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Subchondral Cysts Create Increased Intra-osseous Stress In Early Knee OA: A Finite Element Analysis Using Simulated Lesions.

D. McErlain, J. Milner, Todor G. Ivanov, Lubica Jencikova-Celerin, S. Pollmann, D. Holdsworth
Published 2011 · Medicine, Biology

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AIM OF STUDY To investigate the role of intra-osseous lesions in advancing the pathogenesis of Osteoarthritis (OA) of the knee, using Finite Element Modeling (FEM) in conjunction with high-resolution imaging techniques. METHODS Twenty early stage OA patients (≤ Grade 2 radiographic score) were scanned with a prototype, cone-beam CT system. Scans encompassed the mid-shaft of the femur to the diaphysis of the proximal tibia. Individual bones were segmented to create 3D geometric models that were transferred to FE software for loading experiments. Patient-specific, inhomogeneous material properties were derived from the CT images and mapped directly to the FE models. Duplicate models were also created, with a 3D sphere (range 3-12 mm) introduced into a weight-bearing region of the joint, mimicking the size, location, and composition of a subchondral bone cyst (SBC). A spherical shell extending 1mm radially around the SBC served as the sample volume for measurements of von Mises equivalent stress. Both models were vertically loaded with 750 N, or approximately 1 body weight during a single-leg stance. RESULTS All FE models exhibited a physiologically realistic weight-bearing distribution of stress, which initiated at the joint surface and extended to the cortical bone. Models that contained the SBC experienced a nearly two-fold increase in stress (0.934 ± 0.073 and 1.69 ± 0.159 MPa, for the non-SBC and SBC models, respectively) within the bone adjacent to the SBC. In addition, there was a positive correlation found between the diameter of the SBC and the resultant intra-osseous stress under load (p = 0.004). CONCLUSIONS Our results provide insights into the mechanism by which SBC may accelerate OA, leading to greater pain and disability. Based on these findings, we feel that patient-derived FE models of the OA knee - utilizing in vivo imaging data - present a tremendous potential for monitoring joint mechanics under physiological loads.
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