Loss of collagen content is localized near cartilage lesions on the day of injurious loading and intensified on day 12.

Joint injury can lead to articular cartilage damage, excessive inflammation, and post-traumatic osteoarthritis (PTOA). Collagen is an essential component for cartilage function, yet current literature has limited understanding of how biochemical and biomechanical factors contribute to collagen loss in injured cartilage. Our aim was to investigate spatially dependent changes in collagen content and collagen integrity of injured cartilage, with an explant model of early-stage PTOA. We subjected calf knee cartilage explants to combinations of injurious loading (INJ), interleukin-1α-challenge (IL) and physiological cyclic loading (CL). Using Fourier transform infrared microspectroscopy, collagen content (Amide I band) and collagen integrity (Amide II/1338 cm-1 ratio) were estimated on days 0 and 12 post-injury. We found that INJ led to lower collagen content near lesions compared to intact regions on day 0 (p < 0.001). On day 12, near-lesion collagen content was lower compared to day 0 (p < 0.05). Additionally, on day 12, INJ, IL, and INJ + IL groups exhibited lower collagen content along most of tissue depth compared to free-swelling control group (p < 0.05). CL groups showed higher collagen content along most of tissue depth compared to corresponding groups without CL (p < 0.05). Immunohistochemical analysis revealed higher MMP-1 and MMP-3 staining intensities localized within cell lacunae in INJ group compared to CTRL group on day 0. Our results suggest that INJ causes rapid loss of collagen content near lesions, which is intensified on day 12. Additionally, CL could mitigate the loss of collagen content at intact regions after 12 days.

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite-element modeling of data from the CAROT trial.

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite-element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. In this study, we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient-specific information on degeneration predictions. We used a validated FE modeling approach and three different age-dependent functions (step-wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren-Lawrence (KL) and Boston-Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve (AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient-specific models and patient-specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient-specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient-specific models and for patient-specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient-specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry.

Site-specific elastic and viscoelastic biomechanical properties of healthy and osteoarthritic human knee joint articular cartilage.

Articular cartilage exhibits site-specific biomechanical properties. However, no study has comprehensively characterized site-specific cartilage properties from the same knee joints at different stages of osteoarthritis (OA). Cylindrical osteochondral explants (n = 381) were harvested from donor-matched lateral and medial tibia, lateral and medial femur, patella, and trochlea of cadaveric knees (N = 17). Indentation test was used to measure the elastic and viscoelastic mechanical properties of the samples, and Osteoarthritis Research Society International (OARSI) grading system was used to categorize the samples into normal (OARSI 0-1), early OA (OARSI 2-3), and advanced OA (OARSI 4-5) groups. OA-related changes in cartilage mechanical properties were site-specific. In the lateral and medial tibia and trochlea sites, equilibrium, instantaneous and dynamic moduli were higher (p < 0.001) in normal tissue than in early and advanced OA tissue. In lateral and medial femur, equilibrium, instantaneous and dynamic moduli were smaller in advanced OA, but not in early OA, than in normal tissue. The phase difference (0.1-0.25 Hz) between stress and strain was significantly smaller (p < 0.05) in advanced OA than in normal tissue across all sites except medial tibia. Our results indicated that in contrast to femoral and patellar cartilage, equilibrium, instantaneous and dynamic moduli of the tibia and trochlear cartilage decreased in early OA. These may suggest that the tibia and trochlear cartilage degrades faster than the femoral and patellar cartilage. The information is relevant for developing site-specific computational models and engineered cartilage constructs.

Independent and combined effects of obesity and traumatic joint injury to the structure and composition of rat knee cartilage.

Osteoarthritis (OA) is a multifactorial joint disease characterized by articular cartilage degradation. Risk factors for OA include joint trauma, obesity, and inflammation, each of which can affect joint health independently, but their interaction and the associated consequences of such interaction were largely unexplored. Here, we studied compositional and structural alterations in knee joint cartilages of Sprague-Dawley rats exposed to two OA risk factors: joint injury and diet-induced obesity. Joint injury was imposed by surgical transection of anterior cruciate ligaments (ACLx), and obesity was induced by a high fat/high sucrose diet. Depth-dependent proteoglycan (PG) content and collagen structural network of cartilage were measured from histological sections collected previously in Collins et al.. (2015). We found that ACLx primarily affected the superficial cartilages. Compositionally, ACLx led to reduced PG content in lean animals, but increased PG content in obese rats. Structurally, ACLx caused disorganization of collagenous network in both lean and obese animals through increased collagen orientation in the superficial tissues and a change in the degree of fibrous alignment. However, the cartilage degradation attributed to joint injury and obesity was not necessarily additive when the two risk factors were present simultaneously, particularly for PG content and collagen orientation in the superficial tissues. Interestingly, sham surgeries caused a through-thickness disorganization of collagen network in lean and obese animals. We conclude that the interactions of multiple OA risk factors are complex and their combined effects cannot be understood by superposition principle. Further research is required to elucidate the interactive mechanism between OA subtypes.

Effects of gait modifications on tissue-level knee mechanics in individuals with medial tibiofemoral osteoarthritis: A proof-of-concept study towards personalized interventions.

Gait modification is a common nonsurgical approach to alter the mediolateral distribution of knee contact forces, intending to decelerate or postpone the progression of mechanically induced knee osteoarthritis (KOA). Nevertheless, the success rate of these approaches is controversial, with no studies conducted to assess alterations in tissue-level knee mechanics governing cartilage degradation response in KOA patients undertaking gait modifications. Thus, here we investigated the effect of different conventional gait conditions and modifications on tissue-level knee mechanics previously suggested as indicators of collagen network damage, cell death, and loss of proteoglycans in knee cartilage. Five participants with medial KOA were recruited and musculoskeletal finite element analyses were conducted to estimate subject-specific tissue mechanics of knee cartilages during two gait conditions (i.e., barefoot and shod) and six gait modifications (i.e., 0°, 5°, and 10° lateral wedge insoles, toe-in, toe-out, and wide stance). Based on our results, the optimal gait modification varied across the participants. Overall, toe-in, toe-out, and wide stance showed the greatest reduction in tissue mechanics within medial tibial and femoral cartilages. Gait modifications could effectually alter maximum principal stress (~20 ± 7%) and shear strain (~9 ± 4%) within the medial tibial cartilage. Nevertheless, lateral wedge insoles did not reduce joint- and tissue-level mechanics considerably. Significance: This proof-of-concept study emphasizes the importance of the personalized design of gait modifications to account for biomechanical risk factors associated with cartilage degradation.

Triple contrast computed tomography reveals site-specific biomechanical differences in the human knee joint-A proof of concept study.

Cartilage and synovial fluid are challenging to observe separately in native computed tomography (CT). We report the use of triple contrast agent (bismuth nanoparticles [BiNPs], CA4+, and gadoteridol) to image and segment cartilage in cadaveric knee joints with a clinical CT scanner. We hypothesize that BiNPs will remain in synovial fluid while the CA4+ and gadoteridol will diffuse into cartilage, allowing (1) segmentation of cartilage, and (2) evaluation of cartilage biomechanical properties based on contrast agent concentrations. To investigate these hypotheses, triple contrast agent was injected into both knee joints of a cadaver (N = 1), imaged with a clinical CT at multiple timepoints during the contrast agent diffusion. Knee joints were extracted, imaged with micro-CT (µCT), and biomechanical properties of the cartilage surface were determined by stress-relaxation mapping. Cartilage was segmented and contrast agent concentrations (CA4+ and gadoteridol) were compared with the biomechanical properties at multiple locations (n = 185). Spearman's correlation between cartilage thickness from clinical CT and reference µCT images verifies successful and reliable segmentation. CA4+ concentration is significantly higher in femoral than in tibial cartilage at 60 min and further timepoints, which corresponds to the higher Young's modulus observed in femoral cartilage. In this pilot study, we show that (1) large BiNPs do not diffuse into cartilage, facilitating straightforward segmentation of human knee joint cartilage in a clinical setting, and (2) CA4+ concentration in cartilage reflects the biomechanical differences between femoral and tibial cartilage. Thus, the triple contrast agent CT shows potential in cartilage morphology and condition estimation in clinical CT.

Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties.

Fibril-reinforced poroviscoelastic material models are considered state-of-the-art in modeling articular cartilage biomechanics. Yet, cartilage material parameters are often based on bovine tissue properties in computational knee joint models, although bovine properties are distinctly different from those of humans. Thus, we aimed to investigate how cartilage mechanical responses are affected in the knee joint model during walking when fibril-reinforced poroviscoelastic properties of cartilage are based on human data instead of bovine. We constructed a finite element knee joint model in which tibial and femoral cartilages were modeled as fibril-reinforced poroviscoelastic material using either human or bovine data. Joint loading was based on subject-specific gait data. The resulting mechanical responses of knee cartilage were compared between the knee joint models with human or bovine fibril-reinforced poroviscoelastic cartilage properties. Furthermore, we conducted a sensitivity analysis to determine which fibril-reinforced poroviscoelastic material parameters have the greatest impact on cartilage mechanical responses in the knee joint during walking. In general, bovine cartilage properties yielded greater maximum principal stresses and fluid pressures (both up to 30%) when compared to the human cartilage properties during the loading response in both femoral and tibial cartilage sites. Cartilage mechanical responses were very sensitive to the collagen fibril-related material parameter variations during walking while they were unresponsive to proteoglycan matrix or fluid flow-related material parameter variations. Taken together, human cartilage material properties should be accounted for when the goal is to compare absolute mechanical responses of knee joint cartilage as bovine material parameters lead to substantially different cartilage mechanical responses.

Visible and Near-Infrared Spectroscopy Enables Differentiation of Normal and Early Osteoarthritic Human Knee Joint Articular Cartilage.

Osteoarthritis degenerates cartilage and impairs joint function. Early intervention opportunities are missed as current diagnostic methods are insensitive to early tissue degeneration. We investigated the capability of visible light-near-infrared spectroscopy (Vis-NIRS) to differentiate normal human cartilage from early osteoarthritic one. Vis-NIRS spectra, biomechanical properties and the state of osteoarthritis (OARSI grade) were quantified from osteochondral samples harvested from different anatomical sites of human cadaver knees. Two support vector machines (SVM) classifiers were developed based on the Vis-NIRS spectra and OARSI scores. The first classifier was designed to distinguish normal (OARSI: 0-1) from general osteoarthritic cartilage (OARSI: 2-5) to check the general suitability of the approach yielding an average accuracy of 75% (AUC = 0.77). Then, the second classifier was designed to distinguish normal from early osteoarthritic cartilage (OARSI: 2-3) yielding an average accuracy of 71% (AUC = 0.73). Important wavelength regions for differentiating normal from early osteoarthritic cartilage were related to collagen organization (wavelength region: 400-600 nm), collagen content (1000-1300 nm) and proteoglycan content (1600-1850 nm). The findings suggest that Vis-NIRS allows objective differentiation of normal and early osteoarthritic tissue, e.g., during arthroscopic repair surgeries.

Multiscale In Silico Modeling of Cartilage Injuries.

Injurious loading of the joint can be accompanied by articular cartilage damage and trigger inflammation. However, it is not well-known which mechanism controls further cartilage degradation, ultimately leading to post-traumatic osteoarthritis. For personalized prognostics, there should also be a method that can predict tissue alterations following joint and cartilage injury. This chapter gives an overview of experimental and computational methods to characterize and predict cartilage degradation following joint injury. Two mechanisms for cartilage degradation are proposed. In (1) biomechanically driven cartilage degradation, it is assumed that excessive levels of strain or stress of the fibrillar or non-fibrillar matrix lead to proteoglycan loss or collagen damage and degradation. In (2) biochemically driven cartilage degradation, it is assumed that diffusion of inflammatory cytokines leads to degradation of the extracellular matrix. When implementing these two mechanisms in a computational in silico modeling workflow, supplemented by in vitro and in vivo experiments, it is shown that biomechanically driven cartilage degradation is concentrated on the damage environment, while inflammation via synovial fluid affects all free cartilage surfaces. It is also proposed how the presented in silico modeling methodology may be used in the future for personalized prognostics and treatment planning of patients with a joint injury.

Correction: A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait.

[This corrects the article DOI: 10.1371/journal.pcbi.1009398.].

Injury-related cell death and proteoglycan loss in articular cartilage: Numerical model combining necrosis, reactive oxygen species, and inflammatory cytokines.

Osteoarthritis (OA) is a common musculoskeletal disease that leads to deterioration of articular cartilage, joint pain, and decreased quality of life. When OA develops after a joint injury, it is designated as post-traumatic OA (PTOA). The etiology of PTOA remains poorly understood, but it is known that proteoglycan (PG) loss, cell dysfunction, and cell death in cartilage are among the first signs of the disease. These processes, influenced by biomechanical and inflammatory stimuli, disturb the normal cell-regulated balance between tissue synthesis and degeneration. Previous computational mechanobiological models have not explicitly incorporated the cell-mediated degradation mechanisms triggered by an injury that eventually can lead to tissue-level compositional changes. Here, we developed a 2-D mechanobiological finite element model to predict necrosis, apoptosis following excessive production of reactive oxygen species (ROS), and inflammatory cytokine (interleukin-1)-driven apoptosis in cartilage explant. The resulting PG loss over 30 days was simulated. Biomechanically triggered PG degeneration, associated with cell necrosis, excessive ROS production, and cell apoptosis, was predicted to be localized near a lesion, while interleukin-1 diffusion-driven PG degeneration was manifested more globally. Interestingly, the model also showed proteolytic activity and PG biosynthesis closer to the levels of healthy tissue when pro-inflammatory cytokines were rapidly inhibited or cleared from the culture medium, leading to partial recovery of PG content. The numerical predictions of cell death and PG loss were supported by previous experimental findings. Furthermore, the simulated ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. The mechanobiological model presented here may serve as a numerical tool for assessing early cartilage degeneration mechanisms and the efficacy of interventions to mitigate PTOA progression.

Comparison of constitutive models for meniscus and their effect on the knee joint biomechanics during gait.

Mechanical behavior of meniscus can be modeled using constitutive material models of varying complexity, such as isotropic elastic or fibril reinforced poroelastic (FRPE). However, the FRPE material is complex to implement, computationally demanding in 3D geometries, and simulation is time-consuming. Hence, we aimed to quantify the most suitable and efficient constitutive model of meniscus for simulation of cartilage responses in the knee joint during walking. We showed that simpler constitutive material models can reproduce similar cartilage responses to a knee model with the FRPE meniscus, but only knee models that consider orthotropic elastic meniscus can also reproduce meniscus responses adequately.

A novel knee joint model in FEBio with inhomogeneous fibril-reinforced biphasic cartilage simulating tissue mechanical responses during gait: data from the osteoarthritis initiative.

We developed a novel knee joint model in FEBio to simulate walking. Knee cartilage was modeled using a fibril-reinforced biphasic (FRB) formulation with depth-wise collagen architecture and split-lines to account for cartilage structure. Under axial compression, the knee model with FRB cartilage yielded contact pressures, similar to reported experimental data. Furthermore, gait analysis with FRB cartilage simulated spatial and temporal trends in cartilage fluid pressures, stresses, and strains, comparable to those of a fibril-reinforced poroviscoelastic (FRPVE) material in Abaqus. This knee joint model in FEBio could be used for further studies of knee disorders using physiologically relevant loading.

Associations of human femoral condyle cartilage structure and composition with viscoelastic and constituent-specific material properties at different stages of osteoarthritis.

The relationships between structure and function in human knee femoral cartilage are not well-known at different stages of osteoarthritis. Thus, our aim was to characterize the depth-dependent composition and structure (proteoglycan content, collagen network organization and collagen content) of normal and osteoarthritic human femoral condyle cartilage (n = 47) and relate them to their viscoelastic and constituent-specific mechanical properties that are obtained through dynamic sinusoidal testing and fibril-reinforced poroelastic material modeling of stress-relaxation testing, respectively. We characterized the proteoglycan content using digital densitometry, collagen network organization (orientation angle and anisotropy) using polarized light microscopy and collagen content using Fourier transform infrared spectroscopy. In the superficial cartilage (0-10 % of thickness), the collagen network disorganization and proteoglycan loss were associated with the smaller initial fibril network modulus - a parameter representing the pretension of the collagen network. Furthermore, the proteoglycan loss was associated with the greater strain-dependent fibril network modulus - a measure of nonlinear mechanical behavior. The proteoglycan loss was also associated with greater cartilage viscosity at a low loading frequency (0.005 Hz), while the collagen network disorganization was associated with greater cartilage viscosity at a high loading frequency (1 Hz). Our results suggest that proteoglycan loss and collagen network disorganization reduce the pretension of the collagen network while proteoglycan degradation also increases the nonlinear mechanical behavior of the collagen network. Further, the results also highlight that proteoglycan loss and collagen disorganization increase the viscosity of femoral cartilage, but their contribution to increased viscosity occurs in completely different loading frequencies.

The intrinsic quality of proteoglycans, but not collagen fibres, degrades in osteoarthritic cartilage.

The function of articular cartilage as a load-bearing connective tissue is derived primarily from a balanced interaction between the swelling proteoglycan (PG) matrix and tension-resistant collagen fibrous network. Such balance is compromised during joint disease such as osteoarthritis (OA) due to degradation to PGs and/or collagens. While the PG degradation is generally thought to be related to a loss of protein abundance, the collagenous degradation is more complex as it can be caused independently by a decrease of collagen content, disorganisation of fibrous structure and softening of individual collagen fibrils. A comprehensive understanding of the initial trajectories of degradation of PGs and collagen network can improve our chance of finding potential therapeutic solutions for OA. Here, we developed geometrically, structurally, and compositionally realistic and sample-specific Finite Element (FE) models under the framework of multiphasic mixture theory, from which the elastic moduli of collagen fibres and the PG load-bearing quality in healthy and diseased cartilages were estimated by numerical optimisation of the multi-step indentation stress relaxation force-time curves. We found the intrinsic quality of collagen fibres, measured by their elastic moduli, to stay constant for healthy and diseased cartilages. Combining with previous findings which show unaltered collagen content during early stages of OA, our results suggest the disorganisation of collagen fibrous network as the first form of collagenous degradation in osteoarthritic cartilage. We also found that PG degradation involves not only a loss of protein abundance, but also the quality of the remaining PGs in generating sufficient osmotic pressure for load bearing. This study sheds light on the mechanism of OA pathogenesis and highlights the restoration of collageneous organisation in cartilage as key medical intervention for OA. STATEMENT OF SIGNIFICANCE: Collagen network in articular cartilage consists of individual fibres that are organised into depth-dependent structure specialised for joint load-bearing and lubrication. During osteoarthritis, the collagen network undergoes mechanical degradation, but it is unclear if a loss of content, disorganisation of fibrous structure, or softening of individual fibres causes this degeneration. Using mechanical indentation, Finite Element modelling, and numerical optimisation methods, we determined that individual fibres did not soften in early disease stage. Together with previous findings showing unaltered collagen content, our results pinpoint the disorganisation of collagen structure as the main culprit for early collagenous degradation in osteoarthritic cartilage. Thus, early restoration in cartilage of collagen organisation, instead of individual fibre quality, may be key to slow osteoarthritis development.

Cyclic loading regime considered beneficial does not protect injured and interleukin-1-inflamed cartilage from post-traumatic osteoarthritis.

Injurious overloading and inflammation perturbate homeostasis of articular cartilage, leading to abnormal tissue-level loading during post-traumatic osteoarthritis. Our objective was to gain time- and cartilage depth-dependent insights into the early-stage disease progression with an in vitro model incorporating for the first time the coaction of (1) mechanical injury, (2) pro-inflammatory interleukin-1 challenge, and (3) cyclic loading mimicking walking and considered beneficial for cartilage health. Cartilage plugs (n = 406) were harvested from the patellofemoral grooves of young calves (N = 6) and subjected to injurious compression (50% strain, rate 100%/s; INJ), interleukin-1α-challenge (1 ng/ml; IL), and cyclic loading (intermittent 1 h loading periods, 15% strain, 1 Hz; CL). Plugs were assigned to six groups (control, INJ, IL, INJ-IL, IL-CL, INJ-IL-CL). Bulk and localized glycosaminoglycan (GAG) content (DMMB assay, digital densitometry), aggrecan biosynthesis (35S-sulfate incorporation), and chondrocyte viability (fluorescence microscopy) were assessed on days 3-12. The INJ, IL, and INJ-IL groups exhibited rapid early (days 2-4) GAG loss in contrast to CL groups. On day 3, deep cartilage of INJ-IL-CL group had higher GAG content than INJ group (p < 0.05). On day 12, INJ-IL-CL group showed more accumulated GAG loss (normalized with control) than INJ-IL group (average fold changes 1.97 [95% CI: 1.23-2.70]; 1.66 [1.42-1.89]; p = 0.007). Aggrecan biosynthesis increased in CL groups on day 12 compared to day 0. Despite promoting aggrecan biosynthesis, this cyclic loading protocol seems to be beneficial early-on to deep cartilage, but later becoming incapable of restricting further degradation triggered by marked but non-destructive injury and cytokine transport.

A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait.

Abnormal loading of the knee due to injuries or obesity is thought to contribute to the development of osteoarthritis (OA). Small animal models have been used for studying OA progression mechanisms. However, numerical models to study cartilage responses under dynamic loading in preclinical animal models have not been developed. Here we present a musculoskeletal finite element model of a rat knee joint to evaluate cartilage biomechanical responses during a gait cycle. The rat knee joint geometries were obtained from a 3-D MRI dataset and the boundary conditions regarding loading in the joint were extracted from a musculoskeletal model of the rat hindlimb. The fibril-reinforced poroelastic (FRPE) properties of the rat cartilage were derived from data of mechanical indentation tests. Our numerical results showed the relevance of simulating anatomical and locomotion characteristics in the rat knee joint for estimating tissue responses such as contact pressures, stresses, strains, and fluid pressures. We found that the contact pressure and maximum principal strain were virtually constant in the medial compartment whereas they showed the highest values at the beginning of the gait cycle in the lateral compartment. Furthermore, we found that the maximum principal stress increased during the stance phase of gait, with the greatest values at midstance. We anticipate that our approach serves as a first step towards investigating the effects of gait abnormalities on the adaptation and degeneration of rat knee joint tissues and could be used to evaluate biomechanically-driven mechanisms of the progression of OA as a consequence of joint injury or obesity.

Crack propagation in articular cartilage under cyclic loading using cohesive finite element modeling.

Severe joint injuries often involve cartilage defects that propagate after mechanical loading. The propagation of these lesions may contribute to the development of post-traumatic osteoarthritis (PTOA). However, the mechanisms behind their propagation remain unknown. Currently, no numerical predictive methods exist for estimating crack propagation in cartilage under cyclic loading, yet they would provide essential insights into crack growth in injured tissue after trauma. Here, we present a numerical approach to estimate crack propagation in articular cartilage under cyclic loading using a cohesive damage model. Four different material models for cartilage (hyperelastic, poro-hyperelastic, poro-hyper-viscoelastic, and fibril-reinforced poro-hyperelastic (FRPHE) with different collagen orientations) were implemented. Our numerical cohesive damage model was able to replicate the experimental crack length reported in the literature, showing greater crack length with an increasing number of loading cycles. Damage initiation stress (4.35-4.73 MPa) and fracture energy (0.97-1.55 N/mm) values obtained for the poro-hyperelastic, poro-hyper-viscoelastic, and parallel-FRPHE models were within the range of what has been reported previously. The crack growth predictions obtained by the FRPHE models showed the influence of anisotropy of the fibrillar matrix on the cartilage response. Our results indicate that our cohesive damage model could potentially be used to estimate the adverse conditions in injured soft tissue such as osteochondral lesions, menisci tears, or partial ligament ruptures under (ab)normal biomechanical scenarios.