Sarayu Annamalai Parimal1, Karren Hui Min Chen1, Suresh Anand Sadananthan2, Sam Sim1, Vitali Zagorodnov2, Michael WL Chee1
1Cognitive Neuroscience Laboratory, Duke-NUS Graduate Medical School, Singapore, Singapore; 2Computer Engineering, Nanyang Technological University, Singapore, Singapore
We developed a novel automated algorithm for estimation of visceral and subcutaneous adipose tissues. Using it on abdominal MR scans obtained from 119 healthy elderly volunteers showed that women have more subcutaneous abdominal fat while men have more visceral abdominal fat [6], which was consistent with previous studies. Visceral, and not subcutaneous abdominal fat, is associated with the various risk factors for cardiometabolic diseases [7]. We conclude that this automated method of abdominal adiposity quantification and analysis is a sensitive and valid tool to be utilized in future epidemiological studies of abdominal adiposity and cardiovascular and metabolic health.