Abdominal volume computed tomography assessment of body composition in dogs

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Abstract

Background: Computed tomography (CT) has been used to estimate body composition and determine tissue distribution in dogs, despite limited validation. This may introduce error into estimates of body composition studies and its effect on health in dogs. Further, the modality has not been validated against dual-energy X-ray absorptiometry (DXA) or over a wide range of dog breeds, ages and sexes. The objective of this study was to validate the use of semi-automated, abdominal volume CT for estimating total body composition of dogs relative to DXA. Twenty-two staff-owned dogs (weighing between 5.1-60 kg) were sedated and underwent full body DXA scan and abdominal CT. Abdominal tissue composition was estimated by CT using semi-automated volume segmentation, over predetermined tissue Hounsfield threshold values. Abdominal tissue composition determined by the various CT threshold ranges was compared to total body composition determined by DXA. Results: Abdominal tissue composition estimated by CT strongly correlated with the estimates derived from DXA with a small Bland-Altman mean percentage differences in values: total body mass (- 250/2000HU: r2 = 0.985; - 1.10%); total fat mass (- 250/-25HU: r2 = 0.981; - 1.90%); total lean tissue mass (- 25/150HU: r2 = 0.972; 3.47%); and total bone mineral content (150/2000HU: r2 = 0.900; - 0.87%). Although averaged CT values compared well to DXA analysis, there was moderate variation in the individual predicted values. There was near perfect inter- and intra-observer agreement in segmentation volumes for abdominal fat. Conclusions: Abdominal volume computed tomography (CT) accurately and reliably estimates total body composition in dogs, but greater variations may be observed in dogs weighing less than 10 kg.

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Turner, R. B. S., Hepworth, G., Wilson, K., Tyrrell, D., Dunshea, F. R., & Mansfield, C. S. (2019). Abdominal volume computed tomography assessment of body composition in dogs. BMC Veterinary Research, 15(1). https://doi.org/10.1186/s12917-018-1768-6

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