With the aim of providing information for modelling joint and limb systems, widely available constitutive hyperelastic laws are evaluated in this paper for their ability to predict the mechanical responses of normal and osteoarthritic articular cartilage. Load-displacement data from mechanical indentation were obtained for normal and osteoarthritic cartilage at 0.1 s(-1) and 0.025 s(-1) and converted to the stress-stretch ratio. The data were then fitted to the Arruda-Boyce, Mooney-Rivlin, neo-Hookean, Ogden, polynomial, and Yeoh hyperelastic laws in the MATLAB environment. Although each of the hyperelastic laws performed satisfactorily at the higher rate of loading, their ability to fit experimental data at the lower loading rate varied considerably. For the preferred models, coefficients were provided for stiff, soft, and average tissues to represent normal and degraded tissue at high and low loading rates. The present authors recommend the use of the Mooney-Rivlin or the Yeoh models for describing both normal and degraded articular cartilage, with the Mooney-Rivlin model providing the best compromise between accuracy and required computational power.

It is common practice in laboratories to create models of degraded articular cartilage in vitro and use these to study the effects of degeneration on cartilage responses to external stimuli such as mechanical loading. However, there are inconsistencies in the reported action of trypsin, and there is no guide on the concentration of trypsin or the time to which a given sample can be treated so that a specific level of proteoglycan depletion is achieved. This paper argues that before any level of confidence can be established in comparative analysis it is necessary to first obtain samples with similar properties. Consequently, we examine the consistency of the outcome of the artificial modification of cartilage relative to the effects of the common enzyme, trypsin, used in the process of in vitro proteoglycan depletion. The results demonstrate that for a given time and enzyme concentration, the action of trypsin on proteoglycans is highly variable and is dependent on the initial distribution and concentration of proteoglycans at different depths, the intrinsic sample depth, the location in the joint space and the medium type, thereby sounding a note of caution to researchers attempting to model a proteoglycan-based degeneration of articular cartilage in their experimental studies.

Diagnosis of articular cartilage pathology in the early disease stages using current clinical diagnostic imaging modalities is challenging, particularly because there is often no visible change in the tissue surface and matrix content, such as proteoglycans (PG). In this study, we propose the use of near infrared (NIR) spectroscopy to spatially map PG content in articular cartilage. The relationship between NIR spectra and reference data (PG content) obtained from histology of normal and artificially induced PG-depleted cartilage samples was investigated using principal component (PC) and partial least squares (PLS) regression analyses. Significant correlation was obtained between both data (R 2 = 91.40%, p<0.0001). The resulting correlation was used to predict PG content from spectra acquired from whole joint sample, this was then employed to spatially map this component of cartilage across the intact sample. We conclude that NIR spectroscopy is a feasible tool for evaluating cartilage contents and mapping their distribution across mammalian joint. 503-512 (2010). 11. X. Bi, X. Yang, M. P. G. Bostrom, and N. P. Camacho, "Fourier transform infrared imaging spectroscopy investigations in the pathogenesis and repair of cartilage," Biochim.

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A total histological grade does not necessarily distinguish between different manifestations of cartilage damage or degeneration. An accurate and reliable histological assessment method is required to separate normal and pathological tissue within a joint during treatment of degenerative joint conditions and to sub-classify the latter in meaningful ways. The Modified Mankin method may be adaptable for this purpose. We investigated how much detail may be lost by assigning one composite score ⁄ grade to represent different degenerative components of the osteoarthritic condition. We used four ovine injury models (sham surgery, anterior cruciate ligament ⁄ medial collateral ligament instability, simulated anatomic anterior cruciate ligament reconstruction and meniscal removal) to induce different degrees and potentially 'types' (mechanisms) of osteoarthritis. Articular cartilage was systematically harvested, prepared for histological examination and graded in a blinded fashion using a Modified Mankin grading method. Results showed that the possible permutations of cartilage damage were significant and far more varied than the current intended use that histological grading systems allow. Of 1352 cartilage specimens graded, 234 different manifestations of potential histological damage were observed across 23 potential individual grades of the Modified Mankin grading method. The results presented here show that current composite histological grading may contain additional information that could potentially discern different stages or mechanisms of cartilage damage and degeneration in a sheep model. This approach may be applicable to other grading systems.