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This study addresses the pressing need for improved methods to predict lean mass in adults, and in particular lean body mass (LBM), appendicular lean mass (ALM), and appendicular skeletal muscle mass (ASMM) for the early detection and management of sarcopenia, a condition characterized by muscle loss and dysfunction. Sarcopenia presents significant health risks, especially in populations with chronic diseases like cancer and the elderly. Current assessment methods, primarily relying on Dual-energy X-ray absorptiometry (DXA) scans, lack widespread applicability, hindering timely intervention. Leveraging machine learning techniques, this research aimed to develop and validate predictive models using data from the National Health and Nutrition Examination Survey (NHANES) and the Action for Health in Diabetes (Look AHEAD) study. The models were trained on anthropometric data, demographic factors, and DXA-derived metrics to accurately estimate LBM, ALM, and ASMM normalized to weight. Results demonstrated consistent performance across various machine learning algorithms, with LassoNet, a non-linear extension of the popular LASSO method, exhibiting superior predictive accuracy. Notably, the integration of bone mineral density measurements into the models had minimal impact on predictive accuracy, suggesting potential alternatives to DXA scans for lean mass assessment in the general population. Despite the robustness of the models, limitations include the absence of outcome measures and cohorts highly vulnerable to muscle mass loss. Nonetheless, these findings hold promise for revolutionizing lean mass assessment paradigms, offering implications for chronic disease management and personalized health interventions. Future research endeavors should focus on validating these models in diverse populations and addressing clinical complexities to enhance prediction accuracy and clinical utility in managing sarcopenia.

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Thalassemia major is a genetic haemoglobinopathy manifesting as severe anaemia, jaundice and hepatosplenomegaly. Due to altered iron metabolism and increased bone resorption it is associated with secondary osteoporosis manifested as decreased bone mineral density (BMD). Dual energy X-ray absorptiometry (DXA) is frequently performed for the diagnosis of secondary osteoporosis. Soft tissues are rarely visualized on DXA unless there is calcification involving those structures like nephro-, cholelithiasis or iatrogenic e.g. surgical clips. Hepatic iron deposition occurs in thalassemia due to repeated blood transfusions which leads to increased density of the liver resulting in visualization of liver on DXA scan. We present an interesting image of hepatic visualization on DXA performed for bone mineral density assessment in a patient with thalassemia major.

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Bone mineral density (BMD) varies with aging and both systemic and local diseases; however, such evidence is lacking in feline medicine. This may be due to the need for general anesthesia in cats for direct BMD measurements using dual-energy X-ray absorptiometry (DXA) or quantitative computed tomography (QCT). In this study, computed digital absorptiometry (CDA), an indirect relative BMD-measuring method, was optimized to select an X-ray tube setting for the quantitative assessment of the feline knee joint. The knee joints of nine cats were radiographically imaged and processed using the CDA method with an aluminum density standard and five X-ray tube settings (from 50 to 80 kV; between 1.2 and 12 mAs). The reference attenuation of the X-ray beam for ten steps (S1-S10) of the density standard was recorded in Hounsfield units (HU), compared between X-ray tube settings, and used to determine the ranges of relative density applied for radiograph decomposition. The relative density decreased (p < 0.0001) with an increase in kV and dispersed with an increase in mAs. Then, the percentage of color pixels (%color pixels), representing ranges of relative density, was compared among S1-S10 and used for the recognition of background artifacts. The %color pixels was the highest for low steps and the lowest for high steps (p < 0.0001), regardless of X-ray tube settings. The X-ray tube setting was considered the most beneficial when it effectively covered the lowest possible HU ranges without inducing background artifacts. In conclusion, for further clinical application of the CDA method for quantitative research on knee joint OA in cats, 60 kV and 1.2 mAs settings are recommended.

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BACKGROUND: Osteoporosis is increasingly being recognized in children, mostly secondary to systemic underlying conditions or medication. However, no imaging modality currently provides a full evaluation of bone health in children. We compared DXA, a radiographic bone health index (BHI (BoneXpert) and cone-beam CT for the assessment of low bone mass in children with juvenile idiopathic arthritis (JIA). METHODS: Data used in the present study was drawn from a large multicentre study including 228 children aged 4-16 years, examined between 2015 and 2020. All had a radiograph of the left hand, a DXA scan and a cone-beam CT of the temporomandibular joints within four weeks of each other. For the present study, we included 120 subjects, selected based on DXA BMD and BoneXpert BHI to secure values across the whole range to be tested. RESULTS: One hundred and twenty children (60.0% females) were included, mean age 11.6 years (SD 3.1 years). There was a strong correlation between the absolute values of BHI and BMD for both total body less head (TBLH) (r = 0.75, p < 0.001) and lumbar spine (L1-L4) (r = 0.77, p < 0.001). The correlation between BHI standard deviation score (SDS) and BMD TBLH Z-scores was weak (r = 0.34) but significant (0 = 0.001), varying from weak (r = 0.31) to moderate (r = 0.42) between the three study sites. Categorizing BHI SDS and DXA BMD Z-scores on a 0-5 scale yielded a weak agreement between the two for both TBLH and LS, with w-kappa of 0.2, increasing to 0.3 when using quadratic weights. The agreement was notably higher for one of the three study sites as compared to the two others, particularly for spine assessment, yielding a moderate kappa value of 0.4 - 0.5. For cone-beam CT, based on a 1-3 scale, 59 out of 94 left TMJ's were scored as 1 and 31 as score 2 by the first observer vs. 87 and 7 by the second observer yielding a poor agreement (kappa 0.1). CONCLUSIONS: Categorizing DXA LS and automated radiographic Z-scores on a 0-5 scale gave a weak to moderate agreement between the two methods, indicating that a hand radiograph might provide an adjuvant tool to DXA when assessing bone health children with JIA, given thorough calibration is performed.

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Bone health is crucial at all stages of life. Several medical conditions and changes in lifestyle affect the growth, structure, and functions of bones. This may lead to the development of bone degenerative disorders, such as osteoporosis, osteoarthritis, rheumatoid arthritis, etc., which are major public health concerns worldwide. Accurate and reliable measurement and monitoring of bone health are important aspects for early diagnosis and interventions to prevent such disorders. Significant progress has recently been made in developing new sensing technologies that offer non-invasive, low-cost, and accurate measurements of bone health. In this review, we have described bone remodeling processes and common bone disorders. We have also compiled information on the bone turnover markers for their use as biomarkers in biosensing devices to monitor bone health. Second, this review details biosensing technology for bone health assessment, including the latest developments in various non-invasive techniques, including dual-energy X-ray absorptiometry, magnetic resonance imaging, computed tomography, and biosensors. Further, we have also discussed the potential of emerging technologies, such as biosensors based on nano- and micro-electromechanical systems and application of artificial intelligence in non-invasive techniques for improving bone health assessment. Finally, we have summarized the advantages and limitations of each technology and described clinical applications for detecting bone disorders and monitoring treatment outcomes. Overall, this review highlights the potential of emerging technologies for improving bone health assessment with the potential to revolutionize clinical practice and improve patient outcomes. The review highlights key challenges and future directions for biosensor research that pave the way for continued innovations to improve diagnosis, monitoring, and treatment of bone-related diseases.

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BACKGROUND: T-score measurement via dual-energy X-ray absorptiometry (DXA) is the gold standard for assessing and classifying the bone mineral density status of patients as normal, osteopenic, or osteoporotic according to the World Health Organization criteria. However, the diagnostic accuracy may be affected by the skeletal site selected for DXA. OBJECTIVES: Estimate the prevalence of femoral and lumbar BMD discordance in a community-based setting in Riyadh, Saudi Arabia. DESIGN: Cross-sectional. SETTING: Polyclinics at a tertiary care center. PATIENTS AND METHODS: This study included all patients aged ≥60 years who visited the Department of Family Medicine and underwent DXA screening between 2016 and 2022. MAIN OUTCOME MEASURES: Discordance was defined as a difference in BMD status between two skeletal sites. Minor discordance occurs when adjacent sites have different diagnoses; i.e., one site exhibits osteoporosis and the other exhibits osteopenia. In contrast, major discordance occurs when one site exhibits osteoporosis and the other exhibits normal BMD. SAMPLE SIZE: 1429 older adults. RESULTS: The study patients had a median age of 66 years (60-99, minimum-maximum). The prevalence of discordance was 41.6%, with major discordance present in 2.2% of patients and minor discordance in 39.4%. The distribution of discordance did not differ significantly among the sociodemographic factors. CONCLUSION: Discordance is prevalent among the Saudi geriatric population. During the analysis of DXA results, physicians should account for discordance when diagnosing and ruling out osteoporosis in high-risk patients. LIMITATIONS: All factors influencing discordance were not explored thoroughly; this study mainly focused on older adults. Furthermore, diverse age groups need to be investigated for a more comprehensive understanding of the analyzed factors.

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Background/Objectives: Osteoporosis is a common general disease that mostly affects the skeletal system, including the jawbone. There is a link between systemic and mandibular osteoporosis. This study aimed at assessing the association between systemic (lumbar spine L1-L4, femoral neck, total hip) bone mineral density (BMD) and mandible BMD sites in Romanian postmenopausal females. Methods: A total of 97 menopausal patients were studied, 62 with osteoporosis and 35 females with no osteoporosis. For each patient, dual-energy X-ray absorptiometry (DXA) assessments of BMD in the mandible, proximal femur, total hip, and lumbar spine (L1-L4) were performed. Mandibular measurements were performed using the distal forearm software, followed by manual analysis after the bone contour was defined in each case. Results: Comparing the osteoporosis and control groups, there were significant differences in BMD at each examined location. The mandibular BMD (1.125 ± 0.181506 g/cm2) in the osteoporosis group was considerably smaller than in the control group (1.35497 ± 0.244397 g/cm2). Correlations between the BMD at different sites were significant: lumbar spine and femoral neck (r = 0.738, p < 0.0001), lumbar spine and total hip (r = 0.735, p < 0.0001), lumbar spine and mandible (r = 0.506, p < 0.0001), femoral neck and total hip (r = 0.891, p < 0.0001), femoral neck and mandible (r = 0.482, p < 0.0001), and total hip and mandible (r = 0.466, p < 0.0001). Conclusions: There were correlations between mandible BMD and lumbar spine, femoral neck, and total hip BMD, suggesting that osteoporosis affects mandibular bone density. BMD assessments at common locations may help predict mandibular BMD and the probability of osteoporosis.

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BACKGROUND: The use of dual-energy X-ray absorptiometry (DEXA) and quantitative computed tomography (QCT) methods are important for the diagnosis and follow-up of osteoporosis, and are used especially in cases to determine the degree of osteoporosis and the risk of fracture, monitoring the effectiveness of the treatment applied. PURPOSE: To compare the parameters measured using the DEXA method from the lumbar (L1-L4) vertebrae and the Hounsfield unit (HU) values measured with QCT at the same levels among young adults and the elderly. MATERIAL AND METHODS: The study included 155 patients (age range = 26-93 years). A total of 57 (36.8%) patients (age range = 26-64 years) were defined as the first group, and 98 (63.2%) patients (aged ≥65 years) were defined as the second group. T-test and correlation analysis were performed to compare bone mineral density (BMD), T score, and HU values measured using DEXA and QCT. RESULTS: A statistically significant difference was found between T score, lumbar total BMD, and HU values according to age and sex (P < 0.05). When the values measured from lumbar vertebrae were compared using both DEXA and CT, a high correlation was found between them. CONCLUSION: In the study, it was observed that QCT attenuation measurements of the lumbar spine measured between different age groups provided reliable results in terms of BMD scanning, as in DEXA. It should be noted that QCT has a longer imaging time and higher radiation dose compared to DEXA, and unnecessary scans should be avoided.

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OBJECTIVES: To determine the association between radiologic joint damage (JD) and a lower lean body mass (LBM) in rheumatoid arthritis (RA) patients. METHODS: A cross-sectional study from a single center established RA cohort. JD and appendicular LBM (arms and legs) were measured with the Sharp/van der Heijde (SvdH) score and dual x-ray absorptiometry expressed as kg/m 2 , respectively. A univariable analysis was used to determine the association between JD an LBM; then, a multivariable regression model was performed to evaluate the persistence of this association, adjusted by age, gender, disease duration, socioeconomic status (by the Graffar method), tobacco use, anticitrullinated protein antibody levels, Disease Activity Score in 28 joints for RA with erythrocyte sedimentation rate, glucocorticoid use (as prednisone equivalent), disease-modifying antirheumatic drug use, body mass index, and disability (by the multidimensional Health Assessment Questionnaire). RESULTS: Two hundred forty-seven patients were included; the average (SD) age was 63.0 (12.8) years, disease duration 20 (15.00) years, the total SvdH was 66 (86.75), and the aLBM was 13.6 (3.82) kg/m 2 . In the univariable analysis, a lower appendicular LBM was associated with higher SvdH score on the female population, in terms of the total ( B = -8.6, p < 0.01), bone erosion (-4.4, p < 0.01), and joint space narrowing (-4.2, p < 0.01) scores; this correlation remained in the multivariable analysis in terms of total SvdH ( B = -9.5, p < 0.01), bone erosion (-5.2, p < 0.01), and joint space narrowing (-4.3, p < 0.01). CONCLUSIONS: A lower LBM in female patients was associated with more severe JD independently of other variables examined. Strategies aimed at preserving LBM could have a favorable impact on the course of disease.

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BACKGROUND: There is limited data with respect to body composition changes for laparoscopic sleeve gastrectomy (SG) and laparoscopic Roux-en-Y gastric bypass (RYGB). The objective of this study was to analyse changes in body composition between these two procedures during the first year after bariatric surgery. METHODS: A prospective study was performed in patients undergoing bariatric surgery at two tertiary hospitals between 2017 and 2023. Body composition was assessed with dual-energy x-ray absorptiometry immediately before surgery, and at 1-, 6-, 12-, 18- and 24-months post-operatively, with a subgroup analysis performed for patients who undertook a scan at 18- and 24-months. Total weight loss (TWL), body mass index (BMI), fat mass (FM), lean body mass (LBM) and bone mineral content (BMC) parameters were compared between SG and RYGB. RESULTS: Forty-five patients were included in this series (SG n = 30, RYGB n = 15). There was a significant reduction in mean %TWL of 26.94 ± 8.86% and mean BMI of 11.12 ± 3.70 kg/m2 over 12-months. LBM accounted for 17.8% of TWL over 12-months, SG and RYGB did not differ in terms of loss of FM or LBM. For both procedures, the loss of LBM appeared to plateau at 6-months post-operatively. The only statistically significant finding between the two procedures was that RYGB resulted in an additional 0.06 kg loss compared with SG. CONCLUSION: SG and RYGB have been shown to have comparable weight loss and body composition changes in the short-to-medium term following surgery. LBM reduction was most significant in the early post-operative period across the entire cohort.

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To tackle the burden of obesity-induced cardiometabolic disease, the scientific community relies on accurate and reproducible adiposity measurements in the clinic. These measurements guide our understanding of underlying biological mechanisms and clinical outcomes of human trials. However, measuring adiposity and adipose tissue distribution in a clinical setting can be challenging, and different measurement methods pose important limitations. BMI is a simple and high-throughput measurement, but it is associated relatively poorly with clinical outcomes when compared with waist-to-hip and sagittal abdominal diameter measurements. Body composition measurements by dual energy X-ray absorptiometry or MRI scans would be ideal due to their high accuracy, but are not high-throughput. Another important consideration is that adiposity measurements vary between men and women, between adults and children, and between people of different ethnic backgrounds. In this Perspective article, we discuss how these critical challenges can affect our interpretation of research data in the field of obesity and the design and implementation of clinical guidelines.

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OBJECTIVES: To evaluate a novel calcium-only imaging technique (VCa) with subtracted bone marrow in osteoporosis in dual-layer CT (DLCT) compared to conventional CT images (CI) and dual-energy X-ray absorptiometry (DXA). MATERIAL AND METHODS: Images of a multi-energy CT phantom with calcium inserts, quantitative CT calibration phantom, and of 55 patients (mean age: 64.6 ± 11.5 years) were acquired on a DLCT to evaluate bone mineral density (BMD). CI, calcium-suppressed images, and VCa were calculated. For investigating the association of VCa and CI with DXA a subsample of 30 patients (<90 days between DXA and CT) was used. Multiple regression analysis was performed to identify further factors improving the prediction of DXA BMD. RESULTS: The calcium concentrations of the CT phantom inserts were significantly associated with CT numbers from VCa (R2 = 0.94) and from CI (R2 = 0.89-0.92). VCa showed significantly higher CT numbers than CI in the phantom (p ≤ 0.001) and clinical setting (p < 0.001). CT numbers from VCa were significantly associated with CI (R2 = 0.95, p < 0.001) and with DXA (R2 = 0.31, p = 0.007), whereas no significant association between DXA and CI was found. Prediction of DXA BMD based on CT numbers derived from VCa yielded R2 = 0.76 in multiple regression analysis. ROC for the differentiation of normal from pathologic BMD in VCa yielded an AUC of 0.7, and a cut-off value of 126HU (sensitivity: 0.90; specificity: 0.47). CONCLUSION: VCa images showed better agreement with DXA and known calcium concentrations than CI, and could be used to estimate BMD. A VCa cut-off of 126HU could be used to identify abnormal bone mineral density.

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Osteoporotic fractures, also known as fragility fractures, are reflective of compromised bone strength and are associated with significant morbidity and mortality. Such fractures may be clinically silent, and others may present clinically with pain and deformity at the time of the injury. Unfortunately, and even at the time of detection, most individuals sustaining fragility fractures are not identified as having underlying metabolic bone disease and are not evaluated or treated to reduce the incidence of future fractures. A multidisciplinary international working group with representation from international societies dedicated to advancing the care of patients with metabolic bone disease has developed best practice recommendations for the diagnosis and evaluation of individuals with fragility fractures. A comprehensive narrative review was conducted to identify key articles on fragility fractures and their impact on the incidence of further fractures, morbidity, and mortality. This document represents consensus among the supporting societies and harmonizes best practice recommendations consistent with advances in research. A fragility fracture in an adult is an important predictor of future fractures and requires further evaluation and treatment of the underlying osteoporosis. It is important to recognize that most fragility fractures occur in patients with bone mineral density T scores higher than -2.5, and these fractures confirm the presence of skeletal fragility even in the presence of a well-maintained bone mineral density. Fragility fractures require further evaluation with exclusion of contributing factors for osteoporosis and assessment of clinical risk factors for fracture followed by appropriate pharmacological intervention designed to reduce the risk of future fracture. Because most low-trauma vertebral fractures do not present with pain, dedicated vertebral imaging and review of past imaging is useful in identifying fractures in patients at high risk for vertebral fractures. Given the importance of fractures in confirming skeletal fragility and predicting future events, it is recommended that an established classification system be used for fracture identification and reporting.

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With the aging of the population in our society, osteoporosis (OP) has become one of the chronic diseases that seriously threaten the physical health of the elderly, leading to a heavy burden on healthcare. In recent years, with the continuous development of dual-energy CT (DECT) technology, quantitative measurements of DECT parameters, which is highly sensitive to OP, provides accurate results, is convenient and cost-effective, and is expected to be widely used in bone density testing. This study was aimed to explore the value of quantitative measurements of DECT parameters in diagnosing OP, in order to better guide clinical judgments and treatment. A total of 187 patients who underwent dual-energy X-ray and DECT examinations at Tianjin hospital between January 2022 and June 2023 were included as participants in this study. The bone mineral density (BMD) values of the lumbar spine (L1-L4) were determined using dual-energy X-ray absorptiometry. Simultaneously, CT scans of the lumbar spine (L1-L4) were conducted to measure the CT values of contrast media (CM), mixed-energy image CT values (regular CT value [rCT]), calcium concentration (CaD), as well as fat fraction (FF). Pearson correlation analysis was used to examine the relationship between the quantitative measurements of L1 to L4 vertebral bodies obtained from DECT and BMD. The values of CM, rCT, and CaD in the OP group were all lower than those in the non-OP group with statistical significance (P < .001). Conversely, the fat fraction parameter value in the OP group was significantly higher in contrast with the non-OP group (P = .004); there was a positive correlation between CM, rCT, CaD, and BMD values (R = 0.579, P < .001; R = 0.604, P < .001; R = 0.563, P < .001); CM, rCT, and CaD had high diagnostic value for OP, as evidenced by AUCs of 0.935 (95% CI: 0.900-0.971), 0.956 (95% CI: 0.925-0.987), and 0.926 (95% CI: 0.858-0.954), respectively, all with P values < .001. Quantitative measurement of DECT parameters showed a high sensitivity as well as a high specificity in the diagnosis of OP. It is also highly feasible and holds significant clinical diagnostic value, making it a suitable candidate for widespread application.

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BACKGROUND: Trimethylamine-N-oxide (TMAO) is linked with obesity, while limited evidence on its relationship with body fat distribution. Herein, we investigated the associations between serum TMAO and longitudinal change of fat distribution in this prospective cohort study. METHODS: Data of 1964 participants (40-75y old) from Guangzhou Nutrition and Health Study (GNHS) during 2008-2014 was analyzed. Serum TMAO concentration was quantified by HPLC-MS/MS at baseline. The body composition was assessed by dual-energy X-ray absorptiometry at each 3-y follow-up. Fat distribution parameters were fat-to-lean mass ratio (FLR) and trunk-to-leg fat ratio (TLR). Fat distribution changes were derived from the coefficient of linear regression between their parameters and follow-up duration. RESULTS: After an average of 6.2-y follow-up, analysis of covariance (ANCOVA) and linear regression displayed women with higher serum TMAO level had greater increments in trunk FLR (mean ± SD: 1.47 ± 4.39, P-trend = 0.006) and TLR (mean ± SD: 0.06 ± 0.24, P-trend = 0.011). Meanwhile, for women in the highest TMAO tertile, linear mixed-effects model (LMEM) analysis demonstrated the annual estimated increments (95% CI) were 0.03 (95% CI: 0.003 - 0.06, P = 0.032) in trunk FLR and 1.28 (95% CI: -0.17 - 2.73, P = 0.083) in TLR, respectively. In men, there were no similar significant observations. Sensitivity analysis yielded consistent results. CONCLUSION: Serum TMAO displayed a more profound correlation with increment of FLR and TLR in middle-aged and older community-dwelling women in current study. More and further studies are still warranted in the future. TRIAL REGISTRATION: NCT03179657.

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The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment. However, previous studies showed the possibility of classifying people living with obesity according to their VAT through blood chemical concentrations by applying machine learning techniques. In addition, most of the efforts were spent on men living with obesity while little was done for women. Therefore, this study aims to compare the performance of the multilinear regression model (MLR) in estimating VAT and six different supervised machine learning classifiers, including logistic regression (LR), support vector machine and decision tree-based models, to categorize 149 women living with obesity. For clustering, the study population was categorized into classes 0, 1, and 2 according to their VAT and the accuracy of each MLR and classification model was evaluated using DXA-data (DXAdata), blood chemical concentrations (BLDdata), and both DXAdata and BLDdata together (ALLdata). Estimation error and R 2 were computed for MLR, while receiver operating characteristic (ROC) and precision-recall curves (PR) area under the curve (AUC) were used to assess the performance of every classification model. MLR models showed a poor ability to estimate VAT with mean absolute error ≥ 401.40 and R 2 ≤ 0.62 in all the datasets. The highest accuracy was found for LR with values of 0.57, 0.63, and 0.53 for ALLdata, DXAdata, and BLDdata, respectively. The ROC AUC showed a poor ability of both ALLdata and DXAdata to distinguish class 1 from classes 0 and 2 (AUC = 0.31, 0.71, and 0.85, respectively) as also confirmed by PR (AUC = 0.24, 0.57, and 0.73, respectively). However, improved performances were obtained when applying LR model to BLDdata (ROC AUC ≥ 0.61 and PR AUC ≥ 0.42), especially for class 1. These results seem to suggest that, while a direct and reliable estimation of VAT was not possible in our cohort, blood sample-derived information can robustly classify women living with obesity by machine learning-based classifiers, a fact that could benefit the clinical practice, especially in those health centres where medical imaging devices are not available. Nonetheless, these promising findings should be further validated over a larger population.

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BACKGROUND: In an ageing population, low impact fragility fractures are becoming increasingly common. However, fracture risk can be reduced where low bone density can be identified at an early stage. In this study we aim to demonstrate that IBEX Bone Health (IBEX BH) can provide a clinically useful prediction from wrist radiographs of aBMD and T-score at the ultra-distal (UD) and distal-third (DT) regions of the radius. METHODS: A 261-participant single-centre, non-randomised, prospective, study was carried out to compare a) IBEX BH, a quantitative digital radiography software device, to b) Dual-energy X-ray Absorptiometry (DXA). A total of 257 participants with wrist digital radiograph (DR), forearm DXA pairs were included in the analysis after exclusions. RESULTS: The adjusted R2 value for IBEX BH outputs to the radial areal bone mineral density (aBMD) produced by a GE Lunar DXA system for the UD region is 0.87 (99% Confidence Interval (CI) [0.84, 0.89]). The adjusted R2 value for IBEX BH outputs to aBMD for the DT region is 0.88 (99% CI [0.85, 0.90]). The Area Under the Receiver Operating Characteristic curve (AUC) for the forearm T-score ≤ - 2.5 risk prediction model at the UD region is 0.95 (99% CI [0.93, 0.98]). The AUC for the forearm T-score ≤ - 2.5 risk prediction model at the DT region is 0.98 (99% CI [0.97, 0.99]). CONCLUSION: From a DR of the wrist, IBEX BH provides a clinically useful i) estimate of aBMD at the two regions of interest on the radius and ii) risk prediction model of forearm T-score ≤ - 2.5 at the UD and DT regions.

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The Microsoft Kinect depth sensor, with its built-in software that automatically captures joint coordinates without markers, could be a potential tool for ergonomic studies. This study investigates the performance of Kinect in limb segment lengths using dual-energy X-ray absorptiometry (DXA) as a reference. Healthy children and adults (n = 76) were recruited for limb length measurements by Kinect and DXA. The results showed consistent ratios of arm, forearm, thigh, and leg lengths to height, which were 0.16, 0.14, 0.23, and 0.22 respectively, for both age groups and methods. Kinect exhibited perfect correlation among all limb lengths, indicating fixed proportions assumed by its algorithm. Comparing the two methods, there was a strong correlation (R = 0.850-0.985) and good to excellent agreement (ICC = 0.829-0.977), except for the right leg in adults, where agreement was slightly lower but still moderate (ICC = 0.712). The measurement bias between the methods ranged from - 1.455 to 0.536 cm. In conclusion, Kinect yields outcomes similar to DXA, indicating its potential utility as a tool for ergonomic studies. However, the built-in algorithm of Kinect assumes fixed limb proportions for individuals, which may not be ideal for studies focusing on investigating limb discrepancies or anatomical differences.

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Osteoporosis is the most prevalent skeletal disorder, a condition that is associated with significant social and healthcare burden. In the elderly, osteoporosis is commonly associated with sarcopenia, further increasing the risk of fracture. Several imaging techniques are available for a non-invasive evaluation of osteoporosis and sarcopenia. This review focuses on dual-energy X-ray absorptiometry (DXA), as this technique offers the possibility to evaluate bone mineral density and body composition parameters with good precision and accuracy. DXA is also able to evaluate the amount of aortic calcification for cardiovascular risk estimation. Additionally, new DXA-based parameters have been developed in recent years to further refine fracture risk estimation, such as the Trabecular Bone Score and the Bone Strain Index. Finally, we describe the recent advances of a newly developed ultrasound-based technology known as Radiofrequency Echographic Multi-Spectrometry, which represent the latest non-ionizing approach for osteoporosis evaluation at central sites.

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