Abstract
Skeletal muscle (SM) is an important body-composition component that remains difficult and impractical to quantify by most investigators outside of specialized research centers. A large proportion of total-body SM is found in the extremities, and a large proportion of extremity lean soft tissue is SM. A strong link should thus exist between appendicular lean soft tissue (ALST) mass and total-body SM mass. The objective was to develop prediction models linking ALST estimated by dual-energy X-ray absorptiometry (DXA) with total-body SM quantified by multislice magnetic resonance imaging in healthy adults. ALST and total-body SM were evaluated with a cross-sectional design in adults [body mass index (in kg/m(2)) < 35] with an SM-prediction model developed and validated in model-development and model-validation groups, respectively. The model-development and model-validation groups included 321 and 93 ethnically diverse adults, respectively. ALST alone was highly correlated with total-body SM (model 1: R(2) = 0.96, SEE = 1.63 kg, P < 0.001), although multiple regression analyses showed 2 additional predictor variables: age (model 2: 2-variable combined R(2) = 0.96, SEE = 1.58 kg, P < 0.001) and sex (model 3: 3-variable combined R(2) = 0.96, SEE = 1.58 kg, P < 0.001). All 3 models performed well in the validation group. An SM-prediction model based on the SM-ALST ratio was also developed, although this model had limitations when it was applied across all subjects. Total-body SM can be accurately predicted from DXA-estimated ALST, thus affording a practical means of quantifying the large and clinically important SM compartment.
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