Abstract:
Cartilage fissures, surface fibrillation, and delamination are recognized as early indicators of hip osteoarthritis (OA), suggesting that these forms of damage may be initiated or exacerbated by unfavorable mechanical environments within the cartilage, specifically elevated first principal (most tensile) strain and maximum shear stress. To better understand these biomechanical drivers, this study utilized a population of validated finite element (FE) models of normal human hips. The primary objectives were to meticulously evaluate the mesh requirements necessary for achieving converged predictions of cartilage tensile strain and shear stress, to assess the sensitivity of these predictions to various cartilage constitutive assumptions, and to determine the characteristic patterns of transchondral stress and strain that manifest during activities of daily living.
Five specimen-specific FE models were rigorously evaluated using three distinct constitutive models for articular cartilage: a quasi-linear neo-Hookean model, a nonlinear Veronda-Westmann model, and a tension-compression nonlinear ellipsoidal fiber distribution (EFD) model. These models represent different complexities in capturing the mechanical behavior of cartilage. Transchondral predictions of maximum shear stress and first principal strain were systematically determined across the cartilage layer. The investigation revealed that mesh convergence for these critical biomechanical parameters required a significant refinement, specifically six elements through the cartilage thickness. Furthermore, the choice of cartilage constitutive model had a profound impact on the magnitude and distribution of predicted stresses and strains, underscoring the importance of accurate material characterization in biomechanical simulations. The results identified distinct patterns of high tensile strain and shear stress that recur across different activities, providing crucial insights into potential sites of cartilage degeneration. This biomechanical modeling approach is a powerful tool for advancing our understanding of early OA progression and can ultimately contribute to strategies for prevention and treatment by identifying critical mechanical thresholds.
