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Title: Whole Body Computed Tomography with Advanced Imaging Techniques: A Research Tool for Measuring Body Composition in Dogs
Contributor(s): Purushothaman, Dharma (author); Vanselow, Barbara  (author); Wu, Shubiao  (author)orcid ; Butler, Sarah (author); Brown, Wendy  (author)orcid 
Publication Date: 2013
Open Access: Yes
DOI: 10.1155/2013/610654Open Access Link
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Abstract: 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 (P < 0.01). 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.
Publication Type: Journal Article
Source of Publication: Journal of Veterinary Medicine, v.2013, p. 1-6
Publisher: Hindawi Publishing Corporation
Place of Publication: United States of America
ISSN: 2314-6966
Fields of Research (FoR) 2008: 070799 Veterinary Sciences not elsewhere classified
070702 Veterinary Anatomy and Physiology
Fields of Research (FoR) 2020: 300999 Veterinary sciences not elsewhere classified
300902 Veterinary anatomy and physiology
Socio-Economic Objective (SEO) 2008: 920411 Nutrition
Socio-Economic Objective (SEO) 2020: 200410 Nutrition
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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