Work

Comparison of Methods for Assessing Abdominal Adipose Tissue from Magnetic Resonance Images

Year: 2007

Type: article

Abstract: OBJECTIVE: To compare the inter-rater and intra-rater reliability and analysis time of two methods for quantifying visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) volumes from magnetic resonance (MR) images. RESEARCH METHODS AND PROCEDURES: Ten subjects (BMI, 27.0 +/- 2.1 kg/m(2); 56 years of age +/- 4 years) underwent MR imaging of the abdomen. Ten transverse T1-weighted images were selected from each scan and analyzed using two software packages that differ in principle. The first method, ANALYZE version 5.0, represents the manual threshold method, and the second, HIPPO version 1.3, is based on the fuzzy clustering approach. Inter-rater reliability for each method was assessed by comparing the intra-class correlation coefficients (ICCs) for VAT and SAT results from two evaluators, and intra-rater reliability for each method was assessed by comparing ICCs for VAT and SAT analyses performed 1 week apart by the same evaluator. The total time for analysis also was compared between methods. RESULTS: The inter-rater reliability for VAT was greater with HIPPO than with ANALYZE (ICC = 0.996 vs. 0.828), whereas inter-rater reliability for SAT did not differ between methods (ICC = 0.975 and 0.987). The intra-rater reliability was equally high with HIPPO and ANALYZE for both VAT (ICC = 0.998 vs. 0.992) and SAT (ICC = 0.996 vs. 0.992). HIPPO required less than one-half as much analysis time as ANALYZE (15.9 +/- 4.4 vs. 36.5 +/- 8.2 minutes, p < 0.0001). DISCUSSION: HIPPO software appears advantageous for the quantification of VAT from multislice MR images because inter-rater results are more reliable, and it is more time-efficient than less automated methods.

Source: Obesity

DOI: 10.1038/oby.2007.266

Authors: Hassan Arif, Susan B. Racette, Dennis T. Villareal, John O. Holloszy, Edward P. Weiss

Institutions: Washington University in St. Louis, Saint Louis University

Language: English

Topic: Body Composition Measurement Techniques

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Institutes of Health, National Institute on Aging, National Institute of Diabetes and Digestive and Kidney Diseases