In vivo measurement of human body composition by dual-energy X-ray absorptiometry (DXA)

2003 ◽  
Vol 164 (2) ◽  
pp. 133-137 ◽  
Author(s):  
Troels K. Thomsen ◽  
Vagn J. Jensen ◽  
Morten G. Henriksen
Keyword(s):  
Body Composition ◽  
Human Body ◽  
Dual Energy ◽  
X Ray ◽  
In Vivo Measurement ◽  
Human Body Composition

In vivo assessment of body composition and growth potential of modern broiler using dual-energy X-ray absorptiometry

2020 ◽  
Vol 60 (16) ◽  
pp. 1959
Author(s):  
Camila Angelica Gonçalves ◽  
Nilva Kazue Sakomura ◽  
Miryelle Freire Sarcinelli ◽  
Letícia Graziele Pacheco ◽  
Letícia Soares ◽  
...  
Keyword(s):  
Body Composition ◽  
Growth Rates ◽  
Dual Energy ◽  
The Body ◽  
Growth Potential ◽  
Chemical Components ◽  
Potential Growth ◽  
X Ray ◽  
Growing Period

Context Genetic improvements in modern strains have led to continuous increments in broiler growth rates, which, as a consequence, have resulted in higher economic returns for broiler producers over the last decades. Aim The present study was conducted to characterise the potential growth of the body and feathers of Cobb 500, Hubbard Flex and Ross 308 male and female broilers, as well as to assess the changes in chemical composition that occur up to 16 weeks of age. Methods Birds were fed isoenergetic diets divided in four phases and formulated to marginally exceed the nutritional requirements of the strains throughout the growing period. They were maintained in a controlled environment so as not to limit growth. A dual energy X-ray absorptiometry (DXA) scanner was used to follow the in vivo body composition of 12 broilers of each strain and sex (total of 72 broilers), and the feather weight and composition was determined in four birds of each strain and sex selected at intervals during the growing period (total of 288 broilers) through comparative slaughter with later chemical analysis. Key results Parameters of Gompertz growth curve to describe the strains were estimated for body and feather weight as well as for the growth of their chemical components. Conclusion Differences in the growth rates between strains were evident, indicating the possible differences in selection methods used by geneticists in the different breeding companies. These genetic parameters would explain part of the variation on broiler´s performance which impacts on the way they should be fed and housed during growth. Implications The accurate description of genetic growth potential is useful information to be associated with factorial models that predict nutritional and feed intake requirements of birds. The main advantage of DXA technology is to decrease the variation of body deposition on the Gompertz model, resulting from the use of the same bird throughout its life. Despite the speed of obtaining chemical values of the body, the method is unsuitable for measuring the growth of feathers, which is also important data to be collected and related to the broiler strains.

scholarly journals Comparison of in-vivo body composition using two Lunar dual-energy X-ray absorptiometers

1998 ◽  
Vol 52 (3) ◽  
pp. 180-185 ◽  
Author(s):  
B Oldroyd ◽  
JG Truscott ◽  
G Woodrow ◽  
R Milner ◽  
SP Stewart ◽  
...  
Keyword(s):  
Body Composition ◽  
Dual Energy ◽  
X Ray

scholarly journals Comparison of a GE Lunar DPX-IQ and a Norland XR-26 dual energy X-ray absorptiometry scanner for body composition measurements in pigs – <i>in vivo</i>

2010 ◽  
Vol 53 (2) ◽  
pp. 162-175 ◽  
Author(s):  
D. Lösel ◽  
P. Kremer ◽  
E. Albrecht ◽  
A. M. Scholz
Keyword(s):  
Body Composition ◽  
Bone Mineral ◽  
Performance Testing ◽  
Dual Energy ◽  
The Body ◽  
Fat Percentage ◽  
Mineral Density ◽  
X Ray ◽  
And Performance

Abstract. In the context of future growth and performance testing, this study compares corresponding body composition results measured by two dual energy X-ray absorptiometry systems. To test the capability of each device to detect differences among experimental groups widely varying in body composition, 77 pigs from 6 purebred/crossbred groups were used for the experiment. Each pig was scanned consecutively on a Norland XR-26 and on a GE Lunar DPX-IQ. Coefficients of determination were: R²=0.92 for bone mineral content (BMC), R²=0.90 for bone mineral density (BMD), R²=0.94 for lean mass (LEAN), R²=0.92 for fat mass (FAT), R²=0.88 for lean percentage (%LEAN) and fat percentage (%FAT). However, Norland yielded larger values for %FAT and smaller values for %LEAN, BMC, and BMD than Lunar (P<0.001) with the extent of deviation depending on the specific trait and on the breeding group. The deviation in BMC was greater than the deviation in BMD, suggesting different bone detecting algorithms. Both systems revealed similar differences among the breeding groups, and ranked them in the same order based on numerical values. Differences in calibration, bone detection, and software algorithms, however, require a prior crosscalibration to make the body composition data from both systems directly comparable. Finally, they can be used across research centres for the determination of relative and absolute body composition differences among animal groups and individuals.

Human Body Composition: In Vivo Methods

2000 ◽  
Vol 80 (2) ◽  
pp. 649-680 ◽  
Author(s):  
Kenneth J. Ellis
Keyword(s):  
Body Composition ◽  
Human Body ◽  
Bioelectrical Impedance ◽  
Point Of View ◽  
Whole Body ◽  
Physiological Basis ◽  
Adolescents And Adults ◽  
Body Counting ◽  
Human Body Composition

In vivo methods used to study human body composition continue to be developed, along with more advanced reference models that utilize the information obtained with these technologies. Some methods are well established, with a strong physiological basis for their measurement, whereas others are much more indirect. This review has been structured from the methodological point of view to help the reader understand what can be examined with each technique. The associations between the various in vivo methods (densitometry, dilution, bioelectrical impedance and conductance, whole body counting, neutron activation, X-ray absorptiometry, computer tomography, and magnetic resonance imaging) and the five-level multicompartment model of body composition are described, along with the limitations and advantages of each method. This review also provides an overview of the present status of this field of research in human biology, including examples of reference body composition data for infants, children, adolescents, and adults.

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