Osteoarthritis is a harmful joint disease but prediction of disease progression is problematic. Currently, there is only one modeling framework which can be applied to predict the progression of knee osteoarthritis but it only considers degenerative changes in the collagen fibril network. Here, we have developed the framework further by considering all of the major tissue changes (proteoglycan content, fluid flow, and collagen fibril network) occurring in osteoarthritis. While excessive levels of tissue stresses controlled degeneration of the collagen fibril network, excessive levels of tissue strains controlled the decrease in proteoglycan content and the increase in permeability. We created four knee joint models with increasing degrees of complexity based on the depth-wise composition. Models were tested for normal and abnormal, physiologically relevant, loading conditions in the knee. Finally, the predicted depth-wise compositional changes from each model were compared against experimentally observed compositional changes in vitro. The model incorporating the typical depth-wise composition of cartilage produced the best match with experimental observations. Consistent with earlier in vitro experiments, this model simulated the greatest proteoglycan depletion in the superficial and middle zones, while the collagen fibril degeneration was located mostly in the superficial zone. The presented algorithm can be used for predicting simultaneous collagen degeneration and proteoglycan loss during the development of knee osteoarthritis.
Subject classification (UKÄ)
- Medical Laboratory and Measurements Technologies
- articular cartilage
- finite element analysis
- knee joint