Research Paper Advance Articles
Models for age-specific estimation of appendicular skeletal muscle mass using the ultrasound-measured rectus femoris muscle thickness
- 1 Department of Physical and Rehabilitation Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea
- 2 Department of Rehabilitation Medicine, TK Orthopedic Surgery Hospital, Gyeonggi, Republic of Korea
- 3 Department of Family Medicine, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea
- 4 Department of Rehabilitation Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Gyeonggi, Republic of Korea
- 5 Institute on Aging, Seoul National University, Seoul, Republic of Korea
Received: April 2, 2025 Accepted: July 15, 2025 Published: August 1, 2025
https://doi.org/10.18632/aging.206294How to Cite
Copyright: © 2025 Shim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Ultrasound is a useful tool for assessing muscle status. Estimation equations based on ultrasound measurements have been used to approximate appendicular skeletal muscle mass (ASM). However, age-related changes in skeletal muscle may influence the accuracy of ultrasound-based measurements, as compared to other established techniques. This study aimed to examine these associations across various age groups and to determine whether age-specific models are required for ASM estimation. A total of 265 subjects were analyzed and divided into three age groups: young (Group A, n = 94), middle-aged (Group B, n = 84), and older (Group C, n = 87). Rectus femoris (RF) muscle thickness (MT) was measured using ultrasound and ASM assessed using bioelectrical impedance analysis, which served as the reference method. Multivariate linear regression models were developed for each age group and for total group (Groups A+B+C) using RF MT as the primary predictor. All models showed high adjusted R2 values (0.881–0.955). Group-specific models demonstrating greater accuracy than total group model, based on lower root mean square error, the mean absolute error, and higher adjusted R2. These findings highlight the clinical relevance of using group-specific models to enhance the accuracy of ultrasound-based ASM estimation, thereby improving the screening and early identification of sarcopenia. Future validation in diverse populations and clinical settings is warranted.