An automatic fascicle tracking algorithm quantifying gastrocnemius architecture during maximal effort contractions.

Abstract

BackgroundUltrasound has become a commonly used imaging modality for making dynamic measurements of muscle structure during functional movements in biomechanical studies. Manual measurements of fascicle length and pennation angle are time intensive which limits the clinical utility of this approach while also limiting sample sizes in research. The purpose of this study was to develop an automatic fascicle tracking program to quantify the length and pennation angle of a muscle fascicle during maximal effort voluntary contractions and to evaluate its repeatability between days and reproducibility between different examiners.MethodsFive healthy adults performed maximal effort isometric and isokinetic contractions at 30, 120, 210, and 500 degrees per second about their ankle on an isokinetic dynamometer while their medial gastrocnemius muscle was observed using ultrasound. Individual muscle fascicles and the two aponeuroses were identified by the user in the first frame and automatically tracked by the algorithm by three observers on three separate days. Users also made manual measurements of the candidate fascicle for validation. Repeatability within examiners across days and reproducibility across examiners and days were evaluated using intra-class correlation coefficients (ICC). Agreement between manual and automatic tracking was evaluated using the coefficient of multiple correlations (CMC) and root-mean-square error. Supervised automatic tracking, where the program could be reinitialized if poor tracking was observed, was performed on all videos by one examiner to evaluate the performance of automatic tracking in a typical use case. We also compared the performance our program to a preexisting automatic tracking program.ResultsWe found both manual and automatic measurements of fascicle length and pennation angle to be strongly repeatable within examiners and strongly reproducible across examiners and days (ICCs > 0.74). There was greater agreement between manual and automatic measurements of fascicle length than pennation angle, however the mean CMC value was found to be strong in both cases (CMC > 0.8). Supervision of automatic tracking showed very strong agreement between manual and automatic measurements of fascicle length and pennation angle (CMC > 0.94). It also had considerably less error relative to the preexisting automatic tracking program.ConclusionsWe have developed a novel automatic fascicle tracking algorithm that quantifies fascicle length and pennation angle of individual muscle fascicles during dynamic contractions during isometric and across a range of isokinetic velocities. We demonstrated that this fascicle tracking algorithm is strongly repeatable and reproducible across different examiners and different days and showed strong agreement with manual measurements, especially when tracking is supervised by the user so that tracking can be reinitialized if poor tracking quality is observed.