Quantitative estimation of muscle mass in older adults at risk of sarcopenia using ultrasound: a cross-sectional study.

Abstract

Sarcopenia is an age-associated syndrome of decreased skeletal muscle function and loss of muscle mass. This cross-sectional study was designed to investigate whether ultrasound can be used to quantitatively estimate muscle mass in older adults as an efficient assistive method for the diagnosis of sarcopenia. A cohort of 103 older adults older aged over 60 years who were at risk of sarcopenia, including 57 males and 46 females, was recruited. The participants underwent ultrasound to measure the muscle thickness (MT) of 11 sites across the whole body. Bioelectrical impedance analysis (BIA) was then used to estimate the appendicular muscle mass, and the correlation between skeletal muscle mass index (SMI) and MT at different sites was studied. Finally, muscle mass estimation algorithms for older adults were developed using multiple linear regression. Male participants had a significantly higher SMI (7.03±0.73 vs. 5.84±0.72 kg/m2, P<0.001) and higher MT than female participants at all 11 sites (all P<0.05). The MT of Site 7 (rectus femoris and intermedius femoris) in males had the strongest correlation with SMI (R=0.719, P<0.001). In females, the MT at Site 3 (flexor pollicis longus, flexor digitorum superficialis, and brachioradialis) had the strongest correlation with SMI (R=0.733, P<0.001). The MT of Site 7 was selected for a one-site algorithm; the R2 and standard error of estimate (SEE) values were 0.701 and 0.519 kg/m2, respectively. The MT of Site 3, Site 7, Site 1 (biceps and brachialis), and Site 9 (tibialis anterior) were selected for a four-site algorithm; the R2 and SEE values were 0.819 and 0.404 kg/m2, respectively. MT measured using ultrasound is correlated with SMI at some sites, and the correlations differ between men and women. When sex and age were included in the algorithm, the MT at Site 1, Site 3, Site 7, and Site 9 were valuable for estimating SMI, with Site 7 being the best parameter among them. Ultrasound-derived algorithms can achieve a satisfying fitting effect and provide new solutions for muscle mass estimation in older adults.