Currently, laparoscopic surgery is a standard technique in the field of abdominal surgery. However, the most adequate fluid regimen during laparoscopic surgery remains unclear. The aim of this trial is to compare a restricted fluid therapy with a liberal fluid therapy for laparoscopic abdominal surgery. Our hypothesis was that restrictive fluid therapy would reduce postoperative complications better than liberal fluid therapy.

In this randomized controlled trial, patients scheduled for laparoscopic gastric surgery were randomized to either the liberal group (receiving 7-10 ml/kg/h of crystalloid) or the restrictive group (receiving 1-2 ml/kg/h of crystalloid) for each stratum of surgical procedure from April 2017 to March 2019. For both groups, blood loss was replaced by an equal volume of hydroxyethyl starch. The primary endpoint was postoperative complications up to 30 days after surgery, according to the Clavien-Dindo classification.

We enrolled 148 patients, and 140 of these were randomized to either the liberal or the restrictive group after exclusion. As a result, 69 cases were included in the liberal group for analysis, and 67 patients composed the restrictive group. Median fluid administration for the liberal and restrictive groups was 2950 ml and 800 ml, respectively. As well, overall complications in the liberal and restrictive groups were 27.5% and 19.4%, respectively (risk ratio 0.71, 95% confidence interval 0.38-1.31, p value = 0.264).

Restricted fluid therapy and liberal fluid therapy did not show any statistical differences in postoperative complications after laparoscopic gastric surgery.

This study aimed to observe adolescents' changes and individual responses regarding the anthropometry, cardiometabolic profile, vitamin D concentrations, physical fitness, and motor competence upon immediate return and three months of school activities after lockdown.

The study included 28 adolescents (14.8 ± 0.8 years) of both sexes. Anthropometric measures, body composition, cardiometabolic parameters, physical fitness, and motor competence were assessed. A paired t-test was used to compare the frequencies of respondents and the effect size of the results, considering significant p < 0.05.

After three months of school activities, adolescents changed their body composition, reducing % fat mass (p = 0.008) and increasing fat-free mass (p = 0.008). In terms of physical fitness, there was increased abdominal resistance (p < 0.001; ES = -0.42) and motor performance, with reduction in supine-to-stand test time (p < 0.001; ES = 0.53). There were very beneficial effects in reducing resting heart rate (p ≤ 0.001; ES = 0.61) and increasing vitamin D concentrations (p < 0.001; ES = -0.61). After three months of a school routine, the proportions of change in respondents were similar between girls and boys and eutrophic individuals and overweight individuals.

Returning to school activities after lockdown was important for the recovery of vitamin D concentrations, physical fitness, and motor competence, whose responses were independent of the level of adiposity and sex of the adolescents.

Segmentation of the femur in Dual-Energy X-ray (DXA) images poses challenges due to reduced contrast, noise, bone shape variations, and inconsistent X-ray beam penetration. In this study, we investigate the relationship between noise and certain deep learning (DL) techniques for semantic segmentation of the femur to enhance segmentation and bone mineral density (BMD) accuracy by incorporating noise reduction methods into DL models.

Convolutional neural network (CNN)-based models were employed to segment femurs in DXA images and evaluate the effects of noise reduction filters on segmentation accuracy and their effect on BMD calculation. Various noise reduction techniques were integrated into DL-based models to enhance image quality before training. We assessed the performance of the fully convolutional neural network (FCNN) in comparison to noise reduction algorithms and manual segmentation methods.

Our study demonstrated that the FCNN outperformed noise reduction algorithms in enhancing segmentation accuracy and enabling precise calculation of BMD. The FCNN-based segmentation approach achieved a segmentation accuracy of 98.84% and a correlation coefficient of 0.9928 for BMD measurements, indicating its effectiveness in the clinical diagnosis of osteoporosis.

In conclusion, integrating noise reduction techniques into DL-based models significantly improves femur segmentation accuracy in DXA images. The FCNN model, in particular, shows promising results in enhancing BMD calculation and clinical diagnosis of osteoporosis. These findings highlight the potential of DL techniques in addressing segmentation challenges and improving diagnostic accuracy in medical imaging.

Obesity, characterized by excessive body fat accumulation, is associated with various chronic health conditions. Body fat plays a crucial role in health outcomes, and nutrient intake is a contributing factor. Menopause further influences body fat, but the precise relationships between nutrients and fat mass distribution in pre- and post-menopausal women are unclear.

Data from 4751 adult women aged ≥18 years old (3855 pre-menopausal, 896 post-menopausal) with completed information were obtained from the National Health and Examination Survey (NHANES) from 2011 to 2018. Multivariate linear regression models were used to examine the associations between protein, carbohydrate, fat intake and total percent fat (TPF), android percent fat (APF), gynoid percent fat (GPF), android to gynoid ratio (A/G), subcutaneous adipose tissue mass (SAT), visceral adipose tissue mass (VAT). Subgroup analyses, stratified by menopausal status, were also conducted. Additionally, we employed smoothing curve fitting techniques to investigate potential non-linear relationships between fat mass distribution and nutrient intake.

Compared with pre-menopausal women, post-menopausal women had higher body fat, BMI, and metabolic indicators but lower nutrient intake (All p<0.05). In the overall analysis, we found significant correlations between nutrient intake and fat mass. Specifically, protein intake was negatively correlated with TPF (β = -0.017, 95% CI: -0.030, -0.005), APF (β = -0.028, 95% CI: -0.044, -0.012), GPF (β = -0.019, 95% CI: -0.030, -0.008), while fat intake showed positive correlations with these measures (SAT: β = 2.769, 95% CI: 0.860, 4.678). Carbohydrate intake exhibited mixed associations. Notably, body fat mass-nutrient intake correlations differed by menopausal status. Generally speaking, protein intake showed negative correlations with body fat distribution in pre-menopausal women but positive correlations in post-menopausal women. Carbohydrate intake revealed significant negative associations with abdominal and visceral fat in post-menopausal women, while fat intake was consistently positive across all fat distribution indices, especially impacting visceral fat in post-menopausal women.

Dietary intake plays a crucial role in body fat distribution, with menopausal status significantly influencing the impact of nutrients on specific fat distribution metrics. The study emphasizes the need for dietary guidelines to consider the nutritional needs and health challenges unique to women at different life stages, particularly concerning menopausal status, to effectively manage obesity.

Breast cancer related lymphedema (BCRL) may be assessed through objective measurement of limb swelling with common techniques including volumetric measurement using a tape measure or perometry, and measurement of extracellular water using bioimpedance spectroscopy (BIS). This study aimed to evaluate the performance of a stand-on BIS device for detection of BCRL, introduce a novel graphical method to compare volumetric and BIS methods alongside traditional specificity and sensitivity analysis, and determine and compare BIS thresholds with those published previously.

Female participants with indocyanine green lymphography confirmed unilateral arm lymphedema (n = 197) and healthy controls (n = 267) were assessed using a cross-sectional study design. BIS and volumetric measures were obtained in a single session.

The BIS lymphedema index (L-Dex) method had a significantly higher sensitivity than the excess volume approach (area under the curve = 0.832 vs. 0.649, p = 0.0001). A threshold of L-Dex 6.5 had a higher true positive rate (70.6%) than L-Dex 10 (68.5%) although false positive rate increased from 0.4% to 2.6%. A threshold of 5% excess volume improved the true positive rate (68.5%) compared with 10% excess volume (49.7%) however the false positive rate increased to an unacceptable 47%. The L-Dex ranges in this study were not significantly different from previously published ranges.

BIS was superior for identifying BCRL compared with volume measurements, reaffirming the value of this technique. However, it is recommended that BIS be used in conjunction with comprehensive evaluation of symptoms and clinical presentation. The proposed graphical method provides a simple and easily interpretable approach to compare and define concordance between the two commonly used methods for BCRL assessment namely limb volume and BIS L-Dex indices. The existing BIS (L-Dex) thresholds for presence of BCRL were also validated.

The present Systematic Review with Meta-analysis study aimed to evaluate the validity and reliability of the Portable A-mode Ultrasound (P-US) for measuring body fat percentage (BF%). Only studies with participants of both genders which had assessed BF% using P-US compared to the reference standard were selected. Publications up until May 31, 2022 were searched in the MEDLINE, COCHRANE, Science Direct, Web of Science, LILACS, SciELO, PEDro, SPORT Discus, CINAHL and SCOPUS databases. QUADAS-2 was used to assess the risk of bias in the validity studies and QAREL was used for the methodological quality of reliability studies. The JAMOVI software program synthesized the results, from which the Pearson Correlation Coefficient (r) or the square root of the Multiple Linear Regression Determination Coefficient (R2) were extracted for the validity studies, and the Mean of Errors of the Bland-Altman Test (ME) and the Confidence Interval (95%CI) with Upper and Lower Limits for the reliability studies. A total of 13 studies were included, generating 26 results for the quantitative synthesis, 14 for validity and 12 for reliability. Regarding the validity results, a strong correlation was identified between the equipment (r = 0.870 [0.845-0.895], P<0.001), with moderate and true heterogeneity (I2 = 53.47%, P = 0.003), presenting publication bias. A small effect size was identified regarding the reliability results, overestimating the results due to chance between the devices (ME = 0.207 [-0.798-1.212], P = 0.686), with low heterogeneity also due to chance (I2 = 19.44%, P = 0.253), with no publication bias. All of the evaluated studies showed some violation of the instruments, confirming the high risk of bias and the low methodological quality. There is concern with heterogeneity for the validity results explained by the subgroups' analysis. The P-US associated with anthropometric perimeters satisfactorily measures the BF% with samples greater than 100 participants, and males. The results in the reliability assessment show high agreement and high variability, greatly expanding the confidence interval, which should be viewed with reservations. This review received financial support from the Brazilian Air Force. The study was registered with PROSPERO under the number CRD42020166617.

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).

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.

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.

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.

High-intensity interval training (HIIT) is an effective alternative to moderate intensity continuous training for improvements in body composition and aerobic capacity; however, there is little work comparing different modalities of HIIT. The purpose of this study was to compare the effects of plyometric- (PLYO) and cycle-oriented (CYC) HIIT on body composition, aerobic capacity, and skeletal muscle size, quality, and function in recreationally trained females. Young (21.7 ± 3.1 yrs), recreationally active females were quasi-randomized (1:1 ratio) to 8 weeks of twice weekly PLYO (n = 15) or CYC (n = 15) HIIT. Body composition (four-compartment model), VO2peak, countermovement jump performance, muscle size, and echo intensity (muscle quality), as well as strength and power of the knee extensors and plantar flexors were measured before and after training. Both groups showed a similar decrease in body fat percentage (p < 0.001;η p 2   = 0.409) and echo intensity (p < 0.001;η p 2 = 0.558), and an increase in fat-free mass (p < 0.001;η p 2   = 0.367) and VO2peak (p = 0.001;η p 2 = 0.318). Muscle size was unaffected (p > 0.05), whereas peak torque was reduced similarly in both groups (p = 0.017;η p 2 = 0.188) and rapid torque capacity was diminished only for the knee extensors after CYC (p = 0.022; d = -0.67). These results suggest that PLYO and CYC HIIT are similarly effective for improving body composition, aerobic capacity, and muscle quality, whereas muscle function may express moderate decrements in recreationally active females. ClinicalTrials.gov (NCT05821504).

New recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA).

Identify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders.

Participants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of <20 kg/m2 in adults or <85% of median BMI (mBMI) in children and adolescents. A subset was referred for eating disorders evaluation. Anthropometrics, scans, strength testing, and questionnaires were completed in clinical research centers. Lin's Concordance Correlation Coefficient (CCC) assessed agreement between 3DO and DXA; multivariate linear regression analysis examined associations between weight history and body composition.

Among 95 participants, mean ± SD BMI was 18.3 ± 1.4 kg/m2 in adult women (N = 56), 19.0 ± 0.6 in men (N = 14), and 84.2% ± 4.1% mBMI in children (N = 25). Concordance was excellent for fat-free mass (FFM, CCC = 0.97) and strong for appendicular lean mass (ALM, CCC = 0.86) and fat mass (FM, CCC = 0.87). By DXA, 80% of adults met the low FFM index criterion for malnutrition, and 44% met low ALM for sarcopenia; 52% of children and adolescents were <-2 z-score for FM. 3DO identified 95% of these cases. In the subset, greater weight loss predicted lower FFM, FM, and ALM by both methods; a greater percentage of weight regained predicted a higher percentage of body fat.

3DO can accurately estimate body composition in participants with low BMI and identify criteria for malnutrition and sarcopenia. In a subset, 3DO detected changes in body composition expected with weight loss and regain secondary to eating disorders. These findings support the utility of 3DO for body composition assessment in patients with low BMI, including those with eating disorders. This trial was registered at clinicaltrials.gov as NCT03637855.

Although dual X-ray absorptiometry (DXA) has been used to determine total body volume, using DXA to determine regional (i.e., arm and leg) volumes needs further assessment. Thus, the aim of the present study is to evaluate the validity of total and regional DXA-derived body volume compared to a traditional method for measuring body volume.

A total of 30 males and females (Age: 25.9 ± 4.0 yrs; Height: 1.75 ± 0.10 m; Weight: 70.98 ± 14.02 kg) underwent one whole body DXA scan, underwater weighing, and regional measures of volume via water displacement. Manually created DXA region of interest boxes were used to determine regional DXA body composition. Total body volume was calculated by taking the participant's dry weight and dividing it by the average density from underwater weighing. Linear regression models with body volume from underwater weighing for total body volume and water displacement for regional volume as the dependent variable and DXA lean mass, fat mass, and bone mass as independent variables created total and regional DXA-derived body volume. T-tests assessed DXA-derived body volume to the traditional method of body volume assessment. Regression models were cross-validated using the Repeated k-fold Cross Validation method.

DXA-derived total body volume was not significantly (p = 0.999) different from total body volume measured via total body water displacement. In addition, both arm and leg regional DXA-derived volume was not significantly different (p = 0.999) compared to regional volume measured by regional water displacement. Cross-validation of each model produced R² values of 0.992, 0.923, and 0.932 for total body, arm, and leg, respectively.

The DXA may be used as valid method for estimating total and regional body volume. Thus, these results expand the DXA's capabilities and potentially allow for a convenient regional four-compartment model with DXA-derived regional volume.

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.

We investigated the accuracy and precision of TBW estimates and how measurement conditions affected the accuracy of body composition using multicompartment body composition models.

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).

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.

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.

Adaptive thermogenesis (AT) has been proposed to be a compensatory response that may resist weight loss (WL) and promote weight regain. This systematic review examined the existence of AT in adults after a period of negative energy balance (EB) with or without a weight stabilisation phase. Studies published until 15 May 2020 were identified from PubMed, Cochrane Library, EMBASE, MEDLINE, SCOPUS and Web of Science. Inclusion criteria included statistically significant WL, observational with follow-up or experimental studies, age > 18y, sample size ≥10 participants, intervention period ≥ 1week, published in English, objective measures of total daily energy expenditure (EE) (TDEE), resting EE (REE) and sleeping EE(SEE). The systematic review was registered at PROSPERO (2020 CRD42020165348). A total of thirty-three studies comprising 2528 participants were included. AT was observed in twenty-seven studies. Twenty-three studies showed significant values for AT for REE (82·8 %), four for TDEE (80·0 %) and two for SEE (100 %). A large heterogeneity in the methods used to quantify AT and between subjects and among studies regarding the magnitude of WL and/or of AT was reported. Well-designed studies reported lower or non-significant values for AT. These findings suggest that although WL may lead to AT in some of the EE components, these values may be small or non-statistically significant when higher-quality methodological designs are used. Furthermore, AT seems to be attenuated, or non-existent, after periods of weight stabilisation/neutral EB. More high-quality studies are warranted not only to disclose the existence of AT but also to understand its clinical implications on weight management outcomes.

The accurate assessment of total body and regional body circumferences, volumes, and compositions are critical to monitor physical activity and dietary interventions, as well as accurate disease classifications including obesity, metabolic syndrome, sarcopenia, and lymphedema. We assessed body composition and anthropometry estimates provided by a commercial 3-dimensional optical (3DO) imaging system compared to criterion measures.

Participants of the Shape Up! Adults study were recruited for similar sized stratifications by sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and across five ethnicities (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander). All participants received manual anthropometry assessments, duplicate whole-body 3DO (Styku S100), and dual-energy X-ray absorptiometry (DXA) scans. 3DO estimates provided by the manufacturer for anthropometry and body composition were compared to the criterion measures using concordance correlation coefficient (CCC) and Bland-Altman analysis. Test-retest precision was assessed by root mean square error (RMSE) and coefficient of variation.

A total of 188 (102 female) participants were included. The overall fat free mass (FFM) as measured by DXA (54.1 ± 15.2 kg) and 3DO (55.3 ± 15.0 kg) showed a small mean difference of 1.2 ± 3.4 kg (95% limits of agreement -7.0 to +5.6) and the CCC was 0.97 (95% CI: 0.96-0.98). The CCC for FM was 0.95 (95% CI: 0.94-0.97) and the mean difference of 1.3 ± 3.4 kg (95% CI: -5.5 to +8.1) reflected the difference in FFM measures. 3DO anthropometry and body composition measurements showed high test-retest precision for whole body volume (1.1 L), fat mass (0.41 kg), percent fat (0.60%), arm and leg volumes, (0.11 and 0.21 L, respectively), and waist and hip circumferences (all <0.60 cm). No group differences were observed when stratified by body mass index, sex, or race/ethnicity.

The anthropometric and body composition estimates provided by the 3DO scanner are precise and accurate to criterion methods if offsets are considered. This method offers a rapid, broadly available, and automated method of body composition assessment regardless of body size. Further studies are recommended to examine the relationship between measurements obtained by 3DO scans and metabolic health in healthy and clinical populations.

The purpose of this study was: (1) to compare body volume (BV) estimated from a 2-dimensional (2D) image analysis program (BV_IMAGE), and a dual-energy x-ray absorptiometry (DXA) equation (BV_{DXA-Smith-Ryan}) to an underwater weighing (UWW) criterion (BV_UWW); (2) to compare relative adiposity (%Fat) derived from a 3-compartment (3C) model using BV_IMAGE (%Fat_3C-IMAGE), and a 4-compartment (4C) model using BV_{DXA-Smith-Ryan} (%Fat_{4C-DXA-Smith-Ryan}) to a 4C criterion model using BV_UWW (%Fat_4C-UWW).

Forty-eight participants were included (60% male, 22.9 ± 5.0 years, 24.2 ± 2.6 kg/m²). BV_IMAGE was derived using a single digital image of each participant taken from the rear/posterior view. DXA-derived BV was calculated according to Smith-Ryan et al. Bioimpedance spectroscopy and DXA were used to measure total body water and bone mineral content, respectively, in the 3C and 4C models. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean ± standard deviation.

Near-perfect correlation (r = 0.998, p < 0.001) and no mean differences (p = 0.267) were observed between BV_IMAGE (69.6 ± 11.5 L) and BV_UWW (69.5 ± 11.4 L). No mean differences were observed between %Fat_{4C-DXA-Smith-Ryan} and the %Fat_4C-UWW criterion (p = 0.988). Small mean differences were observed between %Fat_3C-IMAGE and %Fat_4C-UWW (ES = 0.2, p < 0.001). %Fat_3C-IMAGE exhibited smaller SEE and TE, and tighter limits of agreement than %Fat_{4C-DXA-Smith-Ryan}.

The 2D image analysis program provided an accurate and non-invasive estimate of BV, and subsequently %Fat within a 3C model in generally healthy, young adults.

The aim of this study was to investigate whether digitally re-posing three-dimensional optical (3DO) whole-body scans to a standardized pose would improve body composition accuracy and precision regardless of the initial pose.

Healthy adults (n = 540), stratified by sex, BMI, and age, completed whole-body 3DO and dual-energy X-ray absorptiometry (DXA) scans in the Shape Up! Adults study. The 3DO mesh vertices were represented with standardized templates and a low-dimensional space by principal component analysis (stratified by sex). The total sample was split into a training (80%) and test (20%) set for both males and females. Stepwise linear regression was used to build prediction models for body composition and anthropometry outputs using 3DO principal components (PCs).

The analysis included 472 participants after exclusions. After re-posing, three PCs described 95% of the shape variance in the male and female training sets. 3DO body composition accuracy compared with DXA was as follows: fat mass R2 = 0.91 male, 0.94 female; fat-free mass R2 = 0.95 male, 0.92 female; visceral fat mass R2 = 0.77 male, 0.79 female.

Re-posed 3DO body shape PCs produced more accurate and precise body composition models that may be used in clinical or nonclinical settings when DXA is unavailable or when frequent ionizing radiation exposure is unwanted.

Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air-displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual-energy X-ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual-energy X-ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air-displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual-energy X-ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.

Three-dimensional (3D) body scanner technology for body composition assessment is expanding. The aim of this study was to assess the validity of a 3D body scanner. One hundred and ninety-four participants (43% male; age: 23.52 ± 5.47 years; body mass index: 23.98 ± 3.24 kg·m^-2) were measured using 3D scanner and a 4-compartment (4C) model utilizing dual-energy X-ray absorptiometry (DXA), air displacement plethysmography, and bioelectrical impedance spectroscopy. Dependent t tests, validity statistics including total error (TE), standard error of the estimate, constant error, and Bland-Altman analyses were utilized. Compared with 4C, 3D scanner fat mass (FM) [mean difference (MD; 3D-4C): 2.66 kg ± 3.32 kg] and percent body fat (%BF) (MD: 4.13% ± 5.36%) were significantly (p < 0.001) over-predicted; fat free mass (FFM) was significantly underpredicted (MD: -3.15 kg ± 4.75 kg; p < 0.001). 3D demonstrated poor validity indicated by TE (%BF: 5.61%; FM: 4.50 kg; FFM: 5.69 kg). In contrast, there were no significant differences between 3D and DXA measures; 3D scanner demonstrated acceptable measurement for %BF (TE: 4.25%), FM (TE: 2.92 kg), and lean mass (TE: 3.86 kg). Compared with the 4C criterion, high TE values indicated 3D estimates were not valid. In contrast, 3D estimates produced acceptable measurement agreement when compared with DXA; an average overestimation of %BF by 5.31% (vs. 4C) and 4.20% (vs. DXA) may be expected. Novelty: 3D body composition estimates are not valid compared with the 4-C criterion model. 3D estimates appeared to be more valid in females, compared with males. When compared with DXA, 3D estimates were acceptable.

Body composition assessment has large variability. A dual-energy x-ray absorptiometry (DXA) derived four compartment (4C) method has been developed as an accurate and reliable method for assessing body composition in overweight/obese adults. This investigation was aimed at understanding the validity of the DXA-derived 4C equation for use in normal weight individuals, stratified by sex, and with varied levels of lean mass. Values were also compared against DXA alone.

78 men and women (68% female; Mean ± SD; Age: 19.2 ± 1.2 yrs; Ht: 168.8 ± 9.1 cm; Wt: 62.8 ± kg) completed a traditional 4C body composition reference assessment. Body composition was also assessed using a DXA-4C model. Validity was evaluated from total error (TE), constant error, and standard error of the estimate (SEE). Proportional bias was identified with Bland Altman plots.

Although significantly different (p < 0.05) the DXA-4C model produced ideal TE and SEE compared to the 4C criterion for all body composition outcomes of fat mass (TE: 2.1 kg; SEE: 1.9 kg), lean mass (TE: 2.1 kg; SEE: 1.8 kg), and percent body fat (TE: 3.6%; SEE: 3.4%). Validity results did not differ for men vs. women. DXA-4C estimates were slightly better in individuals with higher lean mass. DXA alone resulted in significantly greater error than DXA-4C (p < 0.05).

Body composition assessed from DXA-4C is an accurate approach, particularly in those with high levels of lean mass. This model appears to be more accurate than DXA alone.

There is a shift in thinking about dietary protein requirements from daily requirements to individual meal requirements. Per meal, stimulation of muscle protein synthesis has a saturable dose relationship with the quantity of dietary protein consumed. Protein intake above the saturable dose does not further contribute to the synthetic response; the "excess" amino acids are predominantly oxidized. Given that daily dietary protein intake is finite, finding protein distribution patterns that both reduce amino acid oxidation and maximize their contribution towards protein synthesis (in theory improving net balance) could be "optimal" and is of practical scientific interest to promote beneficial changes in skeletal muscle-related outcomes. This article reviews both observational and randomized controlled trial research on the protein distribution concept. The current evidence on the efficacy of consuming an "optimal" protein distribution to favorably influence skeletal muscle-related changes is limited and inconsistent. The effect of protein distribution cannot be sufficiently disentangled from the effect of protein quantity. Consuming a more balanced protein distribution may be a practical way for adults with marginal or inadequate protein intakes (<0.80 g·kg-1·d-1) to achieve a moderately higher total protein intake. However, for adults already consuming 0.8-1.3 g·kg-1·d-1, the preponderance of evidence supports that consuming at least one meal that contains sufficient protein quantity to maximally stimulate muscle protein synthesis, independent of daily distribution, is helpful to promote skeletal muscle health.

This study aimed to explore the accuracy and precision of three-dimensional optical (3DO) whole-body scanning for automated anthropometry and estimating total and regional body composition.

Healthy children and adolescents (n = 181, ages 5-17 years) were recruited for the Shape Up! Kids study. Each participant underwent whole-body dual-energy x-ray absorptiometry and 3DO scans; multisite conventional tape measurements served as the anthropometric criterion measure. 3DO body shape was described using automated body circumference, length, and volume measures. 3DO estimates were compared with criterion measures using simple linear regression by the stepwise selection method.

Of the 181 participants, 112 were used for the training set, 49 were used for the test set, and 20 were excluded for technical reasons. 3DO body composition estimates were strongly associated with dual-energy x-ray absorptiometry measures for percent body fat, fat mass, and fat-free mass (R2 : 0.83, 0.96, and 0.98, respectively). 3DO provided reliable measurements of fat mass (coefficient of variation, 3.30; root mean square error [RMSE], 0.53), fat-free mass (coefficient of variation, 1.34; RMSE, 0.53 kg), and percent body fat (RMSE = 1.2%).

3DO surface scanning provides accurate and precise anthropometric and body composition estimates in children and adolescents with high precision. 3DO is a safe, accessible, and practical method for evaluating body shape and composition in research and clinical settings.

This study sought to investigate the effects of a multistrain probiotic on body composition, regional adiposity, and a series of associated metabolic health outcomes. Female health care workers employed on a rotating-shift schedule (n = 41) completed baseline anthropometric assessments; a fasted blood draw; questionnaires to assess anxiety, depression (Hospital Anxiety and Depression Scale), and fatigue (Chalder Fatigue Survey); and an exercise fatigue test. Identical post-tests occurred following 6 weeks of daily supplementation with placebo (PLA) or probiotics (2.5 × 10⁹ CFU/g) containing 9 bacterial strains (PRO; Ecologic Barrier) combined with a prebiotic carrier matrix. PRO attenuated fat mass increases (change (Δ), 0.14 kg; confidence interval (CI) -0.46 to 0.75 kg) compared with PLA (Δ, 0.79 kg; CI 0.03-1.54 kg), whereas modest reductions in visceral adiposity resulted for both PRO and PLA. Metabolic biomarkers (total cholesterol, high-density lipoprotein, glucose, adiponectin, C-reactive protein, interleukin-6, leptin) were not influenced by either treatment (p > 0.05). Nonsignificant, but potentially clinically relevant, improvements in anxiety (Δ, -2.3 ± 2.63) and fatigue (Δ, -4.8 ± 5.5) were observed with PRO; exercise performance was unaffected. Results indicate a potential protective effect of probiotics against fat mass gain. Probiotics may alleviate anxiety and fatigue in shift-working females.

Accurate measures of body composition (BC) are essential for performance and health. In addition to accuracy, BC measures should be practical and be minimally invasive to maximize their utility. The purpose of the present study was to compare the day-to-day variability and validity of four common laboratory-based body composition assessments to a criterion four-compartment model. Dual x-ray absorptiometry (DXA), air displacement plethysmography (BP), multi-frequency bioelectrical impedance (MF-BIA) and underwater weighing (UWW) were performed twice in a sample of 32 young men and women. Participants were assessed in a fasted, euhydrated state 2-7 days apart. All methods were compared to a criterion four-compartment model using BP-derived body volume, DXA-derived bone mineral content and MF-BIA-derived total body water (4C_BP ). Additional four-compartment models using UWW- and DXA-derived body volume were also examined (4C_UWW ) and (4C_DXA ). Validity results were conducted with paired t-tests and Bland-Altman analysis. Reliability was determined using intraclass correlations (ICC), coefficients of variation (CV) and standard error of the measurement (SEM). Validity analysis revealed that all methods overestimated per cent body fat and fat mass, and underestimated fat-free mass when compared with 4C_BP , but only DXA and BP were significantly different (P<0·008). All measures were highly reliable across days (ICCs > 0·9, CVs < 12%). Results of the present study indicate that typical laboratory-based methods of body composition are valid and reliable. However, we caution that results should not be translated between methods and assessments should be performed with the same instrument when the goal is to monitor changes in body composition over time.

The regulation of body fluid balance is a key concern in health and disease and comprises three concepts. The first concept pertains to the relationship between total body water (TBW) and total effective solute and is expressed in terms of the tonicity of the body fluids. Disturbances in tonicity are the main factor responsible for changes in cell volume, which can critically affect brain cell function and survival. Solutes distributed almost exclusively in the extracellular compartment (mainly sodium salts) and in the intracellular compartment (mainly potassium salts) contribute to tonicity, while solutes distributed in TBW have no effect on tonicity. The second body fluid balance concept relates to the regulation and measurement of abnormalities of sodium salt balance and extracellular volume. Estimation of extracellular volume is more complex and error prone than measurement of TBW. A key function of extracellular volume, which is defined as the effective arterial blood volume (EABV), is to ensure adequate perfusion of cells and organs. Other factors, including cardiac output, total and regional capacity of both arteries and veins, Starling forces in the capillaries, and gravity also affect the EABV. Collectively, these factors interact closely with extracellular volume and some of them undergo substantial changes in certain acute and chronic severe illnesses. Their changes result not only in extracellular volume expansion, but in the need for a larger extracellular volume compared with that of healthy individuals. Assessing extracellular volume in severe illness is challenging because the estimates of this volume by commonly used methods are prone to large errors in many illnesses. In addition, the optimal extracellular volume may vary from illness to illness, is only partially based on volume measurements by traditional methods, and has not been determined for each illness. Further research is needed to determine optimal extracellular volume levels in several illnesses. For these reasons, extracellular volume in severe illness merits a separate third concept of body fluid balance.

Accurate measurement of bone mineral density (BMD) in dual-energy X-ray absorptiometry (DXA) is essential for proper diagnosis of osteoporosis. Calculation of BMD requires precise bone segmentation and subtraction of soft tissue absorption. Femur segmentation remains a challenge as many existing methods fail to correctly distinguish femur from soft tissue. Reasons for this failure include low contrast and noise in DXA images, bone shape variability, and inconsistent X-ray beam penetration and attenuation, which cause shadowing effects and person-to-person variation.

To present a new method namely, a Pixel Label Decision Tree (PLDT), and test whether it can achieve higher accurate performance in femur segmentation in DXA imaging.

PLDT involves mainly feature extraction and selection. Unlike photographic images, X-ray images include features on the surface and inside an object. In order to reveal hidden patterns in DXA images, PLDT generates seven new feature maps from existing high energy (HE) and low energy (LE) X-ray features and determines the best feature set for the model. The performance of PLDT in femur segmentation is compared with that of three widely used medical image segmentation algorithms, the Global Threshold (GT), Region Growing Threshold (RGT), and artificial neural networks (ANN).

PLDT achieved a higher accuracy of femur segmentation in DXA imaging (91.4%) than either GT (68.4%), RGT (76%) or ANN (84.4%).

The study demonstrated that PLDT outperformed other conventional segmentation techniques in segmenting DXA images. Improved segmentation should help accurate computation of BMD which later improves clinical diagnosis of osteoporosis.

Recent advances have extended anthropometry beyond flexible tape measurements to automated three-dimensional optical devices that rapidly acquire hundreds of body surface dimensions. Three new devices were recently introduced that share in common inexpensive optical cameras. The design, and thus potential clinical applicability, of these systems differ substantially leading us to critically evaluate their accuracy and precision.

113 adult subjects completed evaluations by the three optical devices (KX-16 (16 stationary cameras), Proscanner (1 vertically oscillating camera), and Styku scanner (1 stationary camera)), air displacement plethysmography (ADP), dual-energy X-ray absorptiometry (DXA) and a flexible tape measure. Optical measurements were compared to reference method estimates that included results acquired by flexible tape, DXA and ADP.

Optical devices provided respective circumference and regional volume estimates that overall were well-correlated with those obtained from flexible tape measurements (for example, hip circumference: R2, 0.91, 0.90, 0.96 for the KX-16, Proscanner, and Styku scanner, respectively) and DXA (for example, trunk volume: R2, 0.97, 0.97, and 0.98). Total body volumes measured by the optical devices were highly correlated with those from the ADP system (all R2s, 0.99). Coefficient of variations obtained from duplicate measurements (n, 55) were larger in optical than in reference measurements and significant (P<0.05) bias was present for some optical measurements relative to reference method estimates.

Overall, the evaluated optical imaging systems differing in design provided body surface measurements that compared favorably with corresponding reference methods. However, our evaluations uncovered system measurement limitations, such as discrepancies in landmarking, that with correction have the potential to improve future developed devices.

Body volume (BV), one component of a four-compartment (4C) body composition model, is commonly assessed using air displacement plethysmography (BodPod). However, dual-energy x-ray absorptiometry (DEXA) has been proposed as an alternative method for calculating BV.

This investigation evaluated the validity and reliability of DEXA-derived BV measurement and a DEXA-derived 4C model (DEXA-4C) for percent body fat (%BF), fat mass (FM), and lean mass (LM).

A total sample of 127 men and women (Mean ± SD; Age: 35.8 ± 9.4 years; Body Mass: 98.1 ± 20.9 kg; Height: 176.3 ± 9.2 cm) completed a traditional 4C body composition reference assessment. A DEXA-4C model was created by linearly regressing BodPod BV with DEXA FM, LM, and bone mineral content as independent factors. The DEXA-4C model was validated in a random sub-sample of 27 subjects. Reliability was evaluated in a sample of 40 subjects that underwent a second session of identical testing.

When BV derived from DEXA was applied to a 4C model, there were no significant differences in %BF (p = 0.404), FM (p = 0.295), or LM (p = 0.295) when compared to the traditional 4C model. The approach was also reliable; BV was not different between trials (p = 0.170). For BV, %BF, FM, and LM relative consistency values ranged from 0.995 to 0.998. Standard error of measurement for BV was 0.62 L, ranging from 0.831 to 0.960 kg. There were no significant differences between visits for %BF (p = 0.075), FM (p = 0.275), or LM (p = 0.542).

The DEXA-4C model appears to be a valid and reliable method of estimating %BF, FM, and LM. The prediction of BV from DEXA simplifies the acquisition of 4C body composition by eliminating the need for an additional BV assessment.

There is growing evidence that body shape and regional body composition are strong indicators of metabolic health. The purpose of this study was to develop statistical models that accurately describe holistic body shape, thickness, and leanness. We hypothesized that there are unique body shape features that are predictive of mortality beyond standard clinical measures. We developed algorithms to process whole-body dual-energy X-ray absorptiometry (DXA) scans into body thickness and leanness images. We performed statistical appearance modeling (SAM) and principal component analysis (PCA) to efficiently encode the variance of body shape, leanness, and thickness across sample of 400 older Americans from the Health ABC study. The sample included 200 cases and 200 controls based on 6-year mortality status, matched on sex, race and BMI. The final model contained 52 points outlining the torso, upper arms, thighs, and bony landmarks. Correlation analyses were performed on the PCA parameters to identify body shape features that vary across groups and with metabolic risk. Stepwise logistic regression was performed to identify sex and race, and predict mortality risk as a function of body shape parameters. These parameters are novel body composition features that uniquely identify body phenotypes of different groups and predict mortality risk. Three parameters from a SAM of body leanness and thickness accurately identified sex (training AUC = 0.99) and six accurately identified race (training AUC = 0.91) in the sample dataset. Three parameters from a SAM of only body thickness predicted mortality (training AUC = 0.66, validation AUC = 0.62). Further study is warranted to identify specific shape/composition features that predict other health outcomes.

Obesity is a significant worldwide epidemic that necessitates accessible tools for robust body composition analysis. We investigated whether widely available 3D body surface scanners can provide clinically relevant direct anthropometrics (circumferences, areas and volumes) and body composition estimates (regional fat/lean masses).

Thirty-nine healthy adults stratified by age, sex and body mass index (BMI) underwent whole-body 3D scans, dual energy X-ray absorptiometry (DXA), air displacement plethysmography and tape measurements. Linear regressions were performed to assess agreement between 3D measurements and criterion methods. Linear models were derived to predict DXA body composition from 3D scan measurements. Thirty-seven external fitness center users underwent 3D scans and bioelectrical impedance analysis for model validation.

3D body scan measurements correlated strongly to criterion methods: waist circumference R2=0.95, hip circumference R2=0.92, surface area R2=0.97 and volume R2=0.99. However, systematic differences were observed for each measure due to discrepancies in landmark positioning. Predictive body composition equations showed strong agreement for whole body (fat mass R2=0.95, root mean square error (RMSE)=2.4 kg; fat-free mass R2=0.96, RMSE=2.2 kg) and arms, legs and trunk (R2=0.79-0.94, RMSE=0.5-1.7 kg). Visceral fat prediction showed moderate agreement (R2=0.75, RMSE=0.11 kg).

3D surface scanners offer precise and stable automated measurements of body shape and composition. Software updates may be needed to resolve measurement biases resulting from landmark positioning discrepancies. Further studies are justified to elucidate relationships between body shape, composition and metabolic health across sex, age, BMI and ethnicity groups, as well as in those with metabolic disorders.

Obesity and its consequences, such as diabetes, are global health issues that burden about 171 × 10(6) adult individuals worldwide. Fat mass index (FMI, kg/m(2)), fat-free mass index (FFMI, kg/m(2)), and percent fat mass may be useful to evaluate under- and overnutrition and muscle development in a clinical or research environment. This proof-of-concept study tested whether frontal whole-body silhouettes could be used to accurately measure body composition parameters using active shape modeling (ASM) techniques.

Binary shape images (silhouettes) were generated from the skin outline of dual-energy x-ray absorptiometry (DXA) whole-body scans of 200 healthy children of ages from 6 to 16 yr. The silhouette shape variation from the average was described using an ASM, which computed principal components for unique modes of shape. Predictive models were derived from the modes for FMI, FFMI, and percent fat using stepwise linear regression. The models were compared to simple models using demographics alone [age, sex, height, weight, and body mass index z-scores (BMIZ)].

The authors found that 95% of the shape variation of the sampled population could be explained using 26 modes. In most cases, the body composition variables could be predicted similarly between demographics-only and shape-only models. However, the combination of shape with demographics improved all estimates of boys and girls compared to the demographics-only model. The best prediction models for FMI, FFMI, and percent fat agreed with the actual measures with R(2) adj. (the coefficient of determination adjusted for the number of parameters used in the model equation) values of 0.86, 0.95, and 0.75 for boys and 0.90, 0.89, and 0.69 for girls, respectively.

Whole-body silhouettes in children may be useful to derive estimates of body composition including FMI, FFMI, and percent fat. These results support the feasibility of measuring body composition variables from simple cameras such as those found in cell phones.

Measurements of maternal fat mass (FM) are important for studies of maternal and fetal health. Common methods of estimating FM have not been previously compared in pregnancy with measurements using more complete body composition models.

The goal of this pilot study was to compare multiple methods that estimate FM, including 2-, 3- and 4-compartment models in pregnant women at term, and to determine how these measures compare with FM by dual-energy X-ray absorptiometry (DXA) 2 wk postpartum.

Forty-one healthy pregnant women with prepregnancy body mass index (in kg/m(2)) 19 to 46 underwent skinfold thickness (SFT), bioelectrical impedance analysis (BIA), body density (Db) via air displacement plethysmography (ADP), and deuterium dilution of total body water (TBW) with and without adjustments for gestational age using van Raaij (VRJ) equations at 37-38 wk of gestation and 2 wk postpartum to derive 8 estimates of maternal FM. Deming regression analysis and Bland-Altman plots were used to compare methods of FM assessment.

Systematic differences in FM estimates were found. Methods for FM estimates from lowest to highest were 4-compartment, DXA, TBW(VRJ), 3-compartment, Db(VRJ), BIA, air displacement plethysmography body density, and SFT ranging from a mean ± SD of 29.5 ± 13.2 kg via 4-compartment to 39.1 ± 11.7 kg via SFT. Compared with postpartum DXA values, Deming regressions revealed no substantial departures from trend lines in maternal FM in late pregnancy for any of the methods. The 4-compartment method showed substantial negative (underestimating) constant bias, and the air displacement plethysmography body density and SFT methods showed positive (overestimating) constant bias. ADP via Db(VRJ)and 3-compartment methods had the highest precision; BIA had the lowest.

ADP that uses gestational age-specific equations may provide a reasonable and practical measurement of maternal FM across a spectrum of body weights in late pregnancy. SFT would be acceptable for use in larger studies. This trial was registered at clinicaltrials.gov as NCT02586714.

Anthropometry for measuring body composition, shape, surface area and volume is important for human clinical research and practice. Although training and technical skills are required for traditional tape and caliper anthropometry, a new opportunity exists for automated measurement using newly developed relatively low-cost three-dimensional (3D) imaging devices. The aim of this study was to compare results provided by a Kinect-based device to a traditional laser 3D reference system.

Measurements made by the evaluated device, a hybrid of commercially purchased hardware (KX-16; TC(2), Cary, NC, USA) with our additional added software, were compared with those derived by a high-resolution laser scanner (Vitus Smart XXL; Human Solutions North America, Cary, NC, USA). Both imaging systems were compared with additional linear (stadiometer-derived height) and volumetric (total volume, air-displacement plethysmography) measurements. Subjects (n=101) were healthy children (age ≥5 years) and adults varying in body mass index.

Representative linear (4), circumferential (6), volumetric (3) and surface area (1) measurements made by the Kinect-based device showed a consistent pattern relative to the laser system: high correlations (R(2)s= 0.70-0.99, all P<0.001); 1-3% differences for large linear (for example, height, X±s.d., -1.4±0.5%), circumferential (for example, waist circumference, -2.1±1.8%), volume (for example, total body, -0.8±2.2%) and surface area (whole-body, -1.7±2.0%) estimates. By contrast, mean measurement differences were substantially larger for small structures (for example, forearm volume, 31.3±31.4%).

Low-cost 3D Kinect-based imaging systems have the potential for providing automated accurate anthropometric and related body measurements for relatively large components; further hardware and software developments may be able to improve system small-component resolution.

Mid-thigh cross-sectional muscle area (CSA), muscle attenuation, and greater trochanter soft tissue thickness have been shown to be independent risk factors of hip fracture. Our aim was to determine whether muscle and adipose tissue measures derived from dual-energy X-ray absorptiometry (DXA) scans would have a similar risk association as those measured using other imaging methods. Using a case-cohort study design, we identified 169 incident hip fracture cases over an average of 13.5 years among participants from the Health ABC Study, a prospective study of 3075 individuals initially aged 70 to 79 years. We modeled the thigh 3D geometry and compared DXA and computed tomography (CT) measures. DXA-derived thigh CSA, muscle attenuation, and subcutaneous fat thickness were found to be highly correlated to their CT counterparts (Pearson's r = 0.82, 0.45, and 0.91, respectively; p < 0.05). The fracture risk of men and women were calculated separately. We found that decreased subcutaneous fat, CT thigh muscle attenuation, and appendicular lean mass by height squared (ALM/Ht(2)) were associated with fracture risk in men; hazard ratios (HR) = 1.44 (1.02, 2.02), 1.40 (1.05, 1.85), and 0.58 (0.36, 0.91), respectively, after adjusting for age, race, clinical site, body mass index (BMI), chronic disease, hip bone mineral density (BMD), self-reported health, alcohol use, smoking status, education, physical activity, and cognitive function. In a similar model for women, only decreases in subcutaneous fat and DXA CSA were associated with hip fracture risk; HR = 1.39 (1.07, 1.82) and 0.78 (0.62, 0.97), respectively. Men with a high ALM/Ht(2) and low subcutaneous fat thickness had greater than 8 times higher risk for hip fracture compared with those with low ALM/Ht(2) and high subcutaneous fat. In women, ALM/Ht(2) did not improve the model when subcutaneous fat was included. We conclude that the DXA-derived subcutaneous fat thickness is a strong marker for hip fracture risk in both men and women, especially in men with high ALM/Ht(2).

To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections.

Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results.

The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections.

The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique.

Lymphedema is commonly assessed by measuring the increase in volume of the affected region using methods that are not only accurate and sensitive but also applicable for use in clinical practice. Opto-electronic volumetry (Perometer™) is a rapid and convenient technique recommended as a reference method for this purpose, while the use of dual-energy X-ray absorptiometry is becoming more common. We report here a method agreement study between DXA and perometry for the measurement of forearm volume.

Perometric measurements were performed on both whole arms, in the horizontal plane, of a group of healthy young participants. Perometric data were obtained for 4 and 5 mm slices between the malleoli to the anticubital fossa crease. The DXA-measured masses (bone mineral, fat, and lean) for the same forearm region were obtained using recently published algorithms. Perometric and DXA-measured volumes were compared using correlation and limits of agreement analysis.

DXA-computed volumes were highly and significantly correlated (r=0.986; p<0.0001) with those measured by perometry. The mean bias between the methods was extremely small; 0.7% underestimation by DXA with limits of agreement of 6.3 to -7.7% (DXA-perometry).

This study has demonstrated a high degree of concordance between DXA computed limb volumes and those measured by the reference method of perometry. The relatively small limits of agreement suggest that these methods can be used interchangeably.

Excess adiposity is the main phenotypic feature that defines human obesity and that plays a pathophysiological role in most chronic diseases. Measuring the amount of fat mass present is thus a central aspect of studying obesity at the individual and population levels. Nevertheless, a consensus is lacking among investigators on a single accepted 'reference' approach for quantifying fat mass in vivo. While the research community generally relies on the multi-component body volume class of 'reference' models for quantifying fat mass, no definable guide discerns among different applied equations for partitioning the four (fat, water, protein and mineral mass) or more quantified components, standardizes 'adjustment' or measurement system approaches for model-required labelled water dilution volumes and bone mineral mass estimates, or firmly establishes the body temperature at which model physical properties are assumed. The resulting differing reference strategies for quantifying body composition in vivo leads to small, but under some circumstances, important differences in the amount of measured body fat. Recent technological advances highlight opportunities to expand model applications to new subject groups and measured components such as total body protein. The current report reviews the historical evolution of multi-component body volume-based methods in the context of prevailing uncertainties and future potential.

To investigate the feasibility of breast tissue characterization in terms of water, lipid, and protein contents with a spectral computed tomographic (CT) system based on a cadmium zinc telluride (CZT) photon-counting detector by using postmortem breasts.

Nineteen pairs of postmortem breasts were imaged with a CZT-based photon-counting spectral CT system with beam energy of 100 kVp. The mean glandular dose was estimated to be in the range of 1.8-2.2 mGy. The images were corrected for pulse pile-up and other artifacts by using spectral distortion corrections. Dual-energy decomposition was then applied to characterize each breast into water, lipid, and protein contents. The precision of the three-compartment characterization was evaluated by comparing the composition of right and left breasts, where the standard error of the estimations was determined. The results of dual-energy decomposition were compared by using averaged root mean square to chemical analysis, which was used as the reference standard.

The standard errors of the estimations of the right-left correlations obtained from spectral CT were 7.4%, 6.7%, and 3.2% for water, lipid, and protein contents, respectively. Compared with the reference standard, the average root mean square error in breast tissue composition was 2.8%.

Spectral CT can be used to accurately quantify the water, lipid, and protein contents in breast tissue in a laboratory study by using postmortem specimens.

To investigate the feasibility of a three-material compositional measurement of water, lipid, and protein content of breast tissue with dual kVp cone-beam computed tomography (CT) for diagnostic purposes.

Simulations were performed on a flat panel-based computed tomography system with a dual kVp technique in order to guide the selection of experimental acquisition parameters. The expected errors induced by using the proposed calibration materials were also estimated by simulation. Twenty pairs of postmortem breast samples were imaged with a flat-panel based dual kVp cone-beam CT system, followed by image-based material decomposition using calibration data obtained from a three-material phantom consisting of water, vegetable oil, and polyoxymethylene plastic. The tissue samples were then chemically decomposed into their respective water, lipid, and protein contents after imaging to allow direct comparison with data from dual energy decomposition.

Guided by results from simulation, the beam energies for the dual kVp cone-beam CT system were selected to be 50 and 120 kVp with the mean glandular dose divided equally between each exposure. The simulation also suggested that the use of polyoxymethylene as the calibration material for the measurement of pure protein may introduce an error of -11.0%. However, the tissue decomposition experiments, which employed a calibration phantom made out of water, oil, and polyoxymethylene, exhibited strong correlation with data from the chemical analysis. The average root-mean-square percentage error for water, lipid, and protein contents was 3.58% as compared with chemical analysis.

The results of this study suggest that the water, lipid, and protein contents can be accurately measured using dual kVp cone-beam CT. The tissue compositional information may improve the sensitivity and specificity for breast cancer diagnosis.

Body shape is a known risk factor for diabetes and mortality, but the methods estimating body shape, BMI and waist circumference are crude. We determined whether a novel body shape measure, trunk to leg volume ratio, was independently associated with diabetes and mortality.

Data from the National Health and Nutritional Examination Survey 1999-2004, a study representative of the US population, were used to generate dual-energy X-ray absorptiometry-derived trunk to leg volume ratio and determine its associations to diabetes, metabolic covariates, and mortality by BMI category, gender, and race/ethnicity group.

The prevalence of pre-diabetes and diabetes increased with age, BMI, triglycerides, blood pressure, and decreased HDL level. After adjusting for covariates, the corresponding fourth to first quartile trunk to leg volume ratio odds ratios (OR) were 6.8 (95% confidence interval [CI], 4.9-9.6) for diabetes, 3.9 (95% CI, 3.0-5.2) for high triglycerides, 1.8 (95% CI, 1.6-2.1) for high blood pressure, 3.0 (95% CI, 2.4-3.8) for low HDL, 3.6 (95% CI, 2.8-4.7) for metabolic syndrome, and 1.76 (95% CI, 1.20-2.60) for mortality. Additionally, trunk to leg volume ratio was the strongest independent measure associated with diabetes (P<0.001), even after adjusting for BMI and waist circumference. Even among those with normal BMI, those in the highest quartile of trunk to leg volume ratio had a higher likelihood of death (5.5%) than those in the lowest quartile (0.2%). Overall, trunk to leg volume ratio is driven by competing mechanisms of changing adiposity and lean mass.

A high ratio of trunk to leg volume showed a strong association to diabetes and mortality that was independent of total and regional fat distributions. This novel body shape measure provides additional information regarding central adiposity and appendicular wasting to better stratify individuals at risk for diabetes and mortality, even among those with normal BMI.

Total body volume is an important health metric used to measure body density, shape, and multicompartmental body composition but is currently only available through underwater weighing or air displacement plethysmography (ADP). The objective of this investigation was to derive an accurate body volume from dual-energy X-ray absorptiometry (DXA)-reported measures for advanced body composition models. Volunteers received a whole body DXA scan and an ADP measure at baseline (N = 25) and 6 mo (N = 22). Baseline measures were used to calibrate body volume from the reported DXA masses of fat, lean, and bone mineral content. A second population (N = 385) from the National Health and Nutrition Examination Survey was used to estimate the test-retest precision of regional (arms, legs, head, and trunk) and total body volumes. Overall, we found that DXA-volume was highly correlated to ADP-volume (R² = 0.99). The 6-mo change in total DXA-volume was highly correlated to change in ADP-volume (R² = 0.98). The root mean square percent coefficient of variation precision of DXA-volume measures ranged from 1.1% (total) to 3.2% (head). We conclude that the DXA-volume method can measure body volume accurately and precisely, can be used in body composition models, could be an independent health indicator, and is useful as a prospective or retrospective biomarker of body composition.

Muscle wasting is a consequence of many primary conditions including sarcopenia, cachexia, osteoporosis, HIV/AIDS, and chronic kidney disease. Unfortunately, there is not a clinically accessible method to measure total body protein, which is the functional mass of muscle.

We sought to derive a simple method to measure total body protein by using dual-energy X-ray absorptiometry (DXA) and bioimpedance analysis (BIA).

We retrospectively analyzed a clinical convenience sample of individuals with numerous metabolic conditions from the Monash Medical Centre, Melbourne, Australia, who had a concurrent protein measure by using neutron activation analysis-derived protein (NAA-TBPro), water measure by using BIA, and whole-body DXA scan. The study was split into calibration and validation data sets by using simple random sampling stratified by sex, BMI category, and age decade. We generated a protein estimate direct-calibration protein (DC-TBPro) derived from BIA water, bone mass, and body volume. We compared NAA-TBPro with DC-TBPro and 2 protein estimates from the literature, one that used the DC-TBPro equation with fixed coefficients [4-compartment Lohman method for analysis of total body protein (4CL-TBPro)] and another that used fat-free mass, age, and sex [Wang equation-derived protein (W-TBPro)].

A total of 187 participants [119 women; mean (±SD) age: 37.0 ± 15.4 y; mean (±SD) BMI (in kg/m(2)) 24.5 ± 7.7] were included. When plotted against NAA-TBPro, DC-TBPro had the highest correlation [coefficient of determination (R(2)) = 0.87], lowest root mean squared error (RMSE; 0.87 kg), and fewest outliers compared with 4CL-TBPro (R(2) = 0.75; RMSE = 1.22 kg) and W-TBPro (R(2) = 0.80; RMSE = 1.10 kg).

A simple method to measure total body protein by using a DXA system and BIA unit was developed and compared with NAA as proof of principle. With additional validation, this method could provide a clinically useful way to monitor muscle-wasting conditions.

Obesity-related metabolic disorders are characterized by mild chronic inflammation, leukocyte infiltration, and tissue fibrosis as a result of adipocytokine production from the expanding white adipose tissue. Annexin A1 (AnxA1) is an endogenous glucocorticoid regulated protein, which modulates systemic anti-inflammatory processes and, therefore, may be altered with increasing adiposity in humans. Paradoxically, we found that plasma AnxA1 concentrations inversely correlated with BMI, total percentage body fat, and waist-to-hip ratio in human subjects. Plasma AnxA1 was also inversely correlated with plasma concentrations of the acute-phase protein, C-reactive protein (CRP), and the adipocytokine leptin, suggesting that as systemic inflammation increases, anti-inflammatory AnxA1 is reduced. In addition, AnxA1 gene expression and protein were significantly up-regulated during adipogenesis in a human adipocyte cell line compared to vehicle alone, demonstrating for the first time that AnxA1 is expressed and excreted from human adipocytes. These data demonstrate a failure in the endogenous anti-inflammatory system to respond to increasing systemic inflammation resulting from expanding adipose tissue, a condition strongly linked to the development of type 2 diabetes and cardiovascular disease. These data raise the possibility that a reduction in plasma AnxA1 may contribute to the chronic inflammatory phenotype observed in human obesity.