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Objective To evaluate a novel technique designed to reduce the negative impact of motion artifacts in infant dual-energy X-ray absorptiometry (DXA) scans. Study design Using cross-sectional data from a large multicenter study, we developed and tested advanced methods for infant scan analysis. Newborns (n = 750) received spine and whole-body DXA scans with up to 3 attempts to acquire a motion free scan. Precision of infant DXA was estimated from visits with multiple valid scans. Accuracy of regional reflection, fusion, and omission techniques was estimated by comparing modified scans to unmodified valid scans. The effectiveness of the acquisition and analysis protocol was represented by the reduction in rate of failure to acquire valid results from infant visits. Results For infant whole-body DXA, arm reflection and all fusion techniques caused no significant changes to bone mineral content, bone mineral density, bone area, total mass, fat mass, lean mass, and percentage fat. Leg reflection and arm/leg dual-reflection caused significant changes to total mass, but the percentage change remained small. For infant spine DXA, fusion and omission caused no significant changes. Advanced analysis techniques reduced the failure rate of whole-body scanning from 20.8% to 9.3% and the failure rate of spine scanning from 8.9% to 2.4%. Conclusions Advanced analysis techniques significantly reduced the impact of motion artifacts on infant DXA scans. We suggest this protocol be used in future infant DXA research and clinical practice.

Background: Total body volume (TBV), with the exclusion of internal air voids, is necessary to quantify body composition in Lohman's 4-compartment (4C) model. Objective: This investigation sought to derive a novel, TBV measure with the use of only dual-energy X-ray absorptiometry (DXA) attenuation values for use in Lohman's 4C body composition model. Design: Pixel-specific masses and volumes were calculated from low- and high-energy attenuation values with the use of first principle conversions of mass attenuation coefficients. Pixel masses and volumes were summed to derive body mass and total body volume. As proof of concept, 11 participants were recruited to have 4C measures taken: DXA, air-displacement plethysmography (ADP), and total body water (TBW). TBV measures with the use of only DXA (DXA-volume) and ADP-volume measures were compared for each participant. To see how body composition estimates were affected by these 2 methods, we used Lohman's 4C model to quantify percentage fat measures for each participant and compared them with conventional DXA measures. Results: DXA-volume and ADP-volume measures were highly correlated (R2 = 0.99) and showed no statistically significant bias. Percentage fat by DXA volume was highly correlated with ADP-volume percentage fat measures and DXA software-reported percentage fat measures (R2 = 0.96 and R2 = 0.98, respectively) but were slightly biased. Conclusions: A novel method to calculate TBV with the use of a clinical DXA system was developed, compared against ADP as proof of principle, and used in Lohman's 4C body composition model. The DXA-volume approach eliminates many of the inherent inaccuracies associated with displacement measures for volume and, if validated in larger groups of participants, would simplify the acquisition of 4C body composition to a single DXA scan and TBW measure.

Few studies have described the long-term repeatability of dual-energy X-ray absorptiometry scans. Even fewer studies have been performed with enough participants to identify possible precision covariates such as sex, age, and body mass index (BMI). Our objective was to investigate the long-term repeatability of both total and subregional body composition measurements and their associations with covariates in a large sample. Two valid whole-body dual-energy X-ray absorptiometry scans were available for 609 participants in the National Health and Nutrition Examination Survey 2000–2002. Participants with scan-quality issues were excluded. Participants varied in race and ethnicity, sex, age (mean 38.8 ± 17.5; range 16–69 yr), and BMI (mean, 26.9 ± 5.2; range 14.1–43.5 kg/m 2 ). The length of time between scans ranged from 3 to 51 days (mean, 18.7 ± 8.4). Precision error estimates for total body measures (bone mineral density, bone mineral content, lean mass, total mass, fat mass, and percent body fat) were calculated as root mean square percent coefficients of variation and standard deviations. The average root mean square percent coefficients of variation and root mean square standard deviations of the precision error for total body variables were 1.12 and 0.01 g/cm 2 for bone mineral density, 1.14 and 27.3 g for bone mineral content, 1.97 and 505 g for fat mass, 1.46 and 760 g for lean mass, 1.10 and 858 g for total mass, and 1.80 and 0.59 for percent body fat. In general, only fat and lean masses were impacted by participant and scan qualities (obesity category, sex, the magnitude of the body composition variables, and time between scans). We conclude that long-term precision error values are impacted by BMI, and sex. Our long-term precision error estimates may be more suitable than short-term precision for calculating least significant change and monitoring time intervals.