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Journal of Veterinary Medicine
Volume 2013 (2013), Article ID 610654, 6 pages
Research Article

Whole Body Computed Tomography with Advanced Imaging Techniques: A Research Tool for Measuring Body Composition in Dogs

1School of Environmental and Rural Science, Department of Animal Science, University of New England, Armidale, NSW 2351, Australia
2NSW Department of Primary Industries, Beef Industry Centre, University of New England, Armidale, NSW 2351, Australia
3North Hill Vet Clinic, Armidale, NSW 2350, Australia

Received 6 May 2013; Revised 14 September 2013; Accepted 17 September 2013

Academic Editor: Juan G. Chediack

Copyright © 2013 Dharma Purushothaman et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The use of computed tomography (CT) to evaluate obesity in canines is limited. Traditional CT image analysis is cumbersome and uses prediction equations that require manual calculations. In order to overcome this, our study investigated the use of advanced image analysis software programs to determine body composition in dogs with an application to canine obesity research. Beagles and greyhounds were chosen for their differences in morphology and propensity to obesity. Whole body CT scans with regular intervals were performed on six beagles and six greyhounds that were subjected to a 28-day weight-gain protocol. The CT images obtained at days 0 and 28 were analyzed using software programs OsiriX, ImageJ, and AutoCAT. The CT scanning technique was able to differentiate bone, lean, and fat tissue in dogs and proved sensitive enough to detect increases in both lean and fat during weight gain over a short period. A significant difference in lean : fat ratio was observed between the two breeds on both days 0 and 28 (). Therefore, CT and advanced image analysis proved useful in the current study for the estimation of body composition in dogs and has the potential to be used in canine obesity research.