Validation of dual-energy x-ray absorptiometry for determining in vivo body composition of chickens

Laboratory for Physiology and Immunology of Domestic Animals, Department of Animal Production, KU Leuven, Kasteelpark Arenberg, 30 3001 Leuven, Belgium.

The purpose of this study was to validate dual-energy x-ray absorptiometry (DXA) for measuring the body composition of chickens in vivo. Four trials were conducted with broiler chickens using a DXA instrument (Lunar, DPX-L) and small animal total body scan software (version 4.7a). In the first 2 trials, the effects of scan mode (high resolution or detail slow), scanning position (ventral or dorsal), and the use of attenuating materials (AM) (2-mm polyvinyl chloride or 4-mm polystyrene) on the precision and values of the DXA parameters body mass, lean tissue mass, fat tissue mass and percentage, bone mineral content (BMC), and bone mineral density (BMD) were evaluated. The precision was highest for body mass and lean tissue mass, followed by BMC and BMD, and was lowest for fat tissue mass and percentage. The precision of the measurements was not influenced by scan mode, position, or type of AM. In contrast, the values for all DXA parameters except body mass were significantly influenced by the scan mode but not by the position. The high resolution mode gave significantly higher estimates of fat mass and BMC but significantly lower measures of lean tissue mass and BMD compared with the detail slow mode. A significant difference between AM was only observed for the DXA estimates of fat tissue mass and fat percentage. In trial 3, the accuracy of the DXA measurements was tested by comparison with chemical body composition analysis. Linear regression equations between the respective DXA and chemical parameters were established. High correlations (r > 0.9; P < 0.0001) were obtained for all parameters, except for fat percentage (r = 0.593; P < 0.05). The purpose of the validation trial was to compare the predicted body composition based on the DXA measurements with established equations and the chemical body composition. There was extremely good agreement for body mass, lean tissue mass, and fat tissue mass and percentage, but not for ash weight. It is concluded that, after proper methodological standardization and application of specifically determined regression equations, DXA can be used for estimating the body composition of chickens in vivo. However, the regression equations are strictly limited to one particular instrument, software version, and applied methodology.

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