Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking

Finite element (FE) modeling is becoming an increasingly popular method for analyzing knee joint mechanics and biomechanical mechanisms leading to osteoarthritis (OA). The most common and widely available imaging method for knee OA diagnostics is planar X-ray imaging, while more sophisticated imaging methods, e.g., magnetic resonance imaging (MRI) and computed tomography (CT), are seldom used. Hence, the capability to produce accurate biomechanical knee joint models directly from X-ray imaging would bring FE modeling closer to clinical use. Here, we extend our atlas-based framework by generating FE knee models from X-ray images (N = 28). Based on measured anatomical landmarks from X-ray and MRI, knee joint templates were selected from the atlas library. The cartilage stresses and strains of the X-ray-based model were then compared with the MRI-based model during the stance phase of the gait. The biomechanical responses were statistically not different between MRI- vs. X-ray-based models when the template obtained from X-ray imaging was the same as the MRI template. However, if this was not the case, the peak values of biomechanical responses were statistically different between X-ray and MRI models. The developed X-ray-based framework may pave the way for a clinically feasible approach for knee joint FE modeling.

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation

Knee osteoarthritis (OA) is a painful joint disease, causing disabilities in daily activities. However, there is no known cure for OA, and the best treatment strategy might be prevention. Finite element (FE) modeling has demonstrated potential for evaluating personalized risks for the progression of OA. Current FE modeling approaches use primarily magnetic resonance imaging (MRI) to construct personalized knee joint models. However, MRI is expensive and has lower resolution than computed tomography (CT). In this study, we extend a previously presented atlas-based FE modeling framework for automatic model generation and simulation of knee joint tissue responses using contrast agent-free CT. In this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and scaled to generate a personalized FE model. We compared the simulated tissue responses of the CT-based models with those of the MRI-based models. We show that the CT-based models are capable of producing similar tensile stresses, fibril strains, and fluid pressures of knee joint cartilage compared to those of the MRI-based models. This study provides a new methodology for the analysis of knee joint and cartilage mechanics based on measurement of bone dimensions from native CT scans.

Mechanobiological model for simulation of injured cartilage degradation via pro-inflammatory cytokines and mechanical stimulus

Post-traumatic osteoarthritis (PTOA) is associated with cartilage degradation, ultimately leading to disability and decrease of quality of life. Two key mechanisms have been suggested to occur in PTOA: tissue inflammation and abnormal biomechanical loading. Both mechanisms have been suggested to result in loss of cartilage proteoglycans, the source of tissue fixed charge density (FCD). In order to predict the simultaneous effect of these degrading mechanisms on FCD content, a computational model has been developed. We simulated spatial and temporal changes of FCD content in injured cartilage using a novel finite element model that incorporates (1) diffusion of the pro-inflammatory cytokine interleukin-1 into tissue, and (2) the effect of excessive levels of shear strain near chondral defects during physiologically relevant loading. Cytokine-induced biochemical cartilage explant degradation occurs near the sides, top, and lesion, consistent with the literature. In turn, biomechanically-driven FCD loss is predicted near the lesion, in accordance with experimental findings: regions near lesions showed significantly more FCD depletion compared to regions away from lesions (p<0.01). Combined biochemical and biomechanical degradation is found near the free surfaces and especially near the lesion, and the corresponding bulk FCD loss agrees with experiments. We suggest that the presence of lesions plays a role in cytokine diffusion-driven degradation, and also predisposes cartilage for further biomechanical degradation. Models considering both these cartilage degradation pathways concomitantly are promising in silico tools for predicting disease progression, recognizing lesions at high risk, simulating treatments, and ultimately optimizing treatments to postpone the development of PTOA.

Clinical Contrast-Enhanced Computed Tomography With Semi-Automatic Segmentation Provides Feasible Input for Computational Models of the Knee Joint

Computational models can provide information on joint function and risk of tissue failure related to progression of osteoarthritis (OA). Currently, the joint geometries utilized in modeling are primarily obtained via manual segmentation, which is time-consuming and hence impractical for direct clinical application. The aim of this study was to evaluate the applicability of a previously developed semi-automatic method for segmenting tibial and femoral cartilage to serve as input geometry for finite element (FE) models. Knee joints from seven volunteers were first imaged using a clinical computed tomography (CT) with contrast enhancement and then segmented with semi-automatic and manual methods. In both segmentations, knee joint models with fibril-reinforced poroviscoelastic (FRPVE) properties were generated and the mechanical responses of articular cartilage were computed during physiologically relevant loading. The mean differences in the absolute values of maximum principal stress, maximum principal strain, and fibril strain between the models generated from semi-automatic and manual segmentations were <1 MPa, <0.72% and <0.40%, respectively. Furthermore, contact areas, contact forces, average pore pressures, and average maximum principal strains were not statistically different between the models (p >0.05). This semi-automatic method speeded up the segmentation process by over 90% and there were only negligible differences in the results provided by the models utilizing either manual or semi-automatic segmentations. Thus, the presented CT imaging-based segmentation method represents a novel tool for application in FE modeling in the clinic when a physician needs to evaluate knee joint function.

Maximum shear strain-based algorithm can predict proteoglycan loss in damaged articular cartilage

Post-traumatic osteoarthritis (PTOA) is a common disease, where the mechanical integrity of articular cartilage is compromised. PTOA can be a result of chondral defects formed due to injurious loading. One of the first changes around defects is proteoglycan depletion. Since there are no methods to restore injured cartilage fully back to its healthy state, preventing the onset and progression of the disease is advisable. However, this is problematic if the disease progression cannot be predicted. Thus, we developed an algorithm to predict proteoglycan loss of injured cartilage by decreasing the fixed charge density (FCD) concentration. We tested several mechanisms based on the local strains or stresses in the tissue for the FCD loss. By choosing the degeneration threshold suggested for inducing chondrocyte apoptosis and cartilage matrix damage, the algorithm driven by the maximum shear strain showed the most substantial FCD losses around the lesion. This is consistent with experimental findings in the literature. We also observed that by using coordinate system-independent strain measures and selecting the degeneration threshold in an ad hoc manner, all the resulting FCD distributions would appear qualitatively similar, i.e., the greatest FCD losses are found at the tissue adjacent to the lesion. The proposed strain-based FCD degeneration algorithm shows a great potential for predicting the progression of PTOA via biomechanical stimuli. This could allow identification of high-risk defects with an increased risk of PTOA progression.

A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage

Cartilage provides low-friction properties and plays an essential role in diarthrodial joints. A hydrated ground substance composed mainly of proteoglycans (PGs) and a fibrillar collagen network are the main constituents of cartilage. Unfortunately, traumatic joint loading can destroy this complex structure and produce lesions in tissue, leading later to changes in tissue composition and, ultimately, to post-traumatic osteoarthritis (PTOA). Consequently, the fixed charge density (FCD) of PGs may decrease near the lesion. However, the underlying mechanisms leading to these tissue changes are unknown. Here, knee cartilage disks from bovine calves were injuriously compressed, followed by a physiologically relevant dynamic compression for twelve days. FCD content at different follow-up time points was assessed using digital densitometry. A novel cartilage degeneration model was developed by implementing deviatoric and maximum shear strain, as well as fluid velocity controlled algorithms to simulate the FCD loss as a function of time. Predicted loss of FCD was quite uniform around the cartilage lesions when the degeneration algorithm was driven by the fluid velocity, while the deviatoric and shear strain driven mechanisms exhibited slightly discontinuous FCD loss around cracks. Our degeneration algorithm predictions fitted well with the FCD content measured from the experiments. The developed model could subsequently be applied for prediction of FCD depletion around different cartilage lesions and for suggesting optimal rehabilitation protocols.

Low-energy impact of human cartilage: predictors for microcracking the network of collagen

OBJECTIVE

We aimed to determine the minimum mechanical impact to cause microstructural damage in the network of collagen (microcracking) within human cartilage and hypothesized that energies below 0.1 J or 1 mJ/mm³ would suffice.

DESIGN

We completed 108 low-energy impact tests (0.05, 0.07, or 0.09 J; 0.75 or 1.0 m/s²) using healthy cartilage specimens from six male donors (30.2 ± 8.8 yrs old). Before and after impact we acquired, imaging the second harmonic generation (SHG), ten images from each specimen (50 μm depth, 5 μm step size), resulting in 2160 images. We quantified both the presence and morphology of microcracks. We then correlated test parameters (predictors) impact energy/energy dissipation density, nominal stress/stress rate, and strain/strain rate to microcracking and tested for significance. Where predictors significantly correlated with microstructural outcomes we fitted binary logistic regression plots with 95% confidence intervals (CIs).

RESULTS

No specimens presented visible damage following impact. We found that impact energy/energy dissipation density and nominal stress/stress rate were significant (P < 0.05) predictors of microcracking while both strain and strain rate were not. In our test configuration, an impact energy density of 2.93 mJ/mm³, an energy dissipation density of 1.68 mJ/mm³, a nominal stress of 4.18 MPa, and a nominal stress rate of 689 MPa/s all corresponded to a 50% probability of microcracking in the network of collagen.

CONCLUSIONS

An impact energy density of 1.0 mJ/mm³ corresponded to a ∼20% probability of microcracking. Such changes may initiate a degenerative cascade leading to post-traumatic osteoarthritis.

The mechanics of focal chondral defects in the hip

There is a mean incidence of osteoarthritis (OA) of the hip in 8% of the overall population. In the presence of focal chondral defects, defined as localized damage to the articular cartilage, there is an increased risk of symptomatic progression toward OA. This relationship between chondral defects and subsequent development of OA has led to substantial efforts to develop effective procedures for surgical cartilage repair. This study examined the effects of chondral defects and labral delamination on cartilage mechanics in the dysplastic hip during the gait cycle using subject-specific finite element analysis. Models were generated from volumetric CT data and analyzed with simulated chondral defects at the chondrolabral junction on the posterior acetabulum during five distinct points in the gait cycle. Focal chondral defects increased maximum shear stress on the osteochondral surface of the acetabular cartilage, when compared to the intact case. This effect was amplified with labral delamination. Additionally, chondral defects increased the first principal Lagrange strain on the articular surface of the acetabular cartilage and labrum. Labral delamination relieved some of this tensile strain. As defect size was increased, contact stress increased in the medial zone of the acetabulum, while it decreased anteriorly. The results suggest that in the presence of chondral defects and labral delamination the cartilage experiences elevated tensile strains and shear and contact stress, which could lead to further damage of the cartilage, and subsequent arthritic progression. The framework presented here will serve as the procedure for future finite element studies on cartilage mechanics in hips with varying disease states with simulated chondral defects and labral tears.

Cyclic loading of human articular cartilage: The transition from compaction to fatigue

Osteoarthritis and articular cartilage injuries are common conditions in human joints and a frequent cause of pain and disability. Unfortunately, cartilage is avascular and has limited capabilities for self-repair. Despite the societal impact, there is little information on the dynamic process of cartilage degeneration. We performed a series of cyclic unconfined compression tests motivated by in vivo loading conditions and designed to generate mechanical fatigue. We examined the functional (both stress-stretch and creep) responses of the tissue after recovery from a specified number of loading cycles, as well as histology and second harmonic generation microscopy images. The effect of compaction was complimented by the effect of fatigue in our unconfined compression tests. A three-way, repeated-measures mixed model ANOVA showed significant differences between loading with a physiologically relevant low magnitude, and two more severe loading magnitudes, in terms of the resulting specimen stiffness, time to equilibrium and thickness. There was a statistically significant effect of loading frequency on a specimen's time to equilibrium and significant interaction of force and frequency on specimen thickness and time to equilibrium. Increasing the number of loading cycles significantly impacted a specimen's effective stiffness and resulting thickness. We attribute permanent loss of mechanical function under cyclic loading to rearrangement and disruption of the collagen network and resulting proteoglycan (PG) aggregation, as seen in histological and second harmonic generation images, as a result of induced mechanical fatigue.

An evolutionary model of osteoarthritis including articular cartilage damage, and bone remodeling in a computational study

With osteoarthritis, a complex set of progressive chemical, biological, and mechanical changes occur in both cartilage and bone. The aim of this study is to develop a high-fidelity computational model of the complete bone-cartilage unit to study the evolution of osterarthritis-induced articular cartilage (AC) damage and remodeling of subchondral cortical bone (SCB) and subchondral trabecular bone (STB). A finite element model of spherical indentation was developed with a depth-dependent anisotropic model of degenerating articular cartilage, a calcified cartilage (CC) zone, and SCB and STB remodeling regions. Calcified tissue (CC, SCB, and STB) and AC material regions were integrated to form an evolutionary bone-cartilage unit model. Results indicate that with indentation loading, articular cartilage damage occurs at the articular surface. Furthermore, bone remodeling was predicted to occur with a net stiffening of the subchondral bone plate. Changes in indentation force were minimal (<2%) between initial and final peak indentation loading. However, additional degradation and wear of AC and/or alterations in loading may have more pronounced effects on the mechanical response of the bone-cartilage unit. Bone remodeling and articular cartilage damage predictions are consistent with experimental observations that cartilage damage begins at the articular surface and subchondral bone experiences a thickening (i.e., stiffening) response with osteoarthritis. Our results provide insight into the early-term initiation behavior of osteoarthritis; the potential consequences of evolutions in AC, SCB, and STB with disease progression; and may guide future experimental and computational studies to elucidate mechanisms of osteoarthritis progression.