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Quantifying Leg Muscle Disuse Atrophy During Bed Rest Using DXA, CT, and MRI
Cas J Fuchs1, Wesley J H Hermans1, Job van den Hurk2
1Department of Human Biology, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, the Netherlands.
European Journal of Sport Science
|April 10, 2025
Summary
Dual-energy X-ray absorptiometry (DXA), computed tomography (CT), and magnetic resonance imaging (MRI) accurately quantify muscle loss from disuse. Automated MRI analysis provides a practical and precise method for measuring skeletal muscle atrophy.
Area of Science:
- Physiology
- Radiology
- Biomedical Engineering
Background:
- Skeletal muscle atrophy due to disuse is a significant concern in various clinical settings.
- Accurate quantification of muscle loss is crucial for evaluating interventions and understanding physiological responses.
- Current methods like manual MRI analysis can be labor-intensive and costly.
Purpose of the Study:
- To compare the efficacy of DXA, CT, and MRI in quantifying disuse-induced skeletal muscle atrophy.
- To evaluate an automated MRI analysis method for measuring leg muscle volume changes after bed rest.
Main Methods:
- Twelve healthy males underwent two weeks of strict bed rest.
- Leg muscle assessments were performed before and after bed rest using DXA, CT, and MRI.
- MRI data were analyzed using both manual and automated (AMRA) methods.
Main Results:
- DXA showed a 5% decline in leg lean mass (p < 0.001).
- CT revealed a 6% decrease in thigh muscle cross-sectional area (p < 0.001).
- MRI demonstrated a 5% reduction in muscle volume, with manual and automated methods showing high correlation (r=0.96).
Conclusions:
- DXA, CT, and MRI consistently quantify significant leg muscle loss after two weeks of bed rest.
- Automated MRI analysis is a valid and efficient alternative to manual methods for assessing disuse muscle atrophy.
- Automated MRI offers a practical solution for clinical and research applications requiring muscle volume quantification.
