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Automated assessment of regional muscle volume and hypertrophy using MRI

This study aimed to validate a fully automatic method to quantify knee-extensor muscle volume and exercise-induced hypertrophy. By using a magnetic resonance imaging-based fat-water separated two-point Dixon sequence, the agreement between automated and manual segmentation of a specific ~15-cm regio...

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Autores principales: Mandić, Mirko, Rullman, Eric, Widholm, Per, Lilja, Mats, Dahlqvist Leinhard, Olof, Gustafsson, Thomas, Lundberg, Tommy R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010694/
https://www.ncbi.nlm.nih.gov/pubmed/32042024
http://dx.doi.org/10.1038/s41598-020-59267-x
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author Mandić, Mirko
Rullman, Eric
Widholm, Per
Lilja, Mats
Dahlqvist Leinhard, Olof
Gustafsson, Thomas
Lundberg, Tommy R.
author_facet Mandić, Mirko
Rullman, Eric
Widholm, Per
Lilja, Mats
Dahlqvist Leinhard, Olof
Gustafsson, Thomas
Lundberg, Tommy R.
author_sort Mandić, Mirko
collection PubMed
description This study aimed to validate a fully automatic method to quantify knee-extensor muscle volume and exercise-induced hypertrophy. By using a magnetic resonance imaging-based fat-water separated two-point Dixon sequence, the agreement between automated and manual segmentation of a specific ~15-cm region (partial volume) of the quadriceps muscle was assessed. We then explored the sensitivity of the automated technique to detect changes in both complete and partial quadriceps volume in response to 8 weeks of resistance training in 26 healthy men and women. There was a very strong correlation (r = 0.98, P < 0.0001) between the manual and automated method for assessing partial quadriceps volume, yet the volume was 9.6% greater with automated compared with manual analysis (P < 0.0001, 95% limits of agreement −93.3 ± 137.8 cm(3)). Partial muscle volume showed a 6.0 ± 5.0% (manual) and 4.8 ± 8.3% (automated) increase with training (P < 0.0001). Similarly, the complete quadriceps increased 5.1 ± 5.5% with training (P < 0.0001). The intramuscular fat proportion decreased (P < 0.001) from 4.1% to 3.9% after training. In conclusion, the automated method showed excellent correlation with manual segmentation and could detect clinically relevant magnitudes of exercise-induced muscle hypertrophy. This method could have broad application to accurately measure muscle mass in sports or to monitor clinical conditions associated with muscle wasting and fat infiltration.
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spelling pubmed-70106942020-02-21 Automated assessment of regional muscle volume and hypertrophy using MRI Mandić, Mirko Rullman, Eric Widholm, Per Lilja, Mats Dahlqvist Leinhard, Olof Gustafsson, Thomas Lundberg, Tommy R. Sci Rep Article This study aimed to validate a fully automatic method to quantify knee-extensor muscle volume and exercise-induced hypertrophy. By using a magnetic resonance imaging-based fat-water separated two-point Dixon sequence, the agreement between automated and manual segmentation of a specific ~15-cm region (partial volume) of the quadriceps muscle was assessed. We then explored the sensitivity of the automated technique to detect changes in both complete and partial quadriceps volume in response to 8 weeks of resistance training in 26 healthy men and women. There was a very strong correlation (r = 0.98, P < 0.0001) between the manual and automated method for assessing partial quadriceps volume, yet the volume was 9.6% greater with automated compared with manual analysis (P < 0.0001, 95% limits of agreement −93.3 ± 137.8 cm(3)). Partial muscle volume showed a 6.0 ± 5.0% (manual) and 4.8 ± 8.3% (automated) increase with training (P < 0.0001). Similarly, the complete quadriceps increased 5.1 ± 5.5% with training (P < 0.0001). The intramuscular fat proportion decreased (P < 0.001) from 4.1% to 3.9% after training. In conclusion, the automated method showed excellent correlation with manual segmentation and could detect clinically relevant magnitudes of exercise-induced muscle hypertrophy. This method could have broad application to accurately measure muscle mass in sports or to monitor clinical conditions associated with muscle wasting and fat infiltration. Nature Publishing Group UK 2020-02-10 /pmc/articles/PMC7010694/ /pubmed/32042024 http://dx.doi.org/10.1038/s41598-020-59267-x Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mandić, Mirko
Rullman, Eric
Widholm, Per
Lilja, Mats
Dahlqvist Leinhard, Olof
Gustafsson, Thomas
Lundberg, Tommy R.
Automated assessment of regional muscle volume and hypertrophy using MRI
title Automated assessment of regional muscle volume and hypertrophy using MRI
title_full Automated assessment of regional muscle volume and hypertrophy using MRI
title_fullStr Automated assessment of regional muscle volume and hypertrophy using MRI
title_full_unstemmed Automated assessment of regional muscle volume and hypertrophy using MRI
title_short Automated assessment of regional muscle volume and hypertrophy using MRI
title_sort automated assessment of regional muscle volume and hypertrophy using mri
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010694/
https://www.ncbi.nlm.nih.gov/pubmed/32042024
http://dx.doi.org/10.1038/s41598-020-59267-x
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