Abstract

Knee osteoarthritis (OA), ranked among the leading causes of disability across the globe, reduces the quality of life by causing chronic pain, inflammation, and joint stiffness. OA is a progressive joint disease characterized by altered synthesis and degradation of articular cartilage and underlying bone, attributed to joint mechanics and inflammatory substances as modifiable risk factors. While mechanical loading can benefit overall cartilage health, abnormal mechanical loading can cause tissue damage, for instance, collagen network damage, cell damage/death, and loss of proteoglycans within the cartilage. Chemical factors such as the diffusion of inflammatory cytokines into the cartilage can also alter cartilage synthesis, leading to degradation. Hence, a thorough knowledge of the mechanobiological response of the knee articular cartilage is essential to investigate the onset and progression of knee OA, and potentially enhance knee OA treatments. 

My research focuses on developing physics-based multiscale models, including finite element analysis, to noninvasively assess the mechanobiological environment of the knee and predict cartilage degradation. At the body and joint level, subject-specific neuromusculoskeletal models are used to estimate knee joint kinematics and kinetics during various functional activities. At lower spatial scales, such as tissue and cell levels, I use Abaqus software for multi-physics finite element analysis (driven by inputs from musculoskeletal models) to investigate the mechanobiological responses of cartilage components like fluid, collagens, and proteoglycans. In my talk, I will demonstrate how finite element modeling, implemented in Abaqus, could assist in personalized medicine (such as rehabilitation) to prevent or postpone the progression of knee OA.

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Presenter Bio

Amir Esrafilian, Postdoc Fellow, Stanford University

Amir Esrafilian, PhD, is a biomechanics researcher and is currently pursuing his postdoc fellowship at Stanford University. His work focuses on osteoarthritis disease, developing personalized digital twins to enable tailored treatments, such as rehabilitation and assistive devices, to prevent or decelerate disease progression. He specializes in neuromusculoskeletal modeling (multibody dynamics) and finite element analysis, with expertise in implementing biological material models via UMAT in Abaqus.