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research-article

Determining subject-specific lower-limb muscle architecture data for musculoskeletal models using diffusion tensor MRI

[+] Author and Article Information
James P Charles

Department of Musculoskeletal Biology, Institute of Aging and Chronic Disease, University of Liverpool, Liverpool, United Kingdom
j.charles@liverpool.ac.uk

Chan-Hong Moon

Magnetic Resonance Research Center, Department of Radiology, University of Pittsburgh, PA, USA
moonchgm@gmail.com

William Anderst

Biodynamics Lab, Department of Orthopaedic Surgery, University of Pittsburgh, PA, USA
anderst@pitt.edu

1Corresponding author.

ASME doi:10.1115/1.4040946 History: Received February 21, 2018; Revised July 03, 2018

Abstract

Accurate individualized muscle architecture data is crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor magnetic resonance (MR) imaging (DTI) has emerged as a promising method of gathering muscle architecture data in vivo, however its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here we provide a validation of the method of using anatomical MRI and DTI to gather muscle architecture data in vivo, by directly comparing those data obtained from MR scans of 3 human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.

Copyright (c) 2018 by ASME
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