Predicting the Heterogeneous Chemo-Mechano-Biological Degeneration of Cartilage Using 3-D Biphasic Finite Elements

作     者：Rahman, Muhammed Masudur Watton, Paul N. Neu, Corey P. Pierce, David M. 

作者机构：Department of Mechanical Engineering University of Connecticut Storrs CT United States Department of Computer Science Insigneo Institute for in silico Medicine University of Sheffield Sheffield United Kingdom Department of Mechanical Engineering and Materials Science University of Pittsburgh Pittsburgh United States Paul M. Rady Department of Mechanical Engineering University of Colorado BoulderCO United States Biomedical Engineering Program University of Colorado BoulderCO United States BioFrontiers Institute University of Colorado BoulderCO United States Department of Biomedical Engineering University of Connecticut Storrs CT United States 

出 版 物：《SSRN》 

年 卷 期：2024年

核心收录：

主　　题：Cartilage 

摘      要：We establish a novel chemo-mechano-biological (CMB) modeling framework for cartilage implemented within 3-D nonlinear, finite element analyses. The framework integrates a nonlinear biphasic constitutive model with a signaling-pathways biochemical model to capture the coupled effects of mechanical stimuli, biochemical factors, and cellular activity on cartilage degeneration and remodeling. Through finite element simulations of cyclic compression, we explored cartilage degeneration similar to early-stage osteoarthritis (OA), demonstrating that oxygen-dependent, depth-specific metabolic activity yields more realistic patterns of degeneration compared to our previous models. Specifically, our results align with experimental observations, capturing depth-dependent cartilage degradation most pronounced in the superficial zone. Incorporating these insights, our framework provides a platform to investigate mechanisms of cartilage degeneration and simulate therapeutic interventions. We previously developed automated and publicly available tools to generate patient-specific knee models from MR Images, altogether enabling personalized diagnostics/prognostics and pre-/post-operative planning. Our CMB framework is also publicly available for academic use at https://***/imLab/FEVGnR-Plugin, offering a robust basis for advancing research and clinical strategies in understanding and managing osteoarthritis. © 2024, The Authors. All rights reserved.