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Intra-abdominal fat burden discriminated in vivo using proton magnetic resonance spectroscopy
Authors:Walling Brent E  Munasinghe Jeeva  Berrigan David  Bailey Michael Q  Simpson R Mark
Affiliation:Molecular Pathology Unit, Center for Cancer Research, National Cancer Institute, 37 Convent Drive, Building 37, Room 2000, Bethesda, MD 20892, USA.
Abstract: Objective: To assess proton magnetic resonance spectroscopy (1H‐MRS) as a means to distinguish among mice with disparate intra‐abdominal body fat compositions, and to measure changes in intra‐abdominal fat burden during weight loss and regain. Research Methods and Procedures: Intra‐abdominal fat burden was analyzed as a ratio of integrated areas under the curves of fat to water 1H‐MRS signals collected from a region of interest standardized across B6.V‐Lepob, C57BL/6, and A‐ZIP/F mice that exhibited various genotypically related body fat compositions, ranging from obese (B6.V‐Lepob) to minimal body fat (A‐ZIP/F). 1H‐MRS analysis of fat burden was compared with intra‐abdominal fat volume and with a single cross‐sectional intra‐abdominal fat area calculated from segmented magnetic resonance images. Similar measurements were made from obese B6.V‐Lepob mice before, during, and after they were induced to lose weight by leptin administration. Results: Relative amounts of intra‐abdominal fat analyzed by 1H‐MRS differed significantly according to body composition and genotype of the three strains of mice (p < 0.05). Intra‐abdominal fat assessed by 1H‐MRS correlated with both intra‐abdominal fat volume (r = 0.88, p < 0.001) and body weight (r = 0.82, p < 0.001) among, but not within, all three genotypes. During weight loss and regain, there was a significant overall pattern of changes in intra‐abdominal fat quantity that occurred, which was reflected by 1H‐MRS (p = 0.006). Discussion: Results support the use of localized 1H‐MRS for assessing differences in intra‐abdominal fat. Refinements in 1H‐MRS voxel region of interest size and location as well as instrument precision may result in improved correlations within certain body compositions.
Keywords:leptin  computer‐assisted image analysis  cross‐sectional anatomy  animal models  investigative techniques
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