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The Search For Advanced Imaging Descriptors Of Human Body Shape And Their Association To Diabetes And Other Metabolic Disorders

Abstract

Diabetes and metabolic syndrome are global health problems associated with reduced life span, increased morbidity, and significant financial burdens on individuals and healthcare systems. Each of these disorders has unique body composition and body shape characteristics as it progresses forward. While the biology behind these disorders has made tremendous progress in the last fifty years, the most commonly used methods for estimating the associated body shape and composition have not followed the same trajectory.

Besides body mass index and waist circumference, researchers and clinicians have few simple techniques to assess body fat distribution and determine the status for these disorders. While researchers and clinicians recognize the complexity of internal body composition, they still rely on many basic assumptions that oversimplify an individual's body composition. Over the last several years, I have worked on a developing, validating, and applying a set of methods researchers and clinicians can use to quantify body shape and composition accurately and precisely.

The research presented in this dissertation is driven by the hypothesis that specific body shape and composition characteristics can distinguish healthy individuals from those with abnormal metabolic profiles. This dissertation details the unmet need of simple descriptors that capture the complex nature of body shape and composition, presents the theory and development of new imaging techniques that can be used to quantify body shape and composition, and showcases how these new body shape metrics have been used to identify those most likely to have abnormal metabolic profiles.

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