Escuela Internacional de Doctorado, Universidad Rey Juan Carlos, 29222 Alcorcón, Spain.
Faculty of Health, Universidad Católica de Ávila, C/Canteros, s/n, 05005 Ávila, Spain.
Sensors (Basel). 2023 Jan 20;23(3):1213. doi: 10.3390/s23031213.
Ultrasound imaging (US) is a biosensing technique that is widely used in several healthcare disciplines (including physiotherapy) for assessing multiple muscle metrics, such as muscle morphology and quality. Since all biosensors need to be tested in order to demonstrate their reliability, accuracy, sensitivity, and specificity, identifying factors that affect their diagnostic accuracy is essential. Since previous studies analyzed the impact of sociodemographic but not body composition characteristics in US errors, this study aimed to assess whether body composition metrics are associated with ultrasound measurement errors. B-mode images of the lumbar multifidus muscle at the L5 level were acquired and analyzed in 47 healthy volunteers by two examiners (one experienced and one novice). The cross-sectional area, muscle perimeter, and mean echo intensity were calculated bilaterally. A correlation analysis and a multivariate linear regression model were used for assessing the inter-examiner differences with respect to body composition metrics. The results demonstrated good-to-excellent reliability estimates for the cross-sectional area, muscle perimeter, aspect ratio, roundness, circularity, and mean brightness metrics (all ICC > 0.85). However, solidity showed unacceptable reliability (ICC < 0.7). Age, height, total lean mass, trunk lean mass, and water volume were associated with inter-examiner disagreement on mean echo intensity. Cross-sectional area, perimeter, and roundness measurement errors were associated with lean mass and water volume.
超声成像是一种生物传感技术，广泛应用于多个医疗保健学科（包括物理治疗），用于评估多种肌肉指标，如肌肉形态和质量。由于所有生物传感器都需要经过测试，以证明其可靠性、准确性、灵敏度和特异性，因此确定影响其诊断准确性的因素至关重要。由于之前的研究分析了社会人口统计学因素，但没有分析身体成分特征对 US 误差的影响，因此本研究旨在评估身体成分指标是否与超声测量误差相关。在 47 名健康志愿者中，由两名检查者（一名经验丰富，一名新手）采集并分析了 L5 水平腰椎多裂肌的 B 型超声图像。双侧计算横截面积、肌肉周长和平均回波强度。使用相关分析和多元线性回归模型评估了身体成分指标的检查者间差异。结果表明，横截面积、肌肉周长、纵横比、圆形度、圆度和平均亮度指标的可靠性估计值良好到优秀（所有 ICC > 0.85）。然而，坚固性的可靠性不可接受（ICC < 0.7）。年龄、身高、总瘦体重、躯干瘦体重和水容量与平均回波强度的检查者间差异相关。横截面积、周长和圆形度测量误差与瘦体重和水体积相关。
