A S Jones1, M S Johnson, T R Nagy. 1. Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA.
Abstract
OBJECTIVE: The aim of this study was to assess the precision and accuracy of a quantitative magnetic resonance (QMR) instrument for measuring body composition in live, non-anesthetized mice. METHODS: Forty-eight mice of varying strains, ages and body weights (15.3 to 50.2g) were scanned three times each in the QMR instrument. Animals were killed and chemical carcass analysis performed for comparison. Precision was assessed as the coefficient of variation (CV) for the triplicate scans and accuracy was determined by comparing the first QMR data with the chemical analysis. Prediction equations were generated by linear regression analysis and used in a cross-validation study in which 26 mice were scanned once each, killed, and chemical carcass analysis performed. RESULTS: The mean CV was 1.58% for fat mass (FM) and 0.78% for lean-tissue mass (LTM). QMR significantly (P<0.01) overestimated FM (7.76±5.93 vs. 6.03±5.17g) and underestimated LTM (20.73±6.19 vs. 22.48±6.75g) when compared with chemical carcass analysis. A strong relationship between QMR and chemical data (r(2)=0.99 and r(2)=0.97 for fat and LTM respectively; P<0.0001) allowed for the generation of correction equations that were applied to QMR data in the cross-validation study. There was no significant difference between data predicted from QMR and chemical carcass data for FM and LTM (P=0.15 and 0.10 respectively). CONCLUSION: The QMR instrument showed excellent precision and data was highly correlated with chemical carcass analysis. This combined with QMR's speed for whole animal analysis (95 seconds) make it a highly feasible and useful method for the determination of body composition in live, non-anesthetized mice.
OBJECTIVE: The aim of this study was to assess the precision and accuracy of a quantitative magnetic resonance (QMR) instrument for measuring body composition in live, non-anesthetized mice. METHODS: Forty-eight mice of varying strains, ages and body weights (15.3 to 50.2g) were scanned three times each in the QMR instrument. Animals were killed and chemical carcass analysis performed for comparison. Precision was assessed as the coefficient of variation (CV) for the triplicate scans and accuracy was determined by comparing the first QMR data with the chemical analysis. Prediction equations were generated by linear regression analysis and used in a cross-validation study in which 26 mice were scanned once each, killed, and chemical carcass analysis performed. RESULTS: The mean CV was 1.58% for fat mass (FM) and 0.78% for lean-tissue mass (LTM). QMR significantly (P<0.01) overestimated FM (7.76±5.93 vs. 6.03±5.17g) and underestimated LTM (20.73±6.19 vs. 22.48±6.75g) when compared with chemical carcass analysis. A strong relationship between QMR and chemical data (r(2)=0.99 and r(2)=0.97 for fat and LTM respectively; P<0.0001) allowed for the generation of correction equations that were applied to QMR data in the cross-validation study. There was no significant difference between data predicted from QMR and chemical carcass data for FM and LTM (P=0.15 and 0.10 respectively). CONCLUSION: The QMR instrument showed excellent precision and data was highly correlated with chemical carcass analysis. This combined with QMR's speed for whole animal analysis (95 seconds) make it a highly feasible and useful method for the determination of body composition in live, non-anesthetized mice.
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