Nieminen, P. | Search bioRxiv

bioRxiv2023

An Automated and Robust Tool for Musculoskeletal and Finite Element Modeling of the Knee Joint

ObjectiveTo develop and assess an automatic and robust knee musculoskeletal finite element (MSK-FE) modeling pipeline. MethodsMagnetic resonance images (MRI) were used to train nnU-Net networks for auto-segmentation of knee bones (femur, tibia, patella, and fibula), cartilages (femur, tibia, and patella), menisci, and major knee ligaments. Two different MRI sequences were used to broaden applicability. Next, we created MSK-FE models of an unseen dataset using two MSK-FE modeling pipelines: template-based and auto-meshing. MSK models had personalized knee geometries with multi-degree-of-freedom elastic foundation contacts. FE models used fibril-reinforced poroviscoelastic swelling material models for cartilages and menisci. ResultsVolumes of knee bones, cartilages, and menisci did not significantly differ (p>0.05) across MRI sequences. MSK models estimated secondary knee kinematics during passive knee flexion tests consistent with in vivo and simulation-based values from the literature. Between the template-based and auto-meshing FE models, estimated cartilage mechanics often differed significantly (p<0.05), though differences were <15% (considering peaks during walking), i.e., <1.5 MPa for maximum principal stress, <1 percentage point for collagen fibril strain, and <3 percentage points for maximum shear strain. ConclusionThe template-based modeling provided a more rapid and robust tool than the auto-meshing approach, while the estimated knee biomechanics were comparable. Nonetheless, the auto-meshing approach might provide more accurate estimates in subjects with distinct knee irregularities, e.g., cartilage lesions. SignificanceThe MSK-FE modeling tool provides a rapid, easy-to-use, and robust approach to investigating task- and person-specific mechanical responses of the knee cartilage and menisci, holding significant promise, e.g., in personalized rehabilitation planning.

bioengineering↗

bioRxiv2022

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. The numerical predictions were supported by several previous experimental findings. Furthermore, the ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. 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 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. Author summaryOsteoarthritis is one of the most common musculoskeletal diseases. When osteoarthritis develops after a joint injury, it is designated as post-traumatic osteoarthritis. A defining feature of osteoarthritis is degeneration of articular cartilage, which is partly driven by cartilage cells after joint injury, and further accelerated by inflammation. The degeneration triggered by these biomechanical and biochemical mechanisms is currently irreversible. Thus, early prevention/mitigation of disease progression is a key to avoiding PTOA. Prior computational models have been developed to provide insights into the complex mechanisms of cartilage degradation, but they rarely include cell-level cartilage degeneration mechanisms. Here, we present a novel approach to simulate how the early post-traumatic biomechanical and inflammatory effects on cartilage cells eventually influence tissue composition. Our model includes the key regulators of early post-traumatic osteoarthritis: chondral lesions, cell death, reactive oxygen species, and inflammatory cytokines. The model is supported by several experimental explant culture findings. Interestingly, we found that when post-injury inflammation is mitigated, cartilage composition can partially recover. We suggest that mechanobiological models including cell-tissue-level mechanisms can serve as future tools for evaluating high-risk lesions and developing new intervention strategies.

biophysics↗

bioRxiv2021

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

Post-traumatic osteoarthritis is a degenerative musculoskeletal condition where homeostasis of articular cartilage is perturbated by lesions and inflammation, leading to abnormal tissue-level loading. These mechanisms have rarely been included simultaneously in in vitro osteoarthritis models. We modeled the early disease progression in bovine cartilage regulated by the coaction of (1) mechanical injury, (2) pro-inflammatory interleukin-1 challenge, and (3) cyclic loading mimicking walking and considered beneficial (15% strain, 1 Hz). Surprisingly, cyclic loading did not protect cartilage from accelerated glycosaminoglycan loss over 12 days of interleukin-1-culture despite promoting aggrecan biosynthesis. Our time-dependent data suggest that this loading regime could be beneficial in the first days following injury but later turn detrimental in interleukin-1-inflamed cartilage. Consequently, early anti-catabolic drug intervention may inhibit, whereas cyclic loading during chronic inflammation may promote osteoarthritis progression. Our data on the early stages of post-traumatic osteoarthritis could be utilized in the development of countermeasures for disease progression.

pathology↗