Validity of ultrasonography-derived predictions for estimating skeletal muscle volume: a systematic literature review

Abstract

Abstract Background 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. Purpose The aim of this review is to clarify whether US-derived equations based on MT predict MV based on MRI. Methods 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. Results 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. Conclusions 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.

Keywords

• Bland–Altman analysis
• Magnetic resonance imaging
• Muscle thickness
• Muscle volume
• Prediction equation
• Ultrasonography