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/m2) 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.
