Shim Ga Yang, Kim Jong Bum, Won Chang Won, Lim Jae-Young
Department of Physical and Rehabilitation Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea.
Department of Rehabilitation Medicine, TK Orthopedic Surgery Hospital, Gyeonggi, Republic of Korea.
Aging (Albany NY). 2025 Aug 1;17(8):1988-1998. doi: 10.18632/aging.206294.
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, = 94), middle-aged (Group B, = 84), and older (Group C, = 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 R 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 R. 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.
超声是评估肌肉状态的一种有用工具。基于超声测量的估算方程已被用于估算四肢骨骼肌质量(ASM)。然而,与其他既定技术相比,骨骼肌的年龄相关变化可能会影响基于超声测量的准确性。本研究旨在探讨不同年龄组之间的这些关联,并确定ASM估算是否需要特定年龄模型。总共分析了265名受试者,并将其分为三个年龄组:年轻组(A组,n = 94)、中年组(B组,n = 84)和老年组(C组,n = 87)。使用超声测量股直肌(RF)肌肉厚度(MT),并使用生物电阻抗分析评估ASM,生物电阻抗分析作为参考方法。以RF MT作为主要预测因子,为每个年龄组和总组(A + B + C组)建立多元线性回归模型。所有模型均显示出较高的调整后R值(0.881 - 0.955)。基于较低的均方根误差、平均绝对误差和较高的调整后R,特定组模型显示出比总组模型更高的准确性。这些发现突出了使用特定组模型提高基于超声的ASM估算准确性的临床相关性,从而改善肌肉减少症的筛查和早期识别。未来有必要在不同人群和临床环境中进行验证。