Volume 57 Supplement 1
In vivo assessment of dog subcutaneous fat depots by real time ultrasonography and image analysis
© Payan-Carreira et al. 2015
Published: 25 September 2015
Obesity is the most common nutritional disorder in dogs and a main health and welfare concern worldwide; it links to a shortened lifespan and increased rate of secondary diseases. Surveillance of dog adiposity is a routine practice and is often estimated from body condition scoring (BCS). But BCS is subjective and fairly sensitive, reducing its utility during weight-loss plans. Substitute approaches, simple, cheap and reproducible, are foreseen.
This work aimed to assess real time ultrasonography (RTU) usefulness for analysis of sub-cutaneous body fat depots (SCF) in dogs.
Twenty-eight dogs were enrolled, representing different sizes (nain-4; small-10; medium-14), weights (BW; 5.2–33.0 kg) and BCS (2-4 in a 5 points scale). RTU images were taken with a multifrequency linear array (at 10 MHz) coupled to a GE scanner, from non-sedated dogs in right lateral recumbency, at five anatomical points: entry of the chest; over the ninth intercostal space; lateral abdominal wall; right inner thigh; and between the third and the fifth lumbar vertebrae. Images were analysed in Image J; means from 3-different locations per image were used to set SCF thickness. Using the JMP program correlation procedure was used to analyse SCF and BCS relationships.
BW was poorly associated with SCF thickness (r between 0.21, p>0.05, and 0.59, p<0.01), while BCS and SCF were strongly correlated (r between 0.71 and 0.82; p<0.01), particularly for data collected at lumbar and abdominal points.
Results stress that BW is a poor adiposity predictor and suggest that RTU is a valuable tool to predict dog adiposity.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.