Sports Medicine - Open (Aug 2024)

Stressing the Relevance of Differentiating between Systematic and Random Measurement Errors in Ultrasound Muscle Thickness Diagnostics

  • Lars Hubertus Lohmann,
  • Martin Hillebrecht,
  • Stephan Schiemann,
  • Konstantin Warneke

DOI
https://doi.org/10.1186/s40798-024-00755-z
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Abstract Background The majority of studies that explore changes in musculature following resistance training interventions or examine atrophy due to immobilization or sarcopenia use ultrasound imaging. While most studies assume acceptable to excellent reliability, there seems to be unawareness of the existing absolute measurement errors. As early as 1998, methodological research addressed a collective unawareness of the random measurement error and its practical indications. Referring to available methodological approaches, within this work, we point out the limited value of focusing on relative, correlation-based reliability indices for the interpretability in scientific research but also for clinical application by assessing 1,512 muscle thickness values from more than 400 ultrasound images. To account for intra- and inter-day repeatability, data were collected on two consecutive days within four testing sessions. Commonly-stated reliability values (ICC, CV, SEM and MDC) were calculated, while evidence-based agreement analyses were applied to provide the accompanied systematic and random measurement error. Results While ICCs in the range of 0.832 to 0.998 are in accordance with the available literature, the mean absolute percentage error ranges from 1.34 to 20.38% and the mean systematic bias from 0.78 to 4.01 mm (all p ≤ 0.013), depending on the measurement time points chosen for data processing. Conclusions In accordance with prior literature, a more cautious interpretation of relative reliability values should be based on included systematic and random absolute measurement scattering. Lastly, this paper discusses the rationale for including different measurement error statistics when determining the validity of pre-post changes, thus, accounting for the certainty of evidence.

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