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Int J Body Compos Res. 2009 Sep;7(3):99-107.

Validation of quantitative magnetic resonance (QMR) for determination of body composition in rats.

Author information

1
Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

Abstract

OBJECTIVE:

To validate the use of quantitative magnetic resonance (QMR) to measure fat and lean mass in conscious rats.

METHODS:

Fifty Osborne-Mendel rats (249-770 g) were scanned using the Echo Medical 2 MHz body composition analyzer. Each rat was scanned under six settings (three acquisition times, with and without determination of total water). Precision was determined by the calculated coefficient of variation (CV) of three consecutive scans. Accuracy was determined by comparing the first scan to chemical carcass analysis and analyzed by paired t-tests and least-squares regression analyses. Twenty-five rats were used in the validation study, and 25 in the cross-validation study.

RESULTS:

The precision for fat, lean and water at all settings was <1%. QMR significantly overestimated fat (~5%; P<0.0001), and underestimated both lean (~12.5%; P<0.0001) and total water (~5.5%; P<0.0001). All QMR measures were significantly correlated with carcass measures (r(2)>0.99; P<0.0001). Using prediction equations from the validation study with the cross-validation rats, there were no significant differences between QMR fat and carcass fat at any setting (P>0.400). For four of the six QMR settings, there were no significant differences between QMR and carcass lean (P>0.05). For total water, all QMR settings were significantly different than carcass (P<0.05), but only by ~1%.

CONCLUSIONS:

QMR showed excellent precision for the determination of fat, lean and water. Despite overestimating fat and underestimating lean and water, all were highly related to carcass values. When tested in the cross-validation group, QMR fat could be accurately predicted at all settings; however, lean mass (two settings) and water were still slightly different (less than 1%).

PMID:
20686636
PMCID:
PMC2914623

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