Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models
Abstract Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular l...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-29827-y |
| _version_ | 1797453204496056320 |
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| author | Cassidy McCarthy Grant M. Tinsley Anja Bosy-Westphal Manfred J. Müller John Shepherd Dympna Gallagher Steven B. Heymsfield |
| author_facet | Cassidy McCarthy Grant M. Tinsley Anja Bosy-Westphal Manfred J. Müller John Shepherd Dympna Gallagher Steven B. Heymsfield |
| author_sort | Cassidy McCarthy |
| collection | DOAJ |
| description | Abstract Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88–0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM – 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings. |
| first_indexed | 2024-03-09T15:19:26Z |
| format | Article |
| id | doaj.art-58fbc17b61024b569a3be6fc57542528 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:19:26Z |
| publishDate | 2023-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-58fbc17b61024b569a3be6fc575425282023-11-26T12:53:00ZengNature PortfolioScientific Reports2045-23222023-02-0113111010.1038/s41598-023-29827-yTotal and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition modelsCassidy McCarthy0Grant M. Tinsley1Anja Bosy-Westphal2Manfred J. Müller3John Shepherd4Dympna Gallagher5Steven B. Heymsfield6Pennington Biomedical Research Center, Louisiana State University SystemDepartment of Kinesiology and Sport Management, Texas Tech UniversityDepartment of Human Nutrition and Food Science, Christian-Albrecht’s-University of KielDepartment of Human Nutrition and Food Science, Christian-Albrecht’s-University of KielUniversity of Hawaii Cancer CenterDepartment of Medicine, College of Physicians and Surgeons, New York Obesity Research Center, Columbia UniversityPennington Biomedical Research Center, Louisiana State University SystemAbstract Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88–0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM – 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings.https://doi.org/10.1038/s41598-023-29827-y |
| spellingShingle | Cassidy McCarthy Grant M. Tinsley Anja Bosy-Westphal Manfred J. Müller John Shepherd Dympna Gallagher Steven B. Heymsfield Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models Scientific Reports |
| title | Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models |
| title_full | Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models |
| title_fullStr | Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models |
| title_full_unstemmed | Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models |
| title_short | Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models |
| title_sort | total and regional appendicular skeletal muscle mass prediction from dual energy x ray absorptiometry body composition models |
| url | https://doi.org/10.1038/s41598-023-29827-y |
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