The ability to visualize and quantify tissue shape and its corresponding mechanical function is essential in a broad range of medical disciplines to characterize disease, obtain an accurate diagnosis, plan treatment, and design medical devices. Volumetric images, obtained using CT or MRI, can be reconstructed into 3D models. These models may provide a more thorough description than that afforded by measurements of 2D images alone. However, it is difficult to extract clinically relevant metrics from 3D surfaces. Equally important, objective methods to identify and compare 3D anatomy are not readily available;it remains challenging to decipher which variations are normal and which are pathological. Tools that can statistically analyze 3D shapes of biological tissues in a consistent and clinically meaningful fashion would address each of these issues. The lack of tools available to analyze shape and associate shape parameters with mechanical predictions represents a substantial gap in biomedical computing. We propose to integrate and apply SSM and FE to streamline the process of generating many FE models at once to study how anatomy and variations thereof affect tissue mechanics.
In Aim 1 we will develop tools to relate shape analysis data to clinically relevant parameters by modifying and enhancing the existing software developed under the National Alliance for Medical Image Computing (NA- MIC), ShapeWorks. We will then integrate ShapeWorks with the open-source biomechanical modeling software, FEBio, for shape-function biomechanical analyses.
In Aim 2 we will apply SSM tools from Aim 1 to quantify variation in femoral head anatomy and acetabular coverage among normal hips and hips with femoroacetabular impingement (FAI). Shape analysis data will be correlated to 2D radiographic and 3D model-based measures to determine if current clinical metrics can describe FAI deformities. The integrated platform will then be used in Aim 3 to examine the correspondence between shape and mechanics in a population of patients with acetabular dysplasia. We will test the hypothesis that shape, and shape-alone (as derived by ShapeWorks) can predict hip joint contact mechanics. Our long-term goals are to make ShapeWorks the standard for shape analyses in medicine, and to make the coupled use of ShapeWorks and FEBio a standard for investigating relationships between shape and mechanical function. The work proposed herein will establish the framework for achieving these goals.

Public Health Relevance

In this research, we will expand and integrate statistical shape analysis and biomechanics software to study the relationship between 3D anatomy and mechanical function. We will make the software publically available and use it to investigate Femoroacetabular Impingement (FAI) and Dysplasia, two diseases believed to cause hip osteoarthritis. The research will improve the diagnosis and treatment of FAI and dysplasia.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Pai, Vinay Manjunath
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University of Utah
Schools of Medicine
Salt Lake City
United States
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