collagen increased the permeability of

cartilage tissue. Even after complete removal of proteoglycans or severe degradation

of superficial collagen, the tissues still exhibited strain-rate-dependency. Therefore, it

was concluded that the dense collagen meshwork has the ability to sustain the pore

size of cartilage so that solid–interstitial fluid frictional interaction is able to facilitate

the strain-rate-dependent behaviour. It was also concluded that the effect of surface

lipids on the strain-rate-dependent mechanical behaviour of cartilage tissues is

minimal.

Superficial collagen degradation had the largest effect on tissue stiffness and

strain-rate-dependency when compared with proteoglycan degradation. Hence, it was

concluded that superficial collagen plays a more significant role than proteoglycans

in facilitating the strain-rate-dependent behaviour of kangaroo shoulder cartilage. In

addition, superficial collagen contributed evenly to tissue behaviour at all strain-

rates, which confirmed its significance in governing the mechanical behaviour of

shoulder cartilage tissues. However, these findings were different from the

observations made on kangaroo knee cartilage where superficial collagen contributed

less than proteoglycans to the mechanical behaviour, although its role became

substantially more significant at the higher strain-rates tested. Based on

computational modelling, it was found that collagen disruption would lead to

shoulder cartilage being damaged faster than when proteoglycans were depleted.


Therefore, for shoulder cartilage, collagen disruption can be regarded as more

damaging than proteoglycan depletion.

Adaptation of the cartilage tissues to the mechanical environment was

confirmed by the conclusions drawn from the study of the composition and

microstructure of both shoulder and knee cartilage. It was concluded that knee

cartilage (high and more frequent weight-bearing) has an inhomogeneous

proteoglycan distribution compared to shoulder cartilage (low weight-bearing). In

addition, the proteoglycan content in knee cartilage was considerably higher than in

shoulder cartilage, indicating that the magnitude and frequency of loading affect the

proteoglycan distribution and content. The collagen network of knee cartilage

showed a distinctly different collagen structure than the collagen network of shoulder

cartilage. Although structurally similar, differences in the size of the superficial,

transitional and deep zones were also identified in different locations of the knee.

Therefore, it can be concluded that the structural features of the collagen network

also adapt to external mechanical loading. Superficial collagen was the most

prominent feature of the shoulder collagen network and the microstructure from the

confocal study confirmed that the size of the deep zone in kangaroo shoulder

cartilage is small (i.e. fibres perpendicular to the calcified zone were rarely visible in

the shoulder cartilage).

In summary, the research conducted in this project explored the factors

affecting the strain-rate-dependent behaviour of shoulder cartilage tissues. The main

findings of this study have significant implications for the computational modelling

of shoulder cartilage tissues and tissue engineering approaches to engineering joint-

specific cartilages.


7.2 LIMITATIONS

In terms of experimental limitations, ideally, the present study required human

cartilage tissues. However, obtaining human tissues, especially in the required

quantities, was not feasible due to ethical considerations and difficulties in obtaining

young to mature tissues. Therefore, kangaroo was chosen as the animal model which

the findings of the present study indicated as a suitable for biomechanical

investigation of the shoulder cartilage. However, there were additional limitations

such as the inability to obtain shoulder and knee joints from the same animal because

animals were not specifically euthanised for the present study.

The scope of the present study had to be limited to indentation tests. Although

tension tests are required to develop a comprehensive FE model for the tissue tested,

there were no appropriate resources available to carry out tension tests. An

investigation into the effect of osmotic pressure on the strain-rate-dependent

behaviour of the kangaroo shoulder cartilage was not conducted. However, it would

be important to carry out that study in order to comprehensively understand the

response of the shoulder cartilage to external environmental changes (i.e. changes in

saline concentration).

7.3 FUTURE RESEARCH DIRECTIONS

Despite vast knowledge on cartilage tissues there still exists a significant need for

more research to be carried out in order to achieve the ultimate objectives such as

facilitating the early diagnosis of osteoarthritis, understanding the reasons for

osteoarthritis and engineering cartilage tissues that can function appropriately in vivo

under static and dynamic loading. The extension of this research can mainly be

divided into two parts: improvement of the porohyperelastic cartilage model, and

experimental investigation of the dynamic fluid and solid-skeleton behaviour.


In terms of improving the porohyperelastic FE model with strain-rate-

dependent permeability, which was developed in the present study, tension

experiments on cartilage tissue should be performed to obtain the transverse material

parameters. The inclusion of transverse material parameters in the model could

improve the model results, as implied by the results in Chapter 5. Additionally,

follow-up studies investigating the effect of cross-linking on strain-rate-dependent

cartilage tissue behaviour may provide information on how cross-linking, which is

one of the main features of the load-bearing unit of cartilage, facilitates the dynamic

load-bearing ability of cartilage tissues.

The potential techniques that can be utilised to investigate the fluid behaviour

of cartilage tissue under dynamic loading are high-resolution MRI coupled with

microscopy–micro/nano indentation techniques. High-resolution MRI coupled with

simultaneous mechanical testing can provide potentially valuable information about

fluid behaviour in normal and osteoarthritis-affected cartilage. Moreover, this

methodology would also be valuable in assessing the performance of engineered

cartilage tissues so as to identify whether fluid support is appropriate for long-term

performance.

There are a few plausible ways to investigate collagen behaviour during

dynamic loading. One way is to couple confocal microscopy with micro/nano

manipulation devices or tracking cells during deformation in order to infer

information regarding the potential deformation of collagen fibre as a bulk. Injecting

particles, in particular fluorescence particles, and tracking them using imaging

techniques can also provide information regarding collagen behaviour under dynamic

loading. The results from such studies, if successful, would provide important

information regarding differences in the structural response of normal and


osteoarthritis-affected cartilages. This information could also be used for the

validation of existing and future multiscale numerical models.

Future research that compares the development processes of cartilage tissues

from joints that have different susceptibilities to osteoarthritis (i.e. the knee and

shoulder) will provide insights into the underlying reasons for these different

susceptibilities and thereby lead to the identification of possible preventive strategies

for osteoarthritis. In this context, kangaroo can serve as a valuable animal model for

future research studies in this area.

If conducted, these recommended studies and methodologies will hopefully

contribute to better understanding the internal behaviour of cartilage tissues in

addition to the physiological factors affecting the health and development of the

tissue. Thereby, it will also provide valuable insights into the development of

functionally viable cartilage tissues and the factors affecting osteoarthritis

development.


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Noyel Deegayu Namal Bandara Thibbotuwawa B. Sc. Eng ... Deegayu Namal...Noyel Deegayu Namal Bandara Thibbotuwawa B. Sc. Eng. (Hons), M. Phil. Submitted in fulfilment of the requirements