An automated pipeline for analysing contact stresses in the carpometacarpal joint

Abstract

INTRODUCTION Carpometacarpal (CMC) joint osteoarthritis (OA) is a serious and pervasive disease, affecting 15% of adults over 30 years and two to six times more women than men[1]. Sexual dimorphism, kinematics and their effects on joint biomechanics and resulting cartilage stresses are implicated with the pathogenesis of CMC OA [2]. Here we present an automated pipeline for creating finite element (FE) models of the CMC joint. METHODS A training set of 50 CMC joints were manually segmented from clinical CT scans of the hand with a resolution of 0.4x0.4x0.625 (age range: 18 yrs to 67 yrs; 24 females and 26 males). A custom piecewise parametric template mesh, designed with an articular surface division, was fitted to each segmented data cloud, resulting in a set of correspondent meshes of the metacarpal and trapezium bones. These were used to train a statistical shape model (SSM). 3D Haar-like features were sampled from the image about each mesh node and used to train a random forest regressor for each node (Figure 1 A). During segmentation, a mean mesh was fitted to nodal locations predicted by the regressors (Figure 1 B) using optimal deformations permitted by the SSM (Figure 1 C). The articular surface division of the mesh was used to automatically build a uniform 3D hexahedral mesh of CMC joint cartilage. This cartilage mesh and the bone were finally imported into FEBio for FE analysis (Figure 1 D). FE analysis was performed using displacement driven static analysis. As a proof of concept, we simulated the stress through the cartilage in neutral position from clinical CT. RESULTS AND DISCUSSION It can be seen that the peak effective stress during static neutral position is 264kPa, with the median stress at 140kPa (Figure 2). Figure 2: Effective stress in the CMC joint cartilage in neutral position. CONCLUSIONS Our preliminary results are promising, indicating that this pipeline may be useful for the determination of stresses during different functional tasks. ACKNOWLEDGEMENTS This work was supported by the Nation Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health and the Auckland Bioengineering Institute. REFERENCES 1. Haara M.M., et al., J. Bone Jt. Surg. 86:1452-1457, 2004. 2. Halilaj E., et al., ISB Clinical Orthopaedics and Related Research, 472(4):1114-1122, 2014