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Automated assessmen...
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Mandić, MirkoKarolinska Institutet,Karolinska Institutet, Sweden; Karolinska University Hospital, Sweden
(author)
Automated assessment of regional muscle volume and hypertrophy using MRI
- Article/chapterEnglish2020
Publisher, publication year, extent ...
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2020-02-10
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Nature Publishing Group,2020
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electronicrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:liu-169057
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https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-169057URI
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https://doi.org/10.1038/s41598-020-59267-xDOI
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http://kipublications.ki.se/Default.aspx?queryparsed=id:144463970URI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Funding agencies: Swedish Council for Research in Sport Science (CIF); Swedish Research CouncilSwedish Research Council; Karolinska InstituteKarolinska Institutet
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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 cm3). 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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Rullman, EricKarolinska Institutet,Karolinska Institutet, Sweden; Karolinska University Hospital, Sweden
(author)
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Widholm, PerLinköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Region Östergötland, Röntgenkliniken i Linköping,AMRA Medical AB, Sweden(Swepub:liu)perwi01
(author)
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Lilja, MatsKarolinska Institutet, Sweden; Karolinska University Hospital, Sweden
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Dahlqvist Leinhard, Olof,1978-Linköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Region Östergötland, Röntgenkliniken i Linköping,Region Östergötland, Medicinsk strålningsfysik,AMRA Medical AB, Sweden(Swepub:liu)oloda24
(author)
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Gustafsson, ThomasKarolinska Institutet,Karolinska Institutet, Sweden; Karolinska University Hospital, Sweden
(author)
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Lundberg, Tommy R.Karolinska Institutet,Institutet, Sweden; Karolinska University Hospital, Sweden
(author)
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Karolinska InstitutetKarolinska Institutet, Sweden; Karolinska University Hospital, Sweden
(creator_code:org_t)
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In:Scientific Reports: Nature Publishing Group10:12045-2322
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