In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis

体外生物力学研究重度膝骨关节炎患者半月板的特性

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Abstract

INTRODUCTION: The meniscus is a crucial component of the human knee joint, contributing to load transmission, stability, and lubrication. Meniscal injury can disrupt knee biomechanics and eventually lead to knee osteoarthritis (KOA). Quantifying the biomechanical properties of the meniscus is essential for understanding its role in knee joint function and pathology. METHODS: This study aimed to determine the biomechanical properties of the meniscus in patients with severe KOA using experimental mechanical testing and an inverse finite element analysis (iFEA) model. Meniscal samples were collected and graded from patients undergoing total knee arthroplasty. Tensile (n = 113) and compressive (n = 137) tests were performed to obtain experimental data. An iFEA model with a Mooney-Rivlin hyperelastic formulation was developed to estimate the constitutive parameters of the meniscus through optimization algorithms. RESULTS: In patients with severe KOA, the average tensile modulus of the lateral meniscus (57.9 ± 34.1 MPa) was approximately 40.5% higher than that of the medial meniscus (41.2 ± 28.8 MPa). At 10% strain, the average compressive modulus was 2.2 ± 1.5 MPa for the medial and 2.5 ± 1.5 MPa for the lateral meniscus. Compared with the 10% strain level, the compressive modulus of the medial and lateral menisci increased by 54.5% and 136% at 20% strain, and by 222.7% and 288% at 30% strain, respectively. Both tensile and compressive moduli exhibited a stepwise decrease with increasing degeneration. The iFEA model showed an excellent fit to the experimental data (R(2) > 0.9). DISCUSSION: The biomechanical properties of the meniscus in severe KOA patients differ substantially from those reported in healthy tissues, highlighting the need for caution when using literature-derived parameters in computational modeling. The iFEA framework provides a robust approach for predicting constitutive parameters across different degeneration levels and meniscal regions, offering valuable insights for personalized knee joint modeling and simulation.

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