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Quantitative Comparison and Evaluation of Software Packages for Assessment of Abdominal Adipose Tissue Distribution by Magnetic Resonance Imaging

Overview
Specialty Endocrinology
Date 2007 Aug 19
PMID 17700582
Citations 35
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Abstract

Objective: To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results.

Design: Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue.

Subjects: A random sample of 15 obese adults with type 2 diabetes.

Measurements: Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability.

Results: Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness.

Conclusion: Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages.

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References
1.
Ryan D, Espeland M, Foster G, Haffner S, Hubbard V, Johnson K . Look AHEAD (Action for Health in Diabetes): design and methods for a clinical trial of weight loss for the prevention of cardiovascular disease in type 2 diabetes. Control Clin Trials. 2003; 24(5):610-28. DOI: 10.1016/s0197-2456(03)00064-3. View

2.
Kuk J, Lee S, Heymsfield S, Ross R . Waist circumference and abdominal adipose tissue distribution: influence of age and sex. Am J Clin Nutr. 2005; 81(6):1330-4. DOI: 10.1093/ajcn/81.6.1330. View

3.
Banerji M, Faridi N, Atluri R, Chaiken R, Lebovitz H . Body composition, visceral fat, leptin, and insulin resistance in Asian Indian men. J Clin Endocrinol Metab. 1999; 84(1):137-44. DOI: 10.1210/jcem.84.1.5371. View

4.
Elbers J, Haumann G, Asscheman H, Seidell J, Gooren L . Reproducibility of fat area measurements in young, non-obese subjects by computerized analysis of magnetic resonance images. Int J Obes Relat Metab Disord. 1998; 21(12):1121-9. DOI: 10.1038/sj.ijo.0800525. View

5.
Foster M, Hutchison J, MALLARD J, Fuller M . Nuclear magnetic resonance pulse sequence and discrimination of high- and low-fat tissues. Magn Reson Imaging. 1984; 2(3):187-92. DOI: 10.1016/0730-725x(84)90004-3. View