Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerativeconditions, this three-dimensional finite element model is a useful tool for understanding of the stress distributions within articular cartilage in response to external loads and investigating both the prevention of injury and the pathological degeneration of the joints.In this study, 21 models were analysed by using ANSYS workbench v12.1: four normal articular cartilage models (distal femur, patella, medial and lateral tibia). A redesign to the distal femur model was done to get osteoarthritis articular cartilage (simple and deep) seven models by making partial cut without affecting the subchondral bone, and full cut with part of the subchondral bone in different diameters. Finally a treatment done by replacing the defective parts with artificial articular cartilages with different types of treatment. The finite element analysis studied depending on a Von Mises criteria and total deformation in different activities. The results shows that Autologous Chondrocyte Implementation is the best treatment way and it is close by 87.50% to normal cartilage. This procedure can be used as a diagnostic procedure for osteoarthritic patients and to choose the best treatment options.
CITATION STYLE
Abbass, S. J., & Abdulateef, F. M. R. (2023). FINITE ELEMENT ANALYSIS OF HUMAN AND ARTIFICIAL ARTICULAR CARTILAGE. Journal of Engineering, 18(04), 443–458. https://doi.org/10.31026/j.eng.2012.04.06
Mendeley helps you to discover research relevant for your work.