Abstract
B-mode ultrasound is often used to quantify muscle architecture during movements. Our objectives were to 1) systematically review the reliability of fascicle length (FL) and pennation angles (PA) measured using ultrasound during movements involving voluntary contractions; 2) systematically review the methods used in studies reporting reliability, discuss associated challenges, and provide recommendations to improve the reliability and validity of dynamic ultrasound measurements; and 3) provide an overview of computational approaches for quantifying fascicle architecture, their validity, agreement with manual quantification of fascicle architecture, and advantages and drawbacks. Three databases were searched until June 2019. Studies among healthy human individuals aged 17-85 yr that investigated the reliability of FL or PA in lower-extremity muscles during isoinertial movements and that were written in English were included. Thirty studies (n = 340 participants) were included for reliability analyses. Between-session reliability as measured by coefficient of multiple correlations (CMC), and coefficient of variation (CV) was FL CMC: 0.89-0.96; CV: 8.3% and PA CMC: 0.87-0.90: CV: 4.5-9.6%. Within-session reliability was FL CMC: 0.82-0.99; CV: 0.0-6.7% and PA CMC: 0.91; CV: 0.0-15.0%. Manual analysis reliability was FL CMC: 0.89-0.96; CV: 0.015.9%; PA CMC: 0.84-0.90; and CV: 2.0-9.8%. Computational analysis FL CMC was 0.82-0.99, and PA CV was 14.0-15.0%. Eighteen computational approaches were identified, and these generally showed high agreement with manual analysis and high validity compared with phantoms or synthetic images. B-mode ultrasound is a reliable method to quantify fascicle architecture during movement. Additionally, computational approaches can provide a reliable and valid estimation of fascicle architecture.
Original language | English |
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Pages (from-to) | 978-999 |
Number of pages | 22 |
Journal | Journal of Applied Physiology |
Volume | 128 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2020 |
Keywords
- computer vision
- fascicle
- feature tracking
- image segmentation
- sonogram
- MEDIAL GASTROCNEMIUS-MUSCLE
- HUMAN TRICEPS SURAE
- FASCICLE LENGTH
- VASTUS LATERALIS
- TENDON INTERACTION
- TENDINOUS STRUCTURES
- AUTOMATIC TRACKING
- TIBIALIS ANTERIOR
- STRETCH RESPONSES
- PENNATION ANGLE