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Abstract #0956

Assessing Sex Differences in Abdominal Fat Depots of People with Obesity under Weight Loss using Automated Segmentation

Mingming Wu1, Arum Somasundaram1, Selina Rupp1, Jessie Han1, Stella Naebauer1, Daniela Junker1, Anna Reik2, Meike Wiechert2, Hans Hauner2,3, Christina Holzapfel2, and Dimitrios C. Karampinos1
1Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, School of Medicine, Technical University of Munich, Munich, Germany, 2Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany, 3Else Kroener-Fresenius-Center of Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany

Synopsis

Keywords: Fat, Metabolism, ObesityA deep-learning algorithm based on the nnU-Net and using water-fat images enabled robust automatic segmentation of abdominal organs including visceral and subcutaneous adipose tissue, liver, iliopsoas and erector spinae muscle groups. Each organ's volume and fat content were examined in a weight loss study comprising 127 subjects with BMI of 30-39.9kg/m2, who followed a low caloric diet (LCD). Dixon water-fat images were acquired before and after diet. Differences in fat distribution among abdominal organs and fat content was assessed among both sexes. Differences in the changes of organ volume and fat fraction as a response to the LCD were revealed.

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