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Abstract #4087

A Semi-Empirical Predictor for Visceral Fat Fraction from 3D Dual Echo Dixon Technique

Kajoli Banerjee Krishnan1, Uday Patil1, Rakesh Mullick1, Patrice Hervo2

1Imaging Technologies Lab, GE Global Research, Bangalore, Karnataka, India; 2GE Healthcare, Buc, France

We propose a semi-empirical predictor for automatically estimating abdominal visceral fat fraction (VFF) through statistical analysis of VFF computed using a threshold based on acquisition parameters applied to a representative set of MEDAL images in an anatomical region ranging from T12 to lower end of L4 vertebral body. The estimate when applied to three test cases predicts VFF within 10% of a method in which manually drawn visceral mask on water-only MEDAL image is used to demarcate the subcutaneous layer from the visceral region on the fat-only image. The predictor can be deployed in rapid assessment of obesity-related metabolic health.