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

John F Drazan1, Todd J Hullfish1, Josh R Baxter1

  • 1Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, PA, USA.

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|July 16, 2019
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Summary

This study developed an automatic fascicle tracking algorithm for muscle biomechanics. The algorithm accurately measures fascicle length and pennation angle, showing high repeatability and reproducibility for clinical research.

Keywords:
ContractionDynamometryFascicleFoot and ankleGastrocnemiusImagingMuscle mechanicsUltrasound

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Area of Science:

  • Biomechanics
  • Musculoskeletal Ultrasound
  • Medical Imaging Analysis

Background:

  • Ultrasound enables dynamic muscle structure measurement in biomechanics.
  • Manual fascicle length and pennation angle measurements are time-consuming, limiting clinical use and research sample sizes.

Purpose of the Study:

  • Develop an automatic fascicle tracking program for muscle fascicle length and pennation angle quantification during dynamic contractions.
  • Evaluate the repeatability and reproducibility of the automatic tracking algorithm.

Main Methods:

  • Five healthy adults underwent maximal effort contractions (isometric and isokinetic) while medial gastrocnemius was imaged with ultrasound.
  • An algorithm automatically tracked muscle fascicles and aponeuroses after initial user identification.
  • Repeatability and reproducibility assessed using intra-class correlation coefficients (ICC); agreement with manual measurements using coefficient of multiple correlations (CMC).

Main Results:

  • Automatic and manual measurements demonstrated strong repeatability and reproducibility (ICC > 0.74).
  • High agreement (CMC > 0.8) was found between manual and automatic measurements for both fascicle length and pennation angle.
  • Supervised automatic tracking showed very strong agreement (CMC > 0.94) and reduced error compared to a previous program.

Conclusions:

  • A novel automatic fascicle tracking algorithm was developed for quantifying muscle fascicle length and pennation angle during dynamic contractions.
  • The algorithm exhibits strong repeatability and reproducibility across examiners and days.
  • Strong agreement with manual measurements was confirmed, particularly with user supervision for reinitialization.