Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity

Purpose: To develop a fully automatic algorithm for abdominal organs and adipose tissue compartments segmentation and to assess organ and adipose tissue volume changes in longitudinal water-fat magnetic resonance imaging (MRI) data. Materials and methods: Axial two-point Dixon images were acquired in 20 obese women (age range 24-65, BMI 34.9 +/- 3.8 kg/m(2)) before and after a four-week calorie restriction. Abdominal organs, subcutaneous adipose tissue (SAT) compartments (abdominal, anterior, posterior), SAT regions along the feet-head direction and regional visceral adipose tissue (VAT) were assessed by a fully automatic algorithm using morphological operations and a multi-atlas-based segmentation method. Results: The accuracy of organ segmentation represented by Dice coefficients ranged from 0.672 +/- 0.155 for the pancreas to 0.943 +/- 0.023 for the liver. Abdominal SAT changes were significantly greater in the posterior than the anterior SAT compartment (-11.4% +/- 5.1% versus -9.5% +/- 6.3%, p <0.001). The loss of VAT that was not located around any organ ( -16.1% +/- 8.9%) was significantly greater than the loss of VAT 5 cm around liver, left and right kidney, spleen, and pancreas (p < 0.05). Conclusion: The presented fully automatic algorithm showed good performance in abdominal adipose tissue and organ segmentation, and allowed the detection of SAT and VAT subcompartments changes during weight loss. (C) 2016 Elsevier Ireland Ltd. All rights reserved.