Canine body composition quantification using 3 tesla fat-water MRI.
J Magn Reson Imaging
; 39(2): 485-91, 2014 Feb.
Article
em En
| MEDLINE
| ID: mdl-23596090
PURPOSE: To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean, and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet. MATERIALS AND METHODS: Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities. RESULTS: FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and -2.23 kg, respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue. CONCLUSION: FWMRI can precisely quantify and map body composition with respect to adipose, lean, and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.
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Base de dados:
MEDLINE
Assunto principal:
Água Corporal
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
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Tecido Adiposo
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Imageamento Tridimensional
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Imagem Corporal Total
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Distribuição da Gordura Corporal
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article