Canine body composition quantification using 3 tesla fat–water MRI

  • Aliya Gifford
    Vanderbilt University Institute of Imaging Science Vanderbilt University School of Medicine Nashville Tennessee USA
  • Joel Kullberg
    Department of Radiology Uppsala University Uppsala Sweden
  • Johan Berglund
    Department of Radiology Uppsala University Uppsala Sweden
  • Filip Malmberg
    Center for Image Analysis Uppsala University Uppsala Sweden
  • Katie C. Coate
    Department of Molecular Physiology and Biophysics Vanderbilt University School of Medicine Nashville Tennessee USA
  • Phillip E. Williams
    Department of Molecular Physiology and Biophysics Vanderbilt University School of Medicine Nashville Tennessee USA
  • Alan D. Cherrington
    Department of Molecular Physiology and Biophysics Vanderbilt University School of Medicine Nashville Tennessee USA
  • Malcolm J. Avison
    Vanderbilt University Institute of Imaging Science Vanderbilt University School of Medicine Nashville Tennessee USA
  • E. Brian Welch
    Vanderbilt University Institute of Imaging Science Vanderbilt University School of Medicine Nashville Tennessee USA

書誌事項

公開日
2013-04-17
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1002/jmri.24156
公開者
Wiley

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説明

<jats:sec><jats:title>Purpose</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Materials and Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>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. <jats:bold>J. Magn. Reson. Imaging 2014;39:485–491</jats:bold>. © <jats:bold>2013 Wiley Periodicals, Inc</jats:bold>.</jats:p></jats:sec>

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