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In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging

‘Gold standard’ reference sets of human muscle architecture are based on elderly cadaveric specimens, which are unlikely to be representative of a large proportion of the human population. This is important for musculoskeletal modeling, where the muscle force-generating properties of generic models...

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Detalles Bibliográficos
Autores principales: Charles, James P., Suntaxi, Felipe, Anderst, William J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6793854/
https://www.ncbi.nlm.nih.gov/pubmed/31613899
http://dx.doi.org/10.1371/journal.pone.0223531
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author Charles, James P.
Suntaxi, Felipe
Anderst, William J.
author_facet Charles, James P.
Suntaxi, Felipe
Anderst, William J.
author_sort Charles, James P.
collection PubMed
description ‘Gold standard’ reference sets of human muscle architecture are based on elderly cadaveric specimens, which are unlikely to be representative of a large proportion of the human population. This is important for musculoskeletal modeling, where the muscle force-generating properties of generic models are defined by these data but may not be valid when applied to models of young, healthy individuals. Obtaining individualized muscle architecture data in vivo is difficult, however diffusion tensor magnetic resonance imaging (DTI) has recently emerged as a valid method of achieving this. DTI was used here to provide an architecture data set of 20 lower limb muscles from 10 healthy adults, including muscle fiber lengths, which are important inputs for Hill-type muscle models commonly used in musculoskeletal modeling. Maximum isometric force and muscle fiber lengths were found not to scale with subject anthropometry, suggesting that these factors may be difficult to predict using scaling or optimization algorithms. These data also highlight the high level of anatomical variation that exists between individuals in terms of lower limb muscle architecture, which supports the need of incorporating subject-specific force-generating properties into musculoskeletal models to optimize their accuracy for clinical evaluation.
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spelling pubmed-67938542019-10-25 In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging Charles, James P. Suntaxi, Felipe Anderst, William J. PLoS One Research Article ‘Gold standard’ reference sets of human muscle architecture are based on elderly cadaveric specimens, which are unlikely to be representative of a large proportion of the human population. This is important for musculoskeletal modeling, where the muscle force-generating properties of generic models are defined by these data but may not be valid when applied to models of young, healthy individuals. Obtaining individualized muscle architecture data in vivo is difficult, however diffusion tensor magnetic resonance imaging (DTI) has recently emerged as a valid method of achieving this. DTI was used here to provide an architecture data set of 20 lower limb muscles from 10 healthy adults, including muscle fiber lengths, which are important inputs for Hill-type muscle models commonly used in musculoskeletal modeling. Maximum isometric force and muscle fiber lengths were found not to scale with subject anthropometry, suggesting that these factors may be difficult to predict using scaling or optimization algorithms. These data also highlight the high level of anatomical variation that exists between individuals in terms of lower limb muscle architecture, which supports the need of incorporating subject-specific force-generating properties into musculoskeletal models to optimize their accuracy for clinical evaluation. Public Library of Science 2019-10-15 /pmc/articles/PMC6793854/ /pubmed/31613899 http://dx.doi.org/10.1371/journal.pone.0223531 Text en © 2019 Charles et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Charles, James P.
Suntaxi, Felipe
Anderst, William J.
In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title_full In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title_fullStr In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title_full_unstemmed In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title_short In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
title_sort in vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6793854/
https://www.ncbi.nlm.nih.gov/pubmed/31613899
http://dx.doi.org/10.1371/journal.pone.0223531
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