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Imaging techniques for the assessment of body composition
M F Fuller1, P A Fowler, G McNeill
1Rowett Research Institute, Bucksburn, Aberdeen, U.K.
The Journal of Nutrition
|August 1, 1994
Summary
Body composition analysis in nutrition research is advancing with imaging techniques. While ultrasound imaging (UI) has limitations, computer-assisted axial tomography (CAT) and magnetic resonance imaging (MRI) show promise for assessing tissue and fat, despite challenges.
Area of Science:
- Medical imaging
- Nutrition research
- Body composition analysis
Background:
- Ultrasound imaging (UI), computer-assisted axial tomography (CAT), and magnetic resonance imaging (MRI) are established medical imaging modalities.
- Their utility in nutrition research for body composition assessment is an evolving area.
- While UI is inexpensive and safe, its image quality is suboptimal.
Purpose of the Study:
- To explore and compare the applications of UI, CAT, and MRI in body composition assessment for nutrition research.
- To evaluate the strengths and limitations of each imaging method for differentiating bone, muscle, and adipose tissue.
- To assess the feasibility and accuracy of these techniques for measuring subcutaneous and intra-abdominal adipose tissue.
Main Methods:
- Comparison of image quality, artifact prevalence, and tissue discrimination among UI, CAT, and MRI.
- Evaluation of measurement precision (CV) for tissue volumes using CAT and MRI.
- Validation of MRI for predicting total body lipid in animal models (pigs).
Main Results:
- CAT and MRI offer superior discrimination of bone, muscle, and adipose tissue compared to UI.
- MRI is more susceptible to movement artifacts than CAT due to longer scan times.
- CAT's X-ray exposure may limit its application in human nutrition studies.
- Both CAT and MRI demonstrate similar coefficients of variation for repeated tissue volume measurements.
- Measuring intra-abdominal adipose tissue poses greater challenges than subcutaneous adipose tissue with both CAT and MRI.
- MRI accurately predicted total body lipid in pigs (RSD of 1.9% with 13 slices).
Conclusions:
- CAT and MRI are promising for body composition analysis in nutrition research, offering better tissue differentiation than UI.
- Consideration of artifacts, radiation exposure (CAT), and measurement challenges (intra-abdominal fat) is crucial.
- Validation studies should integrate findings with simpler measures like age and weight for comprehensive assessment.