Stockholm Sports Trauma Research Centre, Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden.
Centre for Medical Imaging, University Hospital, Uppsala University, Uppsala, Sweden.
BMC Med Imaging. 2021 Jul 5;21(1):106. doi: 10.1186/s12880-021-00638-9.
The amount of muscle volume (MV) varies between individuals and is important for health, well-being and performance. Therefore, the monitoring of MV using different imaging modalities is important. Magnetic resonance imaging (MRI) is considered the gold standard, but is not always easily accessible, and the examinations are expensive. Ultrasonography (US) is a much less expensive imaging method widely used to measure changes in muscle thickness (MT). Whether MT may translate into MV needs further investigation.
The aim of this review is to clarify whether US-derived equations based on MT predict MV based on MRI.
A systematic literature review was conducted according to the PRISMA statement, searching the electronic databases PubMed, CINAHL and Web of Science, for currently published equations to estimate MV with US.
The literature search resulted in 363 citations. Twelve articles met the eligibility criteria. Ten articles scored eight out of eleven on QUADAS and two scored nine. Thirty-six prediction equations were identified. R values ranged between 0.53 and 0.961 and the standard error of the estimate (SEE) ranged between 6 and 12% for healthy adult populations, and up to 25.6% for children with cerebral palsy. Eight studies evaluated the results with a Bland-Altman plot and found no systematic errors. The overall strength and quality of the evidence was rated "low quality" as defined by the GRADE system.
The validity of US-derived equations based on MT is specific to the populations from which it is developed. The agreement with MV based on MRI is moderate with the SEE ranging between 6 and 12% in healthy adult populations. Suggestions for future research include investigations as to whether testing positions or increasing the number of measuring sites could improve the validity for prediction equations.
肌肉量（MV）在个体之间存在差异，对于健康、幸福和表现至关重要。因此，使用不同的成像方式监测 MV 非常重要。磁共振成像（MRI）被认为是金标准，但并非总是易于获得，且检查费用昂贵。超声（US）是一种更经济实惠的成像方法，广泛用于测量肌肉厚度（MT）的变化。MT 是否可以转化为 MV 尚需进一步研究。
本综述旨在阐明基于 MT 的 US 衍生方程是否可以预测基于 MRI 的 MV。
根据 PRISMA 声明进行系统文献检索，检索了电子数据库 PubMed、CINAHL 和 Web of Science，以查找目前发表的使用 US 估计 MV 的方程。
文献检索共得到 363 条引文。12 篇文章符合纳入标准。10 篇文章在 QUADAS 中得分为 8 分（满分 11 分），2 篇得分为 9 分。共确定了 36 个预测方程。R 值范围为 0.53 至 0.961，健康成年人的估计标准误差（SEE）范围为 6%至 12%，脑瘫儿童的 SEE 最高可达 25.6%。8 项研究使用 Bland-Altman 图评估了结果，未发现系统误差。根据 GRADE 系统，证据的总体强度和质量被评为“低质量”。
基于 MT 的 US 衍生方程的有效性特定于其开发人群。与基于 MRI 的 MV 之间的一致性为中等，健康成年人的 SEE 范围为 6%至 12%。对未来研究的建议包括研究测试体位或增加测量点的数量是否可以提高预测方程的有效性。
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