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J Magn Reson Imaging. 2009 Jul;30(1):185-93. doi: 10.1002/jmri.21820.

Automated assessment of whole-body adipose tissue depots from continuously moving bed MRI: a feasibility study.

Author information

1
Department of Radiology, Uppsala University, Uppsala, Sweden. joel.kullberg@radiol.uu.se

Abstract

PURPOSE:

To present an automated algorithm for segmentation of visceral, subcutaneous, and total volumes of adipose tissue depots (VAT, SAT, TAT) from whole-body MRI data sets and to investigate the VAT segmentation accuracy and the reproducibility of all depot assessments.

MATERIALS AND METHODS:

Repeated measurements were performed on 24 volunteer subjects using a 1.5 Tesla clinical MRI scanner and a three-dimensional (3D) multi-gradient-echo sequence (resolution: 2.1 x 2.1 x 8 mm(3), acquisition time: 5 min 15 s). Fat and water images were reconstructed, and fully automated segmentation was performed. Manual segmentation of the VAT reference was performed by an experienced operator.

RESULTS:

Strong correlation (R = 0.999) was found between the automated and manual VAT assessments. The automated results underestimated VAT with 4.7 +/- 4.4%. The accuracy was 88 +/- 4.5% and 7.6 +/- 5.7% for true positive and false positive fractions, respectively. Coefficients of variation from the repeated measurements were: 2.32 % +/- 2.61%, 2.25% +/- 2.10%, and 1.01% +/- 0.74% for VAT, SAT, and TAT, respectively.

CONCLUSION:

Automated and manual VAT results correlated strongly. The assessments of all depots were highly reproducible. The acquisition and postprocessing techniques presented are likely useful in obesity related studies.

PMID:
19557740
DOI:
10.1002/jmri.21820
[Indexed for MEDLINE]

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