ArticleEuropean journal of clinical nutrition2023
Skeletal muscle estimation using magnetic-resonance-imaging-based equations for dual-energy X-ray absorptiometry and bioelectrical impedance analysis.
Article in European journal of clinical nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Anthropometric-based predictive equations developed with multi-component models for estimating body composition in athletes.European journal of applied physiology · 2025Pooled it
- Lower-limb muscle mass quantification and whole-body muscle loss detection using preoperative computed tomography images in patients with hip disease.International journal of computer assisted radiology and surgery · 2025Article
- Fundamental Body Composition Principles Provide Context for Fat-Free and Skeletal Muscle Loss With GLP-1 RA Treatments.Journal of the Endocrine Society · 2024Review
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Authors and funding
5 authors.
Funding
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Abstract
BACKGROUND/
objectivesSkeletal muscle mass (SMM) estimation is important but challenging in clinical settings. Criterion methods, such as magnetic resonance imaging (MRI), are often inaccessible. However, surrogate methods, such as dual-energy X-ray absorptiometry (DXA) and multi-frequency bioelectrical impedance analysis (MFBIA), can use MRI-based equations to estimate SMM, although the agreement between these methods is unclear. SUBJECTS/
methodsTotal and segmental SMM were estimated with DXA and MFBIA using MRI-based equations in 313 healthy adults (120 M, 193 F; age 30.2 ± 13.0 y; BMI 24.6 ± 4.0 kg/m
resultsStrong linear relationships were observed for total (R
conclusionsWhile DXA and MFBIA total SMM generally exhibited strong agreement, higher appendicular SMM by DXA highlights technical differences between methods.
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