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Obes Rev. 2002 May;3(2):113-22.

Metabolically active components of fat-free mass and resting energy expenditure in humans: recent lessons from imaging technologies.

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Institut für Humanernährung und Lebensmittelkunde, Agrar- und Ernährungswissenschaftliche Fakultät, Christian-Albrechts-Universität zu Kiel, Düsternbrooker Weg 17-19, D-24105 Kiel, Germany.


Imaging technologies, i.e. magnetic resonance imaging (MRI), computer tomography (CT) and dual-energy X-ray absorptiometry (DEXA), are precise and accurate techniques used to study lean body mass and adipose tissue distribution. CT and MRI can also be used to assess metabolically active components of fat-free mass (FFM). (Throughout this article, metabolic activity is defined with respect to oxidative metabolism.) To date a total of 116 in vivo measurements of organ masses (OM), in combination with the measurement of resting energy expenditure (REE), have been reported. These data suggest that MRI- or CT-derived OM explains part (approximately 5-10%) of the interindividual variance in REE. The data also suggest that REE can be reconstructed from detailed body composition analysis. Calculating REE from the sum of individual OM multiplied by a constant organ tissue-respiration rate showed a high correlation between calculated and measured REE, with only small and non-significant differences of 83-96 kJ d-1. In addition to CT- and MRI-derived OM, data are available of 244 obese and non-obese subjects regarding the association between regional components of lean body mass (LBM, assessed by DEXA) and REE. These results suggest that measurement of LBM distribution also provides the opportunity to adjust for the non-linearity of REE on body mass. Assessment of metabolically active components of FFM or LBM may also add to our understanding of malnutrition-, obesity- and disease states-related variance in REE. There is need for (1) standardization of imaging technology in body composition research; (2) reference data on detailed body composition, also including more recent autopsy data; (3) reducing the number of assumptions in model-based predictions; and (4) a combination of imaging technologies with in vivo measurements of individual OM respiration.

[Indexed for MEDLINE]

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