Hip structural analysis (HSA) of proximal femur scans by dual energy X-ray absorptiometry estimates hip geometry and structural strength, but little is known about how these parameters change during peak bone mass development. We describe age-related changes, precision and long-term stability, and sex and race/ethnic identity differences in hip geometry measures by HSA, and test whether HSA measures predict childhood fractures in healthy children. We used data from the Bone Mineral Density in Childhood Study, a multi-center, longitudinal cohort study of 2,014 healthy U.S. children, ages 5-23y, with up to 7 annual visits. HSA measures included cortical thickness, cross-sectional area, cross-sectional moment of inertia, section modulus, buckling ratio, and bone width at the narrow neck and femoral shaft, and hip axis length. Additional measures included self-identified race and ethnicity, Z-scores for height, BMIZ, appendicular lean soft tissue mass index and fat mass index, and self-reported physical activity, calcium intake, Tanner stage and fractures. Results indicated age-related trends and sex differences in hip geometry. Reference ranges were generated and HSA Z-scores were adjusted for height-for-age Z-score. Femoral shaft measures showed better precision (CV: 1.1 to 3.7%) than narrow neck measures (CV: 2.2 to 7.4%); buckling ratio (both sites) was the least precise. HSA Z-scores tracked well over one year (0.77 to 0.94). Narrow neck buckling ratio (HR 1.16 [95% CI: 1.02, 1.31]) and hip axis length Z-scores (HR 1.20 [95% CI: 1.00, 1.44]) associated with fracture risk. When adjusted for covariates (BMD Z-score, BMIZ, Tanner stage, sex), narrow neck cross-sectional area, cross-sectional moment of inertia, section modulus and bone width, and femoral shaft cross-sectional area and section modulus Z-scores positively associated with fractures (e.g., section modulus Z-score associated with 44% increased fracture risk). These findings provide the foundation for evaluating hip geometry as an indicator of bone strength in children.

Muscle mass and strength are crucial for physiological function and performance in athletes, playing a significant role in maintaining health and optimal athletic performance. Skeletal muscle, which constitutes the majority of lean soft tissue (LST) and appendicular lean soft tissue (ALST) when measured by dual-energy X-ray absorptiometry (DXA), represents a commonly used surrogate for strength. Research has investigated alternative measures of body composition, such as the assessment of ALST through bioelectrical impedance analysis (BIA) and the determination of whole-body muscle mass from creatine pool size using the deuterated creatine (D3Cr) dilution method, for their associations to strength. While the relationship between body composition measures and strength has been studied in older adults, this relationship remains unexplored in athletic populations. This study examined muscle body composition measures using DXA, D3Cr, and BIA and their association with strength in a sample of collegiate athletes. The study enrolled 80 collegiate athletes (40 females) of differing sports disciplines who consumed a 60 mg dose of D3Cr and completed DXA and BIA measures in addition to trunk and leg strength tests. Analysis was sex-stratified using Pearson’s correlations, linear regression, and quartile p trend significance. With an average participant age of 21.8 years, whole-body DXA correlations to muscle strength surpassed height- or mass-normalized values. This trend was especially pronounced in trunk strength’s relationship with body composition over leg strength, across measurement methods. While DXA LST values were higher than BIA and D3Cr in predicting strength, the values did not differ significantly. Adjustments for age, BMI, and BIA variables didn’t enhance this association. A significant trend between DXA LST and all strength measures underscored the equal relevance of DXA and D3Cr muscle mass to strength, favoring whole-body over regional assessments. This calls for future research on muscle mass’s effects on LST and functional outcomes in broader groups, highlighting the importance of comprehensive body composition analysis in athletic performance studies.

Total-body dual X-ray absorptiometry (TBDXA) imaging is a relatively low-cost whole-body imaging modality, widely used for body composition assessment. We develop and validate a deep learning method for automatic fiducial point placement on TBDXA scans using 1,683 manually-annotated TBDXA scans. The method achieves 99.5 https://github.com/hawaii-ai/dxa-pointplacement .

Background Body shape, an intuitive health indicator, is deterministically driven by body composition. We developed and validated a deep learning model that generates accurate dual-energy X-ray absorptiometry (DXA) scans from three-dimensional optical body scans (3DO), enabling compositional analysis of the whole body and specified subregions. Previous works on generative medical imaging models lack quantitative validation and only report quality metrics. Methods Our model was self-supervised pretrained on two large clinical DXA datasets and fine-tuned using the Shape Up! Adults study dataset. Model-predicted scans from a holdout test set were evaluated using clinical commercial DXA software for compositional accuracy. Results Predicted DXA scans achieve R 2 of 0.73, 0.89, and 0.99 and RMSEs of 5.32, 6.56, and 4.15 kg for total fat mass (FM), fat-free mass (FFM), and total mass, respectively. Custom subregion analysis results in R 2 s of 0.70–0.89 for left and right thigh composition. We demonstrate the ability of models to produce quantitatively accurate visualizations of soft tissue and bone, confirming a strong relationship between body shape and composition. Conclusions This work highlights the potential of generative models in medical imaging and reinforces the importance of quantitative validation for assessing their clinical utility.

Background and aims: Body fat distribution, i.e., visceral (VAT), subcutaneous adipose tissue (SAT) and intramuscular fat, is important for disease prevention, but sex and ethnic differences are not well understood. Our aim was to identify anthropometric, demographic, and lifestyle predictors for these outcomes. Methods and results: The cross-sectional ShapeUp!Kids study was conducted among five ethnic groups aged 5-18 years. All participants completed questionnaires, anthropometric measurements, and abdominal MRI scans. VAT and SAT areas at four lumbar levels and muscle density were assessed manually. General linear models were applied to estimate coefficients of determination (R2) and to compare the fit of VAT and SAT prediction models. After exclusions, the study population had 133 male and 170 female participants. Girls had higher BMI-z scores, waist circumference (WC), and SAT than boys but lower VAT/SAT and muscle density. SAT, VAT, and VAT/SAT but not muscle density differed significantly by ethnicity. R2 values were higher for SAT than VAT across groups and improved slightly after adding WC. For SAT, R2 increased from 0.85 to 0.88 (girls) and 0.62 to 0.71 (boys) when WC was added while VAT models improved from 0.62 to 0.65 (girls) and 0.57 to 0.62 (boys). VAT values were significantly lower among Blacks than Whites with little difference for the other groups. Conclusion: This analysis in a multiethnic population identified BMI-z scores and WC as the major predictors of MRI-derived SAT and VAT and highlights the important ethnic differences that need to be considered in diverse populations. (c) 2023 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Background & aims: Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition. Objective: We compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations. Methods: Raw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST. Results: Data from 73 (23.2 +/- 4.8 y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2-50.1U) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equation, all three devices showed significant (p < 0.01) CE from -1.6 to -2.9 kg. Conclusions: Raw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations. Published by Elsevier Ltd on behalf of European Society for Clinical Nutrition and Metabolism.

Background: Athletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels.Methods: The Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) im-aging, and bioelectrical impedance (BIA). Each of these methods generated 2-or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/ isometric dynamometry.Results: In total, 70 (35 female) athletes with a mean age of 21.8 +/- 4.2 years were recruited. Percent hydration (Body Water(6CM)/FFM6CM) had substantial variation in both males (63-73 %) and females (58-78 %). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin's Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC <0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0 %). Increasing quartiles (significant p < 0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status.Conclusion: The criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations.Summary box: This study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual- energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.(c) 2023 The Author(s). Published by Elsevier Ltd.

BACKGROUND & AIMS:The multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). METHODS:Samples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. RESULTS:67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95 % limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95 % LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. CONCLUSIONS:Body composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.

To determine the precision, accuracy, and unique analysis challenges of HSA in children. Hip structural analysis (HSA) variables, a collection of 10 measures including cross-sectional area (CSA), cross-sectional inertia (CSI), and buckling ratio (BR), have been shown to be independent risk factors in determining fracture risk in adults, but there have been few studies reporting the utility and accuracy of HSA in children. Previous work has described the precision of HSA in adults, but the precision and unique challenges of the HSA protocol in children is unexplored. Here we describe the unique challenges, precision, and quality assurance protocol of pediatric HSA measures in a large cohort of over 2,500 children. This is a retrospective analysis of prospectively collected DXA scans acquired as part of two studies, the Bone Mineral Density in Childhood Study (BMDCS) and the Genome-wide Analysis Study (GWAS). The combined sample consisted of 2,514 children (10,787 scans, 1,271 girls) aged from 5 to 21 years. The proximal femur DXA scans were acquired on five Hologic systems (Hologic, Inc., Marlborough, MA) of similar models (A and W) with up to eight years of annual follow-up between 2002 and 2009. All scans were analyzed centrally by the authors using one technologist using APEX 3.4 software. A unique and comprehensive quality assurance check was completed for all scans including a review of the acquisition criteria set by ISCD and a review of the automatically placed HSA region's narrow neck (NN), intertrochanteric (IT), and femoral shaft (FS) region of interests. During processing, regions were either repositioned or eliminated on DXA imaging. Duplicate scans were performed on 150 children (71 girls) for precision assessment. Specific HSA quality control (QC) codes were generated for this particular analysis in accordance with the author's criteria. Short-term precision estimates were calculated as the RMSE and %CV. QA codes were assigned to the NN, IT, and FS boxes that were either incorrectly positioned or invalidated. Of the entire dataset under 10% of NN and FS boxes needed to be repositioned and none were invalidated. Figure 1 provides an example of proper placement of the IT box (at a 45-degree angle) in between the greater and lesser trochanter. If the angle of the IT box is either < 10 or >25 degrees, the IT box was invalidated. In this study, 100% of the IT boxes needed to be repositioned and 54% remained invalid. Multiple reasons were identified for an invalid scan region including the unavoidable presence of a growth plate in the hip scans for participants less than 15 years old, as shown in Figure 1. All HSA precision over all age groups ranged was less than 6% CV except for the NN Buckling ratio and Cross-sectional Inertia. In general, the precision error was lower in the older ages versus the younger participants. See Table 1. We conclude that HSA creates precise estimates in children that are comparable to that in adults for the femur neck and shaft but not the intertrochanteric region. Thorough quality assurance procedures must be in place to safeguard against poor region placement due to the size of the bone.

ObjectiveTo compare multiple body composition analysis methods in athletes with varying states of hydration to the criterion 5-compartment model(5CM) of body composition and assess the relationships of technique-specific estimates of fat and fat-free mass(FM, FFM) to muscle strength.MethodsBody composition was assessed in 80(40-female) athletes with a mean age of 21.8±4.2 years. All athletes underwent laboratory-based methods: air-displacement plethysmography(ADP), deuterium-oxide dilution(D2O), dual-energy X-ray absorptiometry(DXA), underwater-weighing(UWW), and field-based: 3D-optical(3DO) imaging, and three bioelectrical impedance(BIA) devices(S10/SFB7/SOZO). Participants’ muscular strength was assessed by isokinetic/isometric dynamometry. Accuracy was assessed by Lin’s concordance correlation coefficient(CCC) and precision by root-mean-square coefficient of variation(RMS-CV%).ResultsAthletes’ hydration status(total body water/FFM) was significantly(p<0.05) outside of the normal range in both males(0.63-0.73%) and females(0.58-0.78%). The most accurate techniques(ADP/DXA) showed moderate-substantial agreement(CCC=0.90-0.95) in FM and FFM, whereas all field assessments had poor agreement(CCC<0.90), except 3DO FFM in females(CCC=0.91). All measures of FFM produced excellent <1.0% precision, whereas FM from ADP, DXA, D2O, S10, and UWW had <2.0%. The associations between muscle strength and the various devices’ FFM estimates differed. However, more accurate body composition compared to the criterion produced a better determination of muscle strength by significant quartilep-trends(p<0.001). The 5CM exhibits the highest determination for all categories of muscle strength which persisted across all hydration measures.ConclusionTo optimize accuracy in assessing body composition and muscle strength, researchers and clinicians should prioritize selecting devices based on their accuracy compared to the 5CM. Reliable approaches such as ADP and DXA yield accurate and precise body composition estimates and thereby, better strength assessments, regardless of hydration status. Future athlete studies should investigate the impact of changes in FFM on functional measures compared to the criterion method.Summary BoxThis study compared various body composition analysis methods in athletes with varying states of hydration to the criterion 5-compartment model(5CM) and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produced better strength estimates. The best laboratory-based techniques were air displacement plethysmography(ADP) and dual-energy x-ray absorptiometry(DXA), while field assessments had moderate-poor agreement. Prioritize accurate body composition assessment devices compared to the 5CM for better strength estimates in athletes.

To investigate the precision and analysis protocol for VAT, SAT, and VAT/SAT ratio and explore precision covariates in a large prospective sample of children and young adults. Visceral adipose tissue (VAT) has been linked to poor metabolic health, including obesity and metabolic syndrome. Excess VAT can have an early onset during childhood. VAT measured by DXA has been shown to well represent CT and MRI VAT in adults. However, few studies have shown repeatability and quality assurance issues for children. These data have been collected as a part of a retrospective analysis of prospectively collected DXA scans acquired as part of two studies, the Bone Mineral Density in Childhood Study (BMDCS) and the Genome-wide Analysis Study (GWAS). The combined sample consisted of 2,514 children (10,787 scans, 1,271 girls) aged from 5 to 21 years. The whole-body DXA scans were acquired on five Hologic systems (Hologic, Inc., Marlborough, MA) of similar models (A and W) with up to eight years of annual follow-up between 2002 and 2009. All scans were analyzed centrally by the authors using one technologist using APEX 3.4 software. A unique and comprehensive quality assurance check was completed for all scans including a review of the acquisition criteria set by ISCD and a review of the automatically placed VAT regions of interest. During processing, regions were either repositioned or eliminated on DXA imaging. Duplicate scans were available on up to 150 children (71 girls) for precision assessment which was used to evaluate test-retest precision, both overall and by age group. Short-term precision estimates were calculated as the root mean square error and percent coefficients of variation (RMSE %CV). VAT codes were broken up into either invalidated scans or incorrectly positioned and subsequently corrected. Precision for all children in terms of %CV and RMSE (g) was 7.9% (12.8g) and 4.1% (24.7g) for VAT and SAT respectively. See Table 1. In general, the late teen group had the lowest precision error CV% (3.1-9.0) when compared to all other groups, and preteens had the highest %CV range (4.6-11.4). A pair of scans is shown in Figure 1 where the auto analyzer correctly positioned the regions of interest for the first scan but not for the second scan. Seven percent (752 scans) of the total number of scans had to be manually adjusted. We conclude that the precision of the VAT regions is dependent on age where the precision for late teens is similar to that of adults. All Hologic DXA whole body scans in children should be manually reviewed for region placement for the most accurate and precise results.

BACKGROUND:Deuterium oxide (D2O) dilution is the criterion method for total body water (TBW) measurement, but results may vary depending on the specimen type, analysis method, and analyzing laboratory. Bioelectrical impedance (BIA) estimates TBW, but results may vary by device make and model. OBJECTIVES:We investigated the accuracy and precision of TBW estimates and how measurement conditions affected the accuracy of body composition using multicompartment body composition models. METHODS:Eighty collegiate athletes received duplicate TBW measures acquired from 3 BIA devices (S10, SFB7, and SOZO) and from unique D2O combinations of specimen type (saliva, urine), analysis methodology [Fourier transform infrared spectrophotometry (FTIR), isotope-ratio mass spectrometry (IRMS)], and 3 different laboratories. TBW measures were substituted into 2-compartment (2C) and 5-compartment (5C) body composition models. Criterion measures were compared using Lin's concordance correlation coefficient cutoff of poor (<0.90), moderate (0.90-0.95), substantial (0.95-0.99), and almost perfect (>0.99). RESULTS:Fifty-one participants (26 female) completed the protocol. Using IRMS saliva as the criterion TBW, all other measures produced a substantial or almost perfect agreement, except for SFB7 (poor) and SOZO (moderate). The 2C body composition measures using D2O and BIA produced poor agreement except for moderate agreement for lab 3 FTIR saliva. The 5C body composition measures using D2O produced a substantial agreement, whereas the BIA device S10 and SOZO had a moderate agreement, while the SFB7 had a poor agreement to the criterion. Test-retest precision varied between techniques from 0.3% to 1.2% for TBW. CONCLUSIONS:Small differences in TBW measurement led to significant differences in 2C models. The 5C models partially mitigate differences seen in 2C models when different TBW measures are used. Interchanging TBW measures in multicompartment models can be problematic and should be performed with these considerations.

The French chemist Michel Eugene Chevreul discovered creatine in meat two centuries ago. Extensive biochemical and physiological studies of this organic molecule followed with confirmation that creatine is found within the cytoplasm and mitochondria of human skeletal muscles. Two groups of investigators exploited these relationships five decades ago by first estimating the creatine pool size in vivo with C-14 and N-15 labelled isotopes. Skeletal muscle mass (kg) was then calculated by dividing the creatine pool size (g) by muscle creatine concentration (g/kg) measured on a single muscle biopsy or estimated from the literature. This approach for quantifying skeletal muscle mass is generating renewed interest with the recent introduction of a practical stable isotope (creatine-(methyl-d3)) dilution method for estimating the creatine pool size across the full human lifespan. The need for a muscle biopsy has been eliminated by assuming a constant value for whole-body skeletal muscle creatine concentration of 4.3 g/kg wet weight. The current single compartment model of estimating creatine pool size and skeletal muscle mass rests on four main assumptions: tracer absorption is complete; tracer is all retained; tracer is distributed solely in skeletal muscle; and skeletal muscle creatine concentration is known and constant. Three of these assumptions are false to varying degrees. Not all tracer is retained with urinary isotope losses ranging from 0% to 9%; an empirical equation requiring further validation is used to correct for spillage. Not all tracer is distributed in skeletal muscle with non-muscle creatine sources ranging from 2% to 10% with a definitive value lacking. Lastly, skeletal muscle creatine concentration is not constant and varies between muscles (e.g. 3.89-4.62 g/kg), with diets (e.g. vegetarian and omnivore), across age groups (e.g. middle-age, similar to 4.5 g/kg; old-age, 4.0 g/kg), activity levels (e.g. athletes, similar to 5 g/kg) and in disease states (e.g. muscular dystrophies, <3 g/kg). Some of the variability in skeletal muscle creatine concentrations can be attributed to heterogeneity in the proportions of wet skeletal muscle as myofibres, connective tissues, and fat. These observations raise serious concerns regarding the accuracy of the deuterated-creatine dilution method for estimating total body skeletal muscle mass as now defined by cadaver analyses of whole wet tissues and in vivo approaches such as magnetic resonance imaging. A new framework is needed in thinking about how this potentially valuable method for measuring the creatine pool size in vivo can be used in the future to study skeletal muscle biology in health and disease.

BackgroundLower limb muscular strength is a well-known predictor of all-cause mortality and physical function in adults.Assessment of lower limb muscle strength using the criterion isokinetic dynamometer method is expensive and often not accessible in clinical or field settings.Accessible alternatives to the dynamometer would allow for broader screening of the risk and consequences of frailty, including falls and fractures.Recently, 3-dimensional optical (3DO) scanners have been investigated as an alternative to manual anthropometry and other body composition measures for health assessment.3DO wholebody scans have the potential for predicting strength due to their ability to produce over 200 variables of total and regional anthropometric measurements such as limb length and girth.Our previous studies have found only modest 3DO anthropometry and isokinetic knee extension; female: R 2 =0.24,RMSE=31.28,male: R 2 =0.34,RMSE=54.51 (1).Bioelectrical impedance (BIA) is another standard clinical tool for estimating body composition, such as skeletal muscle (SMM), phase angle (PhA), which could be a potential complementary tool to 3DO given its ability to give valid estimates of muscle strength. ObjectiveOur objective is to identify the optimum estimate of lower limb strength using a combination of 3DO anthropometry measures and BIA.

Background: Deuterium dilution is the criterion method to quantify total body water (TBW) in humans and to estimate body composition and hydration Dilution of deuterated water in the body can be estimated from saliva, urine, or blood samples The gold standard for quantifying isotope fractions is isotope ratio mass spectroscopy (IRMS);Fourier Transfer Infrared Spectroscopy (FTIR) is another less validated method that is more accessible Few studies compare the precision and accuracy of TBW where samples are analyzed at different laboratories using different techniques and/or types of samples In this study, we compare results from three laboratories using blinded duplicate samples of either saliva or urine measured using either FTIR or IRMS Methods: The DaKine study recruited 80 athletes for multiple body composition measures Each participant had 9 ml of both urine and saliva collected at baseline, 3 and 4-hour time points following the International Atomic Energy Agency protocol The samples were aliquoted into 30 divisions providing blindedduplicate samples to three laboratories for both urine and saliva Lab1 used IRMS for urine Lab2 used IRMS to process saliva and urine, while Lab3 used FTIR to process saliva and urine Results: Because of the temporary closure of the laboratories due to Covid-19, urine samples from only 24 of the 80 subjects have been processed by the laboratories so far The test-retest RMSE (%CV) for urine was as follows: Lab1=0 25 L (0 55%);Lab2=0 24 L (0 60%);Lab3=pending For saliva, the precision was: Lab1=unavailable;Lab2=0 26 L (0 63%);Lab3=pending The accuracy between laboratories for urine measures was Lab2=0 98Lab1 - 024, R2=0 98, RMSE=1 31 Intra-laboratory comparison of urine and saliva was Lab2(urine)=1 01Lab2- 08, R2=0 98, RMSE=1 2 Conclusions: We conclude that inter-lab urine samples using IRMS are highly accurate (R2 = 0 98) to one another with precisions less than 1% Intralab lab saliva and urine comparisons had similar accuracy and precision