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Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models
The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-sp...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280327/ https://www.ncbi.nlm.nih.gov/pubmed/32185569 http://dx.doi.org/10.1007/s10439-020-02490-4 |
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author | Modenese, Luca Kohout, Josef |
author_facet | Modenese, Luca Kohout, Josef |
author_sort | Modenese, Luca |
collection | PubMed |
description | The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-specific models from medical images, so potentially restricting the options for personalisation and assessment of muscle geometrical models. To overcome this methodological limitation, we propose a novel, completely automated technique that, from a surface geometry of a skeletal muscle and its attachment areas, can generate an arbitrary number of lines of action (fibres) composed by a user-defined number of straight-line segments. These fibres can be included in standard musculoskeletal models and used in biomechanical simulations. This methodology was applied to the surfaces of four muscles surrounding the hip joint (iliacus, psoas, gluteus maximus and gluteus medius), segmented on magnetic resonance imaging scans from a cadaveric dataset, for which highly discretised muscle representations were created and used to simulate functional tasks. The fibres’ moment arms were validated against measurements and models of the same muscles from the literature with promising outcomes. The proposed approach is expected to improve the anatomical representation of skeletal muscles in personalised biomechanical models and finite element applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-020-02490-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7280327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-72803272020-06-15 Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models Modenese, Luca Kohout, Josef Ann Biomed Eng Original Article The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-specific models from medical images, so potentially restricting the options for personalisation and assessment of muscle geometrical models. To overcome this methodological limitation, we propose a novel, completely automated technique that, from a surface geometry of a skeletal muscle and its attachment areas, can generate an arbitrary number of lines of action (fibres) composed by a user-defined number of straight-line segments. These fibres can be included in standard musculoskeletal models and used in biomechanical simulations. This methodology was applied to the surfaces of four muscles surrounding the hip joint (iliacus, psoas, gluteus maximus and gluteus medius), segmented on magnetic resonance imaging scans from a cadaveric dataset, for which highly discretised muscle representations were created and used to simulate functional tasks. The fibres’ moment arms were validated against measurements and models of the same muscles from the literature with promising outcomes. The proposed approach is expected to improve the anatomical representation of skeletal muscles in personalised biomechanical models and finite element applications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10439-020-02490-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-03-17 2020 /pmc/articles/PMC7280327/ /pubmed/32185569 http://dx.doi.org/10.1007/s10439-020-02490-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Article Modenese, Luca Kohout, Josef Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title | Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title_full | Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title_fullStr | Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title_full_unstemmed | Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title_short | Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models |
title_sort | automated generation of three-dimensional complex muscle geometries for use in personalised musculoskeletal models |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7280327/ https://www.ncbi.nlm.nih.gov/pubmed/32185569 http://dx.doi.org/10.1007/s10439-020-02490-4 |
work_keys_str_mv | AT modeneseluca automatedgenerationofthreedimensionalcomplexmusclegeometriesforuseinpersonalisedmusculoskeletalmodels AT kohoutjosef automatedgenerationofthreedimensionalcomplexmusclegeometriesforuseinpersonalisedmusculoskeletalmodels |