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Body composition (BC) measured by DXA differs between devices. We aimed to compare regional and total BC measurements assessed by the Hologic Horizon A and the GE Lunar iDXA devices; to determine device-specific calibration equations for each BC parameter; and to assess the impact of this standardization procedure on the assessment of sarcopenia, lipedema, obesity, and cardiovascular risk with DXA. A total of 926 postmenopausal women (aged 72.9 ± 6.9 yr, height 160.3 ± 6.6 cm, weight 66.1 ± 12.7 kg) underwent BC assessment on each device within 1 h, following the ISCD guidelines. The included sample was split into 80% train and 20% test datasets stratified by age, height, and weight. Inter-device differences in BC parameters were assessed with Bland-Altman analysis, Pearson or Spearman correlation coefficients, and t-tests or Wilcoxon tests. The equations were developed in the train dataset using backward stepwise multiple linear regressions and were evaluated in the test dataset with the R-squared and mean absolute error. We compared the abovementioned BC-derived health conditions before and after standardization in the test set with respect to relative risk, accuracy, Kappa score, and McNemar tests. Total and regional body masses were similar (p>.05) between devices. BMC was greater for all regions in the Lunar device (p<.05), while fat and lean masses differed among regions. Regression equations showed high performance metrics in both datasets. The BC assessment from Hologic classified 2.13 times more sarcopenic cases (McNemar: p<.001), 1.39 times more lipedema (p<.001), 0.40 times less high cardiovascular risk (p<.001), and similarly classified obesity (p>.05), compared to Lunar. After standardization, the differences disappeared (p>.05), and the classification metrics improved. This study discusses how hardware and software differences impact BC assessments. The provided standardization equations address these issues and improve the agreement between devices. Future studies and disease definitions should consider these differences.
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INTRODUCTION: Lipedema is a poorly known condition. Diagnosis is based almost exclusively on clinical criteria, which may be subjective and not always reliable. This study aimed to investigate regional body composition (BC) by dual-energy X-ray absorptiometry (DXA) in patients with lipedema and healthy controls and to determine cut-off values of fat mass (FM) indices to provide an additional tool for the diagnosis and staging of this condition. METHODS: This study is a single-center case-control study performed at Lausanne University Hospital, Switzerland. Women with clinically diagnosed lipedema underwent regional BC assessment by DXA. The control group without clinical lipedema was matched for age and body mass index (BMI) at a ratio of 1:2 and underwent similar examination. Regional FM (legs, arms, legs and arms, trunk, android and gynoid FM) was measured in (kg) and divided by FM index (FMI) (kg/m2) and total FM (kg). The trunk/legs and android/gynoid ratios were calculated. For all indices of FM distribution showing a significant difference between cases and controls, we defined the receiver operating characteristic (ROC) curves, calculating the area under the curve (AUC), sensitivity, specificity, and Youden's index. Types and stages of lipedema were compared in terms of FM indices. Correlation analyses between all FM distribution indices and lipedema stages were performed. RESULTS: We included 222 women (74 with lipedema and 148 controls). Overall, the mean age was 41 years (standard deviation [SD] 11), and mean BMI was 30.9 kg/m2 (SD 7.6). A statistically significant difference was observed for all DXA-derived indices of FM distribution between groups, except for arm FM indices. The ROC curve analysis of leg FM/total FM, as a potential indicator of lipedema, resulted in an AUC of 0.90 (95% confidence interval 0.86-0.94). According to Youden's index, optimal cut-off value identifying lipedema was 0.384. Sensitivity and specificity were 0.95 and 0.73, respectively. We found no significant differences between lipedema types and stages in terms of FM indices, nor significant correlations between the latter and lipedema stages. DISCUSSION/CONCLUSION: BC assessment by DXA, and particularly calculation of the leg FM/total FM index, is a simple tool that may help clinicians rule out lipedema in doubtful cases.
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