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Abstract #3828

Implementation of a Dual Parameter Segmentation Tool for Identification of Brown Adipose Tissue on Magnetic Resonance Imaging

David Reading1, Dana Mathews2, Yee Ng1, Binu Thomas3, Orhan Oz2, Jonathan Graff4, and Takeshi Yokoo5

1Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2Radiology, Division of Nuclear Medicine, UT Southwestern Medical Center, Dallas, TX, United States, 3Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, 4Department of Developmental Biology, UT Southwestern Medical Center, Dallas, TX, United States, 5Radiology, Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Defining regions of brown adipose tissue (BAT) on MRI remains challenging. Dissemination of existing methods is complicated by propriety algorithms, variability between institutions, and the need for time consuming manual segmentation. In this pilot imaging study, we implemented an online segmentation tool for the open-source OsiriX DICOM viewer platform (Pixmeo, Geneva) that can be used to identify regions of BAT on MRI through simultaneous fat fraction and T2* thresholding automatic segmentation. Since an OsiriX plugin is easily distributable and usable across different centers, our tool may facilitate future research studies of BAT using MRI.

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