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

A 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.