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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