Indentation stiffness does not discriminate between normal and degraded articular cartilage

Sensitivity of cartilage mechanical behaviour to spatial variations in material properties

Articular cartilage tissue exhibits a spatial dependence in material properties that govern mechanical behaviour. A mathematical model of cartilage tissue under one dimensional confined compression testing is developed for normal tissue that takes account of these variations in material properties. Modifications to the model representative of a selection of mechanisms driving osteoarthritic cartilage are proposed, allowing application of the model to both physiological and pathophysiological, osteoarthritic tissue. Incorporating spatial variations into the model requires the specification of more parameters than are required in the absence of these variations. A global sensitivity analysis of these parameters is implemented to identify the dominant mechanisms of mechanical response, in normal and osteoarthritic cartilage tissue, to both static and dynamic loading. The most sensitive parameters differ between dynamic and static mechanics of the cartilage, and also differ between physiological and osteoarthritic pathophysiological cartilage. As a consequence changes in cartilage mechanics in response to alterations in cartilage structure are predicted to be contingent on the nature of loading and the health, or otherwise, of the cartilage. In particular the mechanical response of cartilage, especially deformation, is predicted to be much more sensitive to cartilage stiffness in the superficial zone given the onset of osteoarthritic changes to material properties, such as superficial zone increases in permeability and reductions in fixed charge. In turn this indicates that any degenerative changes in the stiffness associated with the superficial cartilage collagen mesh are amplified if other elements of osteoarthritic disease are present, which provides a suggested mechanism-based explanation for observations that the range of mechanical parameters representative of normal and osteoarthritic tissue can overlap substantially.

Assessment of Native Human Articular Cartilage: A Biomechanical Protocol

OBJECTIVES

Recapitulating the mechanical properties of articular cartilage (AC) is vital to facilitate the clinical translation of cartilage tissue engineering. Prior to evaluation of tissue-engineered constructs, it is fundamental to investigate the biomechanical properties of native AC under sudden, prolonged, and cyclic loads in a practical manner. However, previous studies have typically reported only the response of native AC to one or other of these loading regimes. We therefore developed a streamlined testing protocol to characterize the elastic and viscoelastic properties of human knee AC, generating values for several important parameters from the same sample.

DESIGN

Human AC was harvested from macroscopically normal regions of distal femoral condyles of patients (n = 3) undergoing total knee arthroplasty. Indentation and unconfined compression tests were conducted under physiological conditions (temperature 37 °C and pH 7.4) and testing parameters (strain rates and loading frequency) to assess elastic and viscoelastic parameters.

RESULTS

The biomechanical properties obtained were as follows: Poisson ratio (0.4 ± 0.1), instantaneous modulus (52.14 ± 9.47 MPa) at a loading rate of 1 mm/s, Young's modulus (1.03 ± 0.48 MPa), equilibrium modulus (7.48 ± 4.42 MPa), compressive modulus (10.60 ± 3.62 MPa), dynamic modulus (7.71 ± 4.62 MPa) at 1 Hz and loss factor (0.11 ± 0.02).

CONCLUSIONS

The measurements fell within the range of reported values for human knee AC biomechanics. To the authors' knowledge this study is the first to report such a range of biomechanical properties for human distal femoral AC. This protocol may facilitate the assessment of tissue-engineered composites for their functionality and biomechanical similarity to native AC prior to clinical trials.

Computational methods for the investigation of ski boots ergonomics

Ski boots are known to cause vasoconstriction in the wearer’s lower limbs and, thus, cause a “cold leg” phenomenon. To address this problem, this work provides a computational framework for analysing interactions between the ski boot and the lower limb. The geometry of the lower limb was derived from magnetic resonance imaging and computed tomography techniques and anthropometric data. The geometry of the ski boot shell was obtained by means of three-dimensional computer aided design models from a manufacturer. Concerning the ski boot liner, laser scanning techniques were implemented to capture the geometry of each layer. The mechanical models of the ski boot and the lower limb were identified and validated by means of coupled experimental investigations and computational analyses. The computational models were exploited to simulate the buckling process and to investigate interaction phenomena between the boot and the lower limb. Similarly, experimental activities were performed to further analyse the buckling phenomena. The obtained computational and experimental results were compared regarding both interaction pressure and displacements between the buckle and the corresponding buckle hooks. These comparisons provided reasonable agreement (mean value of discrepancy between the model and mean experimental results in the tibial region: 20%), underlining the model’s capability to correctly interpret results from experimental measurements. Results identified the critical areas of the leg, such as the tibial region, the calcaneal region of the foot and the anterior sole, which may suffer the most due to the hydrostatic pressure and compressive strain exerted on them. The results highlight that computational methods allow investigation of the interaction phenomena between the lower leg and ski boot, potentially providing an effective framework for a more comfortable and ergonomic design of ski boots.

Machine Learning Classification of Articular Cartilage Integrity Using Near Infrared Spectroscopy

Introduction

Assessment of cartilage integrity during arthroscopy is limited by the subjective visual nature of the technique. To address this shortcoming in diagnostic evaluation of articular cartilage, near infrared spectroscopy (NIRS) has been proposed. In this study, we evaluated the capacity of NIRS, combined with machine learning techniques, to classify cartilage integrity.

Methods

Rabbit (n = 14) knee joints with artificial injury, induced via unilateral anterior cruciate ligament transection (ACLT), and the corresponding contra-lateral (CL) joints, including joints from separate non-operated control (CNTRL) animals (n = 8), were used. After sacrifice, NIR spectra (1000–2500 nm) were acquired from different anatomical locations of the joints (n_TOTAL = 313: n_CNTRL = 111, n_CL = 97, n_ACLT = 105). Machine and deep learning methods (support vector machines–SVM, logistic regression–LR, and deep neural networks–DNN) were then used to develop models for classifying the samples based solely on their NIR spectra.

Results

The results show that the model based on SVM is optimal of distinguishing between ACLT and CNTRL samples (ROC_AUC = 0.93, kappa = 0.86), LR is capable of distinguishing between CL and CNTRL samples (ROC_AUC = 0.91, kappa = 0.81), while DNN is optimal for discriminating between the different classes (multi-class classification, kappa = 0.48).

Conclusion

We show that NIR spectroscopy, when combined with machine learning techniques, is capable of holistic assessment of cartilage integrity, with potential for accurately distinguishing between healthy and diseased cartilage.

Electronic supplementary material

The online version of this article (10.1007/s12195-020-00612-5) contains supplementary material, which is available to authorized users.

Determination of two fluoroquinolones and their combinations with hyaluronan effect in in vitro canine cartilage explants

Background

Previous studies reported the effect of enrofloxacin (Enro) and marbofloxacin (Mar) on cell death and alteration of the key genes involved in catabolic and anabolic processes and demonstrated the beneficial effects of hyaluronan (HA) combined with fluoroquinolones (FQs) on primary canine chondrocytes. This study further determines the effects of these treatments on canine cartilage explants in both normal and interleukin-1 beta (IL-1β)-stimulated conditions.

Methods

We examined sulfate glycosaminoglycan (s-GAG) release, uronic acid (UA) content, and safranin-O staining, as well as the expression patterns of inflammatory, extracellular matrix (ECM) component and enzymes.

Results

Enro treatment alone effectively stimulated proteoglycan anabolism by increasing UA content and glycosaminoglycans (GAGs) in normal and pre-IL-1β-stimulated explant, whereas Mar showed opposite results. The combination of HA and FQs increased s-GAG release and UA content in normal explants in addition to effective down-regulated expression of MMP3. HA reduced the adverse effects of Mar by enhancing UA and GAG contents in both normal and pre-IL-1β-explants. Moreover, HA effectively induced HAS1and ACANup-regulation and reduced MMP9, TNF, PTGS2,and NFKB1 expression for a long term.

Discussion

Our results suggest the direct effects of Enro and Mar may selectively stimulate the conditioned explants to express MMP-codinggenes and promote gene expression involved in matrix production, pro-inflammatory cytokines, and cell degradation in different directions. HA successfully reduced the adverse effects of FQs by enhancing s-GAG and UA contents and down-regulated expression of MMPs.

Effects of corticosteroids and their combinations with hyaluronanon on the biochemical properties of porcine cartilage explants

Background

Intra-articular injection of corticosteroids is used to treat the inflammatory pain of arthritis and osteoarthritis (OA), but our previous study found a deleterious effect of these steroids on chondrocyte cells. Hyaluronic acid (HA) injection has been suggested as a means to counteract negative side effects through replenishment of synovial fluid that can decrease pain in affected joints. To better understand the effects of corticosteroids on these processes, dexamethasone (Dex) and prednisolone (Pred) were administered to porcine cartilage explants at several concentrations with and without HA. We examined corticoid effects by determining sulfate-glycosaminoglycan (s-GAG) and uronic acid (UA) content of the explant media, and safranin-O staining of the cells. Analysis of lactate dehydrogenase (LDH) activity was conducted to assess cell cytotoxicity.

Results

Dex treatment significantly reduced cellular cytotoxicity compared to the other treatment groups, especially with regards to the release of s-GAG, and protects against superficial proteoglycan damage. However, there was no difference between Pred and Dex, with and without HA, in the UA content remaining in porcine cartilage explants.

Conclusions

The data suggest that combinations of Dex and Pred with HA did not have a significant effect on protection or enhancement of the articular cartilage matrix under the current conditions.

Spatial mapping of proteoglycan content in articular cartilage using near-infrared (NIR) spectroscopy

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.

Load-unloading response of intact and artificially degraded articular cartilage correlated with near infrared (NIR) absorption spectra

The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δr, characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δr and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δr. This correlation of δr with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δr values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.

Nanoscale study of cartilage surfaces using atomic force microscopy

Articulating cartilage wear plays an important role in cartilage degeneration and osteoarthritis (OA) progression. This study investigated the changes of mechanical properties and surface roughness of sheep cartilages with wear progression at a nanometre scale. Young sheep’s rear legs were subjected to a series of wear tests to generate worn cartilage samples to simulate the OA progression. Atomic force microscopy (AFM) was used to determine the effective indentation modulus and to measure the surface morphology of moist cartilage surfaces. The study has found that the mean effective indentation modulus values of worn cartilages were lower than that of healthy cartilage as the control sample. A medium-to-strong correlation between the effective indentation modulus values and the OA grades has been found. The relation between surface topography and effective indentation modulus values of the cartilage surfaces with OA progression was weakly correlated. The method established in this study can be implemented to investigate the effective indentation modulus values of clinical osteoarthritic cartilages and to assist in the understanding and assessment of OA.

Repeated measurement of mechanical properties in viable osteochondral explants following a single blunt impact injury

The objective of this work was to develop a method for repeated same-site measurement of mechanical properties suitable for the detection of degenerative changes in a biologically active explant model after a single blunt impact injury. Focal blunt impact injuries to articular surfaces lead to local cartilage degeneration and loss of mechanical properties. We employed a repeated measurement methodology to determine variations in mechanical same-site properties before and after injury in living cartilage, with the hypothesis that normalization with initial mechanical properties may provide a clearer evaluation of impact effects and improve our understanding of the biologic responses to impact injury. Bovine osteochondral explants were cultured for up to 14 days after impact injury. Indentation tests were performed before and after impact injury to assess relative changes in mechanical properties. Creep strain increased significantly in impacted explants after 7 days and in both impacted and control explants after 14 days. Further analysis at 14 days revealed decreases in stretch factor beta, creep time constant and local compressive modulus. A repeated measures methodology reliably detected changes in the mechanical behaviour of viable osteochondral explants after a single impact injury.

ISSUES AND ADVANCES IN THE EARLY STAGE DIAGNOSIS OF OSTEOARTHRITIS

With the progress of localized treatment procedures such as unicompartmental knee replacement, chondrocyte implantation and osteochondral grafting, it has become important to develop a means of assessing early stage cartilage and bone degradation. This review outlines the recent advances in arthroscopic tools, and discusses the major problems and issues faced in developing effective assessment methods. The central problem in joint tissue assessment is to discriminate degradation from the wide variation in normal tissue. This discrimination, however, is far from being realized by current methodologies, and is compounded by the difficulty in correlating structural features with pain and mobility in the joint. In response to these findings, an argument is provided for a new direction in quantitative tissue evaluation using an integrated chemical, structural, and functional approach, and the importance of structure–function–pain relationships.

Contribution of tissue composition and structure to mechanical response of articular cartilage under different loading geometries and strain rates

Mechanical function of articular cartilage in joints between articulating bones is dependent on the composition and structure of the tissue. The mechanical properties of articular cartilage are traditionally tested in compression using one of the three loading geometries, i.e., confined compression, unconfined compression or indentation. The aim of this study was to utilize a composition-based finite element model in combination with a fractional factorial design to determine the importance of different cartilage constituents in the mechanical response of the tissue, and to compare the importance of the tissue constituents with different loading geometries and loading rates. The evaluated parameters included water and collagen fraction as well as fixed charge density on cartilage surface and their slope over the tissue thickness. The thicknesses of superficial and middle zones, as based on the collagen orientation, were also included in the evaluated parameters. A three-level resolution V fractional factorial design was used. The model results showed that inhomogeneous composition plays only a minor role in indentation, though that role becomes more significant in confined compression and unconfined compression. In contrast, the collagen architecture and content had a more profound role in indentation than with two other loading geometries. These differences in the mechanical role of composition and structure between the loading geometries were emphasized at higher loading rates. These findings highlight how the results from mechanical tests of articular cartilage under different loading conditions are dependent upon tissue composition and structure.

Assessment of common hyperelastic constitutive equations for describing normal and osteoarthritic articular cartilage

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.

Comparison of single-phase isotropic elastic and fibril-reinforced poroelastic models for indentation of rabbit articular cartilage

Classically, single-phase isotropic elastic (IE) model has been used for in situ or in vivo indentation analysis of articular cartilage. The model significantly simplifies cartilage structure and properties. In this study, we apply a fibril-reinforced poroelastic (FRPE) model for indentation to extract more detailed information on cartilage properties. Specifically, we compare the information from short-term (instantaneous) and long-term (equilibrium) indentations, as described here by IE and FRPE models. Femoral and tibial cartilage from rabbit (age 0-18 months) knees (n=14) were tested using a plane-ended indenter (diameter=0.544 mm). Stepwise creep tests were conducted to equilibrium. Single-phase IE solution for indentation was used to derive instantaneous modulus and equilibrium (Young's) modulus for the samples. The classical and modified Hayes' solutions were used to derive values for the indentation moduli. In the FRPE model, the indentation behavior was sample-specifically described with three material parameters, i.e. fibril network modulus, non-fibrillar matrix modulus and permeability. The instantaneous and fibril network modulus, and the equilibrium Young's modulus and non-fibrillar matrix modulus showed significant (p<0.01) linear correlations of R(2)=0.516 and 0.940, respectively (Hayes' solution) and R(2)=0.531 and 0.960, respectively (the modified Hayes' solution). No significant correlations were found between the non-fibrillar matrix modulus and instantaneous moduli or between the fibril network modulus and the equilibrium moduli. These results indicate that the instantaneous indentation modulus (IE model) provides information on tensile stiffness of collagen fibrils in cartilage while the equilibrium modulus (IE model) is a significant measure for stiffness of PG matrix. Thereby, this study highlights the feasibility of a simple indentation analysis.

An alternative mechanical parameter for assessing the viability of articular cartilage

This paper is a sequel to previously published findings showing that mechanical indentation alone cannot clearly discriminate between normal and degraded articular cartilage. Consequently, the structural elasticity potential ℜc = ɛr/ σi, which combines indentation stress σi with near-instantaneous rebound ɛr following unloading, is hypothesized as a potential cartilage assessment parameter, which arguably measures the integrity of the collagen fibre—proteoglycan entrapment system. To establish the validity of our hypothesis, samples of normal intact, artificially degraded, and osteoarthritic bovine cartilage were subjected to quasi-static compression at 0.1 s−1 and 0.025 s−1 to 30 per cent strain and then unloaded. A significant reduction in recovery was observed for artificially and naturally degraded samples in the first 5 s following unloading ( p<0.01). The structural elasticity potential provided a considerable improvement over the results obtained using the individual indentation and rebound parameters to distinguish between paired normal and artificially degraded samples and indicated a high statistical significance of p<0.005 when applied to the differentiation of normal and osteoarthritic samples.