Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models

Abstract

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R²s (0.88-0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM - 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings.

Figure 1

Total skeletal muscle mass (SM) measured with MRI versus appendicular lean mass (ALM) measured with DXA in the whole sample (n = 475). The Deming regression equation, line (solid), and R² are shown in the figure (p < 0.001).

Figure 2

Predicted total, arm, and leg skeletal muscle (SM) mass versus corresponding value measured with MRI in the validation sample (n = 47 women; 48 men) on the left (A,C,E) and associated Bland–Altman plots on the right (B,D,F). The regression equations, lines, R²s, and 95% limits of agreement (LOA) are shown in the figures. The statistical significance of each panel is summarized in the text.

Figure 3

Total skeletal muscle (SM) mass predicted by Kim’s equation versus SM measured with MRI at Kiel (A) and corresponding Bland–Altman plot (B) (n = 475). Total body skeletal muscle (SM) mass predicted by the newly developed Kiel equation versus SM measured with MRI by Kim et al. (C) and corresponding Bland–Altman plot (D) (n = 270). The lines of identity (thin solid line), regression equations and lines (solid lines with gray shading indicating 95% CI), and R²s are shown in (A,C). The regression lines with 95% CI and 95% limits of agreement (LOA) (dashed lines) are shown in (B,D). Statistical significance of each panel is summarized in the text.