Abstract

Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degradation, collagen reorientation, and PG depletion both on the surface and around the lesion. Our results confirm that the cartilage lesion depth is a crucial parameter affecting tissue degeneration, even under physiological loading conditions. The results suggest that potential fibril reorientation might prevent or slow down fibril degradation under conditions in which the tissue mechanical homeostasis is perturbed like the presence of defects or injurious loading.

Highlights

  • Osteoarthritis (OA) is a complex multi-faceted joint disease of which articular cartilage degeneration is a hallmark

  • The focus of this paper is to propose an integrated in silico cartilage degeneration model including key features of cartilage damage

  • The results show that maximum shear strain (Equation 13) with a threshold value of K0,PG = 30% can predict the fixed charge density (FCD) loss in cartilage explants with focal defect most accurately compared to experiments

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Summary

Introduction

Osteoarthritis (OA) is a complex multi-faceted joint disease of which articular cartilage degeneration is a hallmark. OA is a prevalent disease in the elderly, but younger patients can be affected by mechanically induced OA due to an injury or chronic overloading of the tissue (e.g., due to sports activities) (Mukherjee et al, 2020). OA compromises the biological and mechanical integrity of articular cartilage, whose main role is to reduce the friction between articulating bone surfaces and transmit loads to the underlying subchondral bone (Da Silva et al, 2009; Eskelinen et al, 2019). The model predictions are compared with previous experimental observations on the role of injurious mechanical loading and the presence of focal defects in cartilage degeneration

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