Lean regional muscle volume estimates using explanatory bioelectrical models in healthy subjects and patients with muscle wasting

Abstract

Abstract Background The availability of non‐invasive, accessible, and reliable methods for estimating regional skeletal muscle volume is paramount in conditions involving primary and/or secondary muscle wasting. This work aimed at (i) optimizing serial bioelectrical impedance analysis (SBIA) by computing a conductivity constant based on quantitative magnetic resonance imaging (MRI) data and (ii) investigating the potential of SBIA for estimating lean regional thigh muscle volume in patients with severe muscle disorders. Methods Twenty healthy participants with variable body mass index and 20 patients with idiopathic inflammatory myopathies underwent quantitative MRI. Anatomical images and fat fraction maps were acquired in thighs. After manual muscle segmentation, lean thigh muscle volume (lVMRI) was computed. Subsequently, multifrequency (50 to 350 kHz) serial resistance profiles were acquired between current skin electrodes (i.e. ankle and hand) and voltage electrodes placed on the anterior thigh. In vivo values of the muscle electrical conductivity constant were computed using data from SBIA and MRI gathered in the right thigh of 10 healthy participants. Lean muscle volume (lVBIA) was derived from SBIA measurements using this newly computed constant. Between‐day reproducibility of lVBIA was studied in six healthy participants. Results Electrical conductivity constant values ranged from 0.82 S/m at 50 kHz to 1.16 S/m at 350 kHz. The absolute percentage difference between lVBIA and lVMRI was greater at frequencies >270 kHz (P < 0.0001). The standard error of measurement and the intra‐class correlation coefficient for lVBIA computed from measurements performed at 155 kHz (i.e. frequency with minimal difference) against lVMRI were 6.1% and 0.95 in healthy participants and 9.4% and 0.93 in patients, respectively. Between‐day reproducibility of lVBIA was as follows: standard error of measurement = 4.6% (95% confidence interval [3.2, 7.8] %), intra‐class correlation coefficient = 0.98 (95% confidence interval [0.95, 0.99]). Conclusions These findings demonstrate a strong agreement of lean muscle volume estimated using SBIA against quantitative MRI in humans, including in patients with severe muscle wasting and fatty degeneration. SBIA shows promises for non‐invasive, fast, and accessible estimation and follow‐up of lean regional skeletal muscle volume for transversal and longitudinal studies.

Keywords

• Skeletal muscle
• Bioelectrical impedance analysis
• Myopathies
• Muscle mass
• Muscle volume
• Muscle atrophy