Muscle Ultrasound Image Analysis with a Semi-Automated Software (MuscleExpert) Yields Results Comparable to ImageJ: Muscle Thickness, Muscle Area, and Muscle Quality.

PURPOSE

The aim of this study is to present and validate the semi-automated MuscleExpert software against the widely used ImageJ by comparing muscle thickness (MT), muscle area (MA), and muscle quality (MQ- measured as grayscale).

METHODS

Ten volunteers participated in this study. Ultrasound images of the tibialis anterior and medial gastrocnemius muscles were acquired using 2D B-mode ultrasonography and analyzed on both software. Equivalence of means was evaluated via 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 as well as standard error of measurement (SEM), and the agreement across the measurement was assessed using Bland-Altman plots.

RESULTS

The TOST for MT, MA, and MQ was within their respective equivalence margins. The ICC was excellent for all measures (MT: ICC=0.999; MA: ICC=0.999; MQ: ICC=1.000). Precision was similarly high, with CVs of 0.49% for MT, 0.54% for MA, and 0.33% for MQ, demonstrating minimal variability between the two methods. SEM values were low across all outcomes, corresponding to 0.49 % for MT, 0.53% for MA, and 0.23% for MQ. Finally, the Bland-Altman analysis demonstrated minimal systematic differences and no proportional bias between ImageJ and MuscleExpert for all three metrics.

CONCLUSION

The present findings indicate that MuscleExpert and ImageJ produce nearly identical results for MT, MA, 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.