Cross Calibration of the GE Prodigy and iDXA for the Measurement of Total and Regional Body Composition in Adults

WHAM-A Prospective Study of Weight and Body Composition After Risk-Reducing Bilateral Salpingo-oophorectomy

CONTEXT

Body weight and composition may change over the natural menopause transition. Whether surgical menopause has similar effects, and the impact of hormone replacement therapy (HRT), are unknown. Understanding the metabolic effects of surgical menopause will inform clinical care.

OBJECTIVE

To prospectively measure weight and body composition over 24 months following surgical menopause compared with a similar comparison group who retained their ovaries.

METHODS

Prospective observational study of weight change from baseline to 24 months in 95 premenopausal women at elevated risk of ovarian cancer planning risk-reducing salpingo-oophorectomy (RRSO) and 99 comparators who retained their ovaries. Change in body composition from baseline to 24 months was also assessed by dual-energy x-ray absorptiometry in a subgroup of 54 women who underwent RRSO and 81 comparators who retained their ovaries. In the subgroup, weight, fat mass, lean mass, and abdominal fat measures were compared between groups.

RESULTS

At 24 months both groups had gained weight (RRSO 2760 ± 4860 g vs comparators 1620 ± 4540 g) with no difference between groups (mean difference 730 g; 95% CI 920 g to 2380 g; P = .383). In the body composition subgroup, there was no difference in weight between groups at 24 months (mean difference 944 g; 95% CI -1120 g to 2614 g; P = .431). RRSO women may have gained slightly more abdominal visceral adipose tissue (mean difference 99.0 g; 95% CI 8.8 g to 189.2 g; P = .032) but there were no other differences in body composition. There were also no differences in weight or body composition between HRT users and nonusers at 24 months.

CONCLUSION

24 months after RRSO, there was no difference in body weight compared with women who retained their ovaries. RRSO women gained more abdominal visceral adipose tissue than comparators, but there were no other differences in body composition. Use of HRT following RRSO had no effect on these outcomes.

Cross-Calibration of iDXA and pQCT Scanners at Rural and Urban Research Sites in The Gambia, West Africa

Between-scanner differences in measures of bone and body composition can obscure or exaggerate physiological differences in multi-site studies or the magnitude of changes in longitudinal studies. We conducted a cross-calibration study at two bone imaging centres in The Gambia, West Africa where DXA (dual-energy X-ray absorptiometry) and pQCT (peripheral Quantitative-Computed Tomography) are routinely used. Repeat scans were obtained from 64 Gambian adults (58% Male) aged Mean(SD) 30.9 (13.5) years with Mean(SD) body mass index (BMI) 21.7 (4.0) kg/m², using DXA (GE Lunar iDXA, whole body [WB], total hip [TH], lumbar spine [LS]) and pQCT (Stratec XCT2000L/XCT2000, tibia 4%, 50% sites). Between-scanner differences were tested using paired t tests (p < 0.05). Between-scanner correlation was explored with linear regression, and cross-calibration equations derived. Bland-Altman analysis investigated machine trend/bias. When differences were detected (p < 0.05), cross-calibration equations were applied to urban values, with t tests and Bland Altman analysis repeated. Between-scanner differences exceeded the predefined level of statistical significance (p < 0.05) for WB aBMD and BA; all pQCT measures vBMD, BMC, cortical cross-sectional area (CSA) and stress-strain index (SSI). Between-scanner correlation was high (R²:0.92-0.99), except pQCT Mu.Den (R² = 0.51). Bland Altman plots indicated bias increased with increasing BMD. Cross-calibration equations attenuated all between-scanner differences and systematic bias. Cross-calibration, particularly of pQCT scanners, is an important consideration in multi-site studies particularly where between population comparisons are intended. Our experiences and findings may be generalisable to other resource-limited settings where the logistics of sourcing parts and in-country repair may result in lengthy scanner downtime.

Cross-calibration of two dual-energy X-ray absorptiometry devices for the measurement of body composition in young children

This study aimed to cross-calibrate body composition measures from the GE Lunar Prodigy and GE Lunar iDXA in a cohort of young children. 28 children (mean age 3.4 years) were measured on the iDXA followed by the Prodigy. Prodigy scans were subsequently reanalysed using enCORE v17 enhanced analysis ("Prodigy enhanced"). Body composition parameters were compared across three evaluation methods (Prodigy, Prodigy enhanced, iDXA), and adjustment equations were developed. There were differences in the three evaluation methods for all body composition parameters. Body fat percentage (%BF) from the iDXA was approximately 1.5-fold greater than the Prodigy, whereas bone mineral density (BMD) was approximately 20% lower. Reanalysis of Prodigy scans with enhanced software attenuated these differences (%BF: - 5.2% [95% CI - 3.5, - 6.8]; and BMD: 1.0% [95% CI 0.0, 1.9]), although significant differences remained for all parameters except total body less head (TBLH) total mass and TBLH BMD, and some regional estimates. There were large differences between the Prodigy and iDXA, with these differences related both to scan resolution and software. Reanalysis of Prodigy scans with enhanced analysis resulted in body composition values much closer to those obtained on the iDXA, although differences remained. As manufacturers update models and software, researchers and clinicians need to be aware of the impact this may have on the longitudinal assessment of body composition, as results may not be comparable across devices and software versions.

Comparison of Two DXA Systems, Hologic Horizon W and GE Lunar Prodigy, for Assessing Body Composition in Healthy Korean Adults

BACKGROUND

Dual-energy X-ray absorptiometry (DXA) is the most widely used method for evaluating muscle masses. The aim of this study was to investigate the agreement between muscle mass values assessed by two different DXA systems.

METHODS

Forty healthy participants (20 men, 20 women; age range, 23 to 71 years) were enrolled. Total and regional body compositional values for fat and lean masses were measured consecutively with two DXA machines, Hologic Horizon and GE Lunar Prodigy. Appendicular lean mass (ALM) was calculated as the sum of the lean mass of four limbs.

RESULTS

In both sexes, the ALM values measured by the GE Lunar Prodigy (24.8±4.3 kg in men, 15.8±2.9 kg in women) were significantly higher than those assessed by Hologic Horizon (23.0±4.0 kg in men, 14.8±3.2 kg in women). Furthermore, BMI values or body fat (%), either extremely higher or lower levels, contributed greater differences between two systems. Bland-Altman analyses revealed a significant bias between ALM values assessed by the two systems. Linear regression analyses were performed to develop equations to adjust for systematic differences (men: Horizon ALM [kg]=0.915×Lunar Prodigy ALM [kg]+0.322, R2=0.956; women: Horizon ALM [kg]=1.066×Lunar Prodigy ALM [kg]-2.064, R2=0.952).

CONCLUSION

Although measurements of body composition including muscle mass by the two DXA systems correlated strongly, significant differences were observed. Calibration equations should enable mutual conversion between different DXA systems.

Cross-Calibration of Bone Mineral Densities and Body Composition between GE Lunar Prodigy and Osteosys Primus

Background

The aim of this study was to investigate the correlation between bone mineral density (BMD) and body composition measured by the Osteosys Primus^® and the GE Lunar Prodigy^® and to calculate the conversion rate between the 2 devices.

Methods

The 40 subjects were men and women in aged 20 to 29 years old. All participants were scanned twice on both the Osteosys Primus (OsteoSys) and the GE Lunar Prodigy (GE Healthcare) DXA systems using the manufacturers’ standard scanning and positioning protocols.

Results

Compared to the GE Lunar device, the mean Osteosys fat mass was overestimated to be 12.1% (1,776.9 g) in the whole body, 5.1% (163.9 g) in gynoid, and 6.7% (87.2 g) in android. Compared with the GE Lunar device, the mean BMDs of the Osteosys Primus were underestimated to be 2.3% (0.023 g/cm²) in the whole body and 3.1% (0.035 g/cm²) in L1-4. Compared with the GE Lunar device, the mean lean mass derived by the Osteosys Primus were underestimated to 2.3% (1,045.3 g) in the total body, 3.8% (179.4 g) in arms, and 7.7% (1,104.8 g) in legs, respectively. There were a strong correlation of BMD and body composition between both groups.

Conclusions

Linear correction equations were developed to ensure comparability of BMD and muscle mass between the Osteosys Primus and the GE Lunar Prodigy. Importantly, use of equations from previous studies would have increased the discrepancy between the Osteosys Primus and the GE Lunar Prodigy.

Explaining Discrepancies Between Total and Segmental DXA and BIA Body Composition Estimates Using Bayesian Regression

INTRODUCTION/BACKGROUND

Few investigations have sought to explain discrepancies between dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) body composition estimates. The purpose of this analysis was to explore physiological and anthropometric predictors of discrepancies between DXA and BIA total and segmental body composition estimates.

METHODOLOGY

Assessments via DXA (GE Lunar Prodigy) and single-frequency BIA (RJL Systems Quantum V) were performed in 179 adults (103 F, 76 M, age: 33.6 ± 15.3 yr; BMI: 24.9 ± 4.3 kg/m²). Potential predictor variables for differences between DXA and BIA total and segmental fat mass (FM) and lean soft tissue (LST) estimates were obtained from demographics and laboratory techniques, including DXA, BIA, bioimpedance spectroscopy, air displacement plethysmography, and 3-dimensional optical scanning. To determine meaningful predictors, Bayesian robust regression models were fit using a t-distribution and regularized hierarchical shrinkage "horseshoe" prior. Standardized model coefficients (β) were generated, and leave-one-out cross validation was used to assess model predictive performance.

RESULTS

LST hydration (i.e., total body water:LST) was a predictor of discrepancies in all FM and LST variables (|β|: 0.20-0.82). Additionally, extracellular fluid percentage was a predictor for nearly all outcomes (|β|: 0.19-0.40). Height influenced the agreement between whole-body estimates (|β|: 0.74-0.77), while the mass, length, and composition of body segments were predictors for segmental LST estimates (|β|: 0.23-3.04). Predictors of segmental FM errors were less consistent. Select sex-, race-, or age-based differences between methods were observed. The accuracy of whole-body models was superior to segmental models (leave-one-out cross-validation-adjusted R² of 0.83-0.85 for FM_TOTAL and LST_TOTAL vs. 0.20-0.76 for segmental estimates). For segmental models, predictive performance decreased in the order of: appendicular lean soft tissue, LST_LEGS, LST_TRUNK and FM_LEGS, FM_ARMS, FM_TRUNK, and LST_ARMS.

CONCLUSIONS

These findings indicate the importance of LST hydration, extracellular fluid content, and height for explaining discrepancies between DXA and BIA body composition estimates. These general findings and quantitative interpretation based on the presented data allow for a better understanding of sources of error between 2 popular segmental body composition techniques and facilitate interpretation of estimates from these technologies.

The comparative measurement of body segment parameters using dual energy X-ray absorptiometry between sexes

OBJECTIVE

The study aimed to determine the proportion of the body segments in relation to the total body mass in healthy people, as well as analyze the composition of each segment and compare these results between sexes.

METHODS

A total of 60 young adults (30 men and 30 women) were subjected to a full-body scan by dual energy Xrays absorptiometry (DXA) under standardized conditions. The regions of interest (ROI) were determined by a single trained evaluator. The body was divided into 16 segments to obtain values of total mass, lean mass (LM), fat mass, bone mineral content (BMC), lean mass percentage (%LM) and fat mass percentage (%FM) of each body segment represented by the 16 ROI.

RESULTS

Men presented higher absolute mass in the upper limbs (Δ= 32.87%; p <0.05). The proportion of the lower limbs (Δ= 6.83%; p<0.05) and trunk (Δ= 5.07%; p <0.05) of men is higher than women. In addition, males have more LM in the upper limbs (Δ= 42.19%; p<0.05) and trunk (Δ= 26.46%; p<0.001) and more BMC in the trunk (Δ= 18.78%; p<0.05) and forearms (Δ= 32.21%; p<0.05). They also present higher %LM (Δ= 6.48%; p<0.001) and lower %FM (Δ= 54.43%; p<0.001) than women in the forearms.

CONCLUSIONS

The different body segments represent a different percentage of the total body mass in men than in women, as well as, men present more LM and BMC in the trunk and upper limbs.

The Potential Role of Fish-Derived Protein Hydrolysates on Metabolic Health, Skeletal Muscle Mass and Function in Ageing

Fish protein represents one of the most widely consumed dietary protein sources by humans. The processing of material from the fishing industry generates substantial unexploited waste products, many of which possess high biological value. Protein hydrolysates, such as fish protein hydrolysates (FPH), containing predominantly di- and tripeptides, are more readily absorbed than free amino acids and intact protein. Furthermore, in animal models, FPH have been shown to possess numerous beneficial properties for cardiovascular, neurological, intestinal, renal, and immune health. Ageing is associated with the loss of skeletal muscle mass and function, as well as increased oxidative stress, compromised vascularisation, neurological derangements, and immunosenescence. Thus, there appears to be a potential application for FPH in older persons as a high-quality protein source that may also confer additional health benefits. Despite this, there remains a dearth of information concerning the impact of FPH on health outcomes in humans. The limited evidence from human interventional trials suggests that FPH may hold promise for supporting optimal body composition and maintaining gut integrity. FPH also provide a high-quality source of dietary protein without negatively impacting on subjective appetite perceptions or regulatory hormones. Further studies are needed to assess the impact and utility of FPH on skeletal muscle health in older persons, ideally comparing FPH to ‘established’ protein sources or a non-bioactive, nitrogen-matched control. In particular, the effects of acute and chronic FPH consumption on post-exercise aminoacidaemia, skeletal muscle protein synthesis, and intramyocellular anabolic signalling in older adults are worthy of investigation. FPH may represent beneficial and sustainable alternative sources of high-quality protein to support skeletal muscle health and anabolism in ageing, without compromising appetite and subsequent energy intake.