4.7 Article

Accurate quantification of visceral adipose tissue (VAT) using water-saturation MRI and computer segmentation: Preliminary results

Journal

JOURNAL OF MAGNETIC RESONANCE IMAGING
Volume 23, Issue 5, Pages 736-741

Publisher

WILEY
DOI: 10.1002/jmri.20551

Keywords

MR; fat; fat quantification; MR; sequences

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Purpose: To describe and evaluate the accuracy of water-saturation MRI and a computer segmentation program for quantification of visceral adipose tissue (VAT). Materials and Methods: MRI was performed on five patients with whole-volume coverage of the abdomen using two different sequences: 1) a T1 -weighted spoiled gradient-echo breath-hold sequence (non-water-saturation) and 2) a T1-weighted spoiled gradient-echo water- saturation breath-hold sequence (water-saturation). The computer segmentation program analyzed the data and calculated VAT volumes (cm(3)) from both sequences. The data from one patient were additionally processed with the use of a manual technique. The intrastudy reproducibility of the proposed method using the wa ter-satu ration MRI sequence and the computer segmentation technique was tested by repeated measures of the automated system analysis (x 10) on MRI data from a single subject to calculate variability. Results: VAT volumes measured by the water-saturation MRI sequences were consistently greater than those measured by the non-water-saturation sequences. Comparison of VAT volumes derived from the water-saturation images and measured by the computer segmentation technique vs. the manual technique showed good correlation (K = 0.8), with a significant time-saving benefit associated with the automated method (5 minutes vs. 1 hour). There was poor correlation between VAT volume measurement calculated by the manual technique and the computer segmentation technique using non-water-saturation images. The reproducibility of the computer segmentation technique using data derived from watersaturation images was high, with a low variability (+/- 5%). Conclusion: The results obtained demonstrate that the proposed method may be able to provide accurate quantification of VAT in a highly reproducible and efficient manner.

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