MuscleExpert: a semi-automated tool delivering ImageJ-comparable measurements of muscle thickness, area, and quality
Year: 2026
Type: article
Abstract: Background: Most image-analysis software programs were not designed specifically for ultrasound-based measurements, resulting in irrelevant general-purpose features that force users to navigate through multiple menus and making the analysis time-consuming and increasing the likelihood of error. The aim of this study was to present and validate the semi-automated MuscleExpert software against the widely used ImageJ by comparing muscle thickness (MT), cross-sectional area (CSA), and muscle quality (MQ-measured as echo intensity). Methods: the two-one-sided tests (TOST) procedure; the reliability between means was quantified by an intraclass correlation coefficient (ICC); the precision was expressed as the coefficient of variation (CV) and standard error of measurement (SEM); and agreement was assessed using Bland-Altman plots. Results: The TOST for MT, CSA, and MQ were within their respective equivalence margins. The ICC was excellent for all measures (MT: ICC = 0.999; CSA: ICC = 0.999; MQ: ICC = 1.000). Precision was similarly high, with CVs of 0.49% (MT), 0.54% (CSA), and 0.33% (MQ), demonstrating minimal variability between the two methods. SEM values were low across all outcomes, corresponding to 0.49% (MT), 0.53% (CSA), and 0.23% (MQ). Finally, the Bland-Altman analysis demonstrated minimal systematic differences and no proportional bias between ImageJ and MuscleExpert for all metrics. The present findings indicate that MuscleExpert and ImageJ produce nearly identical results for MT, CSA, and MQ. These findings support the integration of MuscleExpert into clinical and research workflows, offering a more efficient solution for muscle assessment without compromising measurement integrity.
Source: PeerJ
DOI: 10.7717/peerj.21757
Authors: Zongpan Li, Li-Qun Zhang, Marcel Bahia Lanza
Institution: University of Maryland, Baltimore
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,395
OpenAlex ID: W7214074487