This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. STATISTICAL AND BIOMECHANICAL ANALYSIS OF HIP DYSPLASIA Background: Acetabular dysplasia may be the leading cause of premature osteoarthritis (OA) of the hip. However, the relationship between the altered geometry associated with dysplasia and the resulting stresses in and around the joint is poorly understood. Recognizing the mechanical consequences of different and often subtle forms of dysplasia allows earlier identification of """"""""at risk"""""""" hips, in turn allowing the initiation of earlier treatment. This research delineates the true spectrum of this three-dimensional pathology by quantifying stress transfer in the hip joint and predicting the long-term success rate of corrective surgeries. Rationale: Much of orthopaedics is governed by mechanics and much of mechanics is dictated by shape. Thus, we believe that the potential impact of robust, open-source software tools for meshing and statistical shape analysis is profound. The ability to study statistical shape models in a biomechanical context has several important implications, including the ability to drive the biomechanical simulations of patient groups using group-averaged geometries, the ability to make group comparisons of both geometry and biomechanical parameters in a way that systematically captures group variability, and finally, the ability to study sensitivities in biomechanical outcomes with respect to geometric variability. Questions: This project presents some important challenges for algorithm and software development in the CIBC: (1) Achieving a sufficient level of robustness to compete with the commercial pipeline;(2) Validating the quality of the elements in the biomechanics applications;(3) Extending the tools in a general way to deal with open geometries;(4) Addressing some of the issues of building joint models (multiple surfaces) with tight tolerances (bones separated by cartilage);and (5) Achieving a proper anatomical alignment of the bones. Design &Methods: This DBP relies on two collaborative methods: (1) Patient-specific finite element (FE) models: For this aim, we will work with the Bioengineering and Orthopedics group at the University of Utah to deploy Seg3D and BioMesh software and facilitate its use;and (2) Statistical shape models of the hip joint: For this aim, we will apply and extend the software tools available in ShapeWorks. The strategy will be to examine the efficacy of the current technology and extend it, as necessary, to be able to address the needs of the DBP.
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