Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography
Skeletal muscle size, mass, and composition are critical properties for studying metabolic and muscle-related diseases, as they directly impact the understanding of disease progression and treatment outcomes. Quantifying a live animal's lean, adipose, and skeletal mass is important in metabolic, physiology, pharmacologic, and geroscience studies. However, obtaining accurate body composition measurements, especially of lean mass, remains challenging due to the inherent limitations of conventional assessment techniques. Micro-computed tomography (micro-CT) is a non-invasive radiological technique that enables high-resolution visualization of internal structures in small animal models. A standardized micro-CT method can significantly enhance translational research with more reliable and impactful results, particularly during aging studies or at different time points within the same animal. Despite its potential, the lack of standardization in image acquisition and analysis methods significantly hinders the comparability of results across different studies. Herein, we present a comprehensive and detailed low-cost protocol for lean mass analysis using micro-CT to address these challenges and promote consistency in research involving small animal models.
Authors
- Flávia Fonseca Bloise (ORCID: https://orcid.org/0000-0002-5207-2896)
- Thamires Siqueira Oliveira (ORCID: https://orcid.org/0000-0002-8987-3822)
- Alexander Pereira-Rosa
- Rodrigo J Vianna-Barbosa
- Tula C Wilmart-Gonçalves
- Tânia M Ortiga
- Matheus S Ferreira
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Czech Academy of Sciences, Institute of Biophysics (CZ)
- National Institute of Science and Technology for Structural Biology and Bioimaging (BR)
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (BR)
Publication Details
- Journal
- Journal of Visualized Experiments
- Published
- 2024-11-08
- DOI
- https://doi.org/10.3791/67393
- Primary Topic
- Body Composition Measurement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00