Estimation of Skeletal Muscle Mass and Visceral Adipose Tissue Volume by a Single Magnetic Resonance Imaging Slice in Healthy Elderly Adults

Background: Assessing skeletal muscle (SM) and visceral adipose tissue (VAT) by a single MRI slice at lumbar vertebra (L) 3 can replace whole-body MRI in young and middle-aged adults. However, this technique has not been proven in older adults. Objective: The aim of this analysis was to reinvestigate the best estimate for SM and VAT in an independent population of healthy elderly people. Methods: SM and VAT were assessed by whole-body MRI in 84 subjects >= 60 y [45 men; mean +/- SD age: 68.4 +/- 5.4 y, mean +/- SD body mass index (in kg/m(2)): 25.5 +/- 3.5]. SM and VAT areas of 9 slices at the lumbar spine were analyzed. The best estimate was investigated by Pearson correlations. Total volumes (in liters) were predicted by the area at lumbar vertebra 3 (A(L3)). Besides Bland-Altman analysis, linear regressions were performed to explain the variance of the bias by age, height, and percentage of fat mass (%FM). In a mixed population (healthy elderly plus reference population), linear regression with total SM and VAT volume as dependent variables and A(L3), age, and height as independent variables was applied. Results: When comparing the correlation coefficients between the tissue areas and total volumes, L3 was identified as the best estimate (rrange: 0.71-0.94; all P < 0.05). However, Bland-Altman analysis showed a positive SM bias in men (mean SD: -1.0% +/- 9.0%; P < 0.05) and a negative SM bias in women (mean +/- SD: 3.7% +/- 9.6%; P < 0.05). Contrary to SM, no significant bias was observed for VAT. In the elderly, stepwise linear regression showed height as a predictor for SM bias (R-2 = 0.21, SEE = 2.07 L; P < 0.05) and %FM and age as predictors of the nonsignificant VAT bias (R-2 = 0.26, SEE = 0.22L, P < 0.05), in men only. In the mixed population, A(L3) and height were predictors for total SM, and A(L3) for total VAT, independent of sex. Conclusions: A(L3) was confirmed as the best estimate for SM and VAT volumes in healthy elderly adults. Contrary to VAT, there is a bias for SM, and height has to be added to the algorithm.