Bidirectional mediation of bone mineral density and brain atrophy on their associations with gait variability.

This mediation analysis aimed to investigate the associations among areal bone mineral density, mobility-related brain atrophy, and specific gait patterns. A total of 595 participants from the Taizhou Imaging Study, who underwent both gait and bone mineral density measurements, were included in this cross-sectional analysis. We used a wearable gait tracking device to collect quantitative gait parameters and then summarized them into independent gait domains with factor analysis. Bone mineral density was measured in the lumbar spine, femoral neck, and total hip using dual-energy X-ray absorptiometry. Magnetic resonance images were obtained on a 3.0-Tesla scanner, and the volumes of brain regions related to mobility were computed using FreeSurfer. Lower bone mineral density was found to be associated with higher gait variability, especially at the site of the lumbar spine (ß = 0.174, FDR = 0.001). Besides, higher gait variability was correlated with mobility-related brain atrophy, like the primary motor cortex (ß = 0.147, FDR = 0.006), sensorimotor cortex (ß = 0.153, FDR = 0.006), and entorhinal cortex (ß = 0.106, FDR = 0.043). Bidirectional mediation analysis revealed that regional brain atrophy contributed to higher gait variability through the low lumbar spine bone mineral density (for the primary motor cortex, P = 0.018; for the sensorimotor cortex, P = 0.010) and the low lumbar spine bone mineral density contributed to higher gait variability through the primary motor and sensorimotor cortices (P = 0.026 and 0.010, respectively).

Prevalence of Sarcopenia and Its Defining Components in Non-alcoholic Fatty Liver Disease Varies According to the Method of Assessment and Adjustment: Findings from the UK Biobank.

Sarcopenia may increase non-alcoholic fatty liver disease (NAFLD) risk, but prevalence likely varies with different diagnostic criteria. This study examined the prevalence of sarcopenia and its defining components in adults with and without NAFLD and whether it varied by the method of muscle mass assessment [bioelectrical impedance (BIA) versus dual-energy X-ray absorptiometry (DXA)] and adjustment (height2 versus BMI). Adults (n = 7266) in the UK Biobank study (45-79 years) with and without NAFLD diagnosed by MRI, were included. Sarcopenia was defined by the 2018 European Working Group on Sarcopenia in Older People definition, with low appendicular skeletal muscle mass (ASM) assessed by BIA and DXA and adjusted for height2 or BMI. Overall, 21% of participants had NAFLD and the sex-specific prevalence of low muscle strength (3.6-7.2%) and sarcopenia (0.1-1.4%) did not differ by NAFLD status. However, NAFLD was associated with 74% (males) and 370% (females) higher prevalence of low ASM when adjusted for BMI but an 82% (males) to 89% (females) lower prevalence when adjusted for height2 (all P < 0.05). The prevalence of impaired physical function was 40% (males, P = 0.08) to 123% (females, P < 0.001) higher in NAFLD. In middle-aged and older adults, NAFLD was not associated with a higher prevalence of low muscle strength or sarcopenia but was associated with an increased risk of impaired physical function and low muscle mass when adjusted for BMI. These findings support the use of adiposity-based adjustments when assessing low muscle mass and the assessment of physical function in NAFLD.

A Study on Intelligent Optical Bone Densitometry.

Osteoporosis is a prevalent chronic disease worldwide, particularly affecting the aging population. The gold standard diagnostic tool for osteoporosis is Dual-energy X-ray Absorptiometry (DXA). However, the expensive cost of the DXA machine and the need for skilled professionals to operate it restrict its accessibility to the general public. This paper builds upon previous research and proposes a novel approach for rapidly screening bone density. The method involves utilizing near-infrared light to capture local body information within the human body. Deep learning techniques are employed to analyze the obtained data and extract meaningful insights related to bone density. Our initial prediction, utilizing multi-linear regression, demonstrated a strong correlation (r = 0.98, p-value = 0.003**) with the measured Bone Mineral Density (BMD) obtained from Dual-energy X-ray Absorptiometry (DXA). This indicates a highly significant relationship between the predicted values and the actual BMD measurements. A deep learning-based algorithm is applied to analyze the underlying information further to predict bone density at the wrist, hip, and spine. The prediction of bone densities in the hip and spine holds significant importance due to their status as gold-standard sites for assessing an individual's bone density. Our prediction rate had an error margin below 10% for the wrist and below 20% for the hip and spine bone density.

Raman spectroscopic analysis for osteoporosis identification in humans with hip fractures.

Osteoporosis is a significant health concern. While multiple techniques have been utilized to diagnose this condition, certain limitations still persist. Raman spectroscopy has shown promise in predicting bone strength in animal models, but its application to humans requires further investigation. In this study, we present an in vitro approach for predicting osteoporosis in 10 patients with hip fractures using Raman spectroscopy. Raman spectra were acquired from exposed femoral heads collected during surgery. Employing a leave-one-out cross-validated linear discriminant analysis (LOOCV-LDA), we achieved accurate classification (90 %) between osteoporotic and osteopenia groups. Additionally, a LOOCV partial least squares regression (PLSR) analysis based on the complete Raman spectra demonstrated a significant prediction (r2 = 0.84, p < 0.05) of bone mineral density as measured by dual X-ray absorptiometry (DXA). To the best of our knowledge, this study represents the first successful demonstration of Raman spectroscopy correlating with osteoporotic status in humans.

Resistance training presents beneficial effects on bone development of adolescents engaged in swimming but not in impact sports: ABCD Growth Study.

BACKGROUND: Sports practice during adolescence is important to enhance bone development, although it may provide different effects depending on the mechanical impact present in the sport. Besides, resistance training (RT) may also induce bone changes directly (via muscle contractions) and indirectly (via myokines). However, there have been no studies analyzing the longitudinal influence of engaging in sport with and without added mechanical load. Thus, this study aims to analyze the combined effects of sports participation and resistance training on areal bone mineral density (aBMD) accrual in adolescent athletes participating in swimming and impact sports for 12-months. METHODS: This was a 12-month longitudinal study. The sample comprised 91 adolescents (21 females) aged 10 to 18 years, engaged in impact sports (basketball, tennis, track & field, baseball and gymnastics, n = 66) and non-impact sport (swimming, n = 25). The sample was divided according to resistance training participation: impact sports only (n = 45), impact sports + resistance training (n = 21), swimming-only (n = 17) and swimming + resistance training (n = 8). aBMD and soft tissues were measured using dual-energy X-ray absorptiometry. Generalized linear models analysis was used for the resistance training (RT) x type of sport interaction in predicting aBMD changes overtime, adjusting for maturation, sex and baseline aBMD. RESULTS: After 12-months, all groups showed a significant increase in aBMD, except for the swimming groups (regardless of resistant training), which showed a significant loss in spine aBMD (-0.045 [-0.085 to -0.004] g/cm2 in swimming-only and - 0.047 [-0.073 to -0.021] g/cm2 in swimming + RT). In comparisons between groups, only swimming + RT group, compared with swimming-only group presented higher upper limbs aBMD (0.096 g/cm2 [0.074 to 0.118] in swimming + RT vs. 0.046 [0.032 to 0.060] g/cm2 in swimming only; p < 0.05) and whole body less head (WBLH) aBMD (0.039 [0.024 to 0.054] g/cm2 in swimming + RT vs. 0.017 [0.007 to 0.027] g/cm2 swimming-only; p < 0.05). CONCLUSION: Despite the significant gain in aBMD in all groups and body sites after 12-months, except for the spine site of swimmers, the results indicate that participation in RT seems to improve aBMD accrual in swimmers at the upper limbs and WBLH.

Fat-free mass predictive equation using bioelectrical impedance and maturity offset in adolescent athletes: Development and cross-validation.

OBJECTIVES: This is a cross-sectional study, aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using single-frequency bioelectrical impedance (BIA), considering the predicted age at peak height velocity (PHV) as a variable. Additionally, the study aims to test the FFM-BIA obtained using a previous predictive equation that used skeletal maturity as a variable. METHOD: The participants (n = 169 male adolescent athletes) were randomly divided into two groups: development of a new predictive equation (n = 113), and cross-validation (n = 56). The concordance test between the FFM values obtained by Koury et al. predictive equation and DXA data was determined (n = 169). Bioelectrical data was obtained using a single-frequency analyzer. RESULTS: Among the models tested, the new predictive equation has resistance index (height2/resistance) and predictive age at PHV as variables and presented R2 = 0.918. The frequency of maturity status using skeletal maturity and PHV diagnosis was inadequate (Kappa = 0.4257; 95%CI = 0.298-0.553). Bland-Altman plots and concordance correlation coefficient showed substantial concordance between the FFM-DXA values (48.8 ± 11.2 kg) and the new predictive equation (CCC = 0.960). The results showed that the new equation performed better than the equation developed by Koury et al. (CCC = 0.901). CONCLUSIONS: Our results show that it is feasible to predict FFM in male adolescent athletes using predictive age at PHV, with moderate concordance. The calculation of FFM using more economical and less complex variables is viable and should be further explored.

Emergence of imaging technology beyond the clinical setting: Utilization of mobile health tools for at-home testing.

Body composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessibility and cost remain barriers to widespread adoption. The integration of AI-powered image analysis may help explain tissue differentiation, whereas mobile health apps offer real-time metabolic monitoring and personalized feedback. New apps such as MeThreeSixty and Made Health and Fitness offer the advantages of clinic-based imaging techniques from the comfort of home. These innovations hold the potential for individualizing strategies and interventions, optimizing clinical outcomes, and empowering informed decision-making for both healthcare professionals and patients/clients. Navigating the intricacies of these emerging tools, critically assessing their validity and reliability, and ensuring inclusivity across diverse populations and conditions will be crucial in harnessing their full potential. By integrating advancements in body composition assessment, healthcare can move beyond the limitations of traditional methods and deliver truly personalized, data-driven care to optimize well-being.

Bone mineral density, turnover, and microarchitecture assessed by second-generation high-resolution peripheral quantitative computed tomography in patients with Sheehan's syndrome.

Sheehan's syndrome (SS) is a rare but well-characterized cause of hypopituitarism. Data on skeletal health is limited and on microarchitecture is lacking in SS patients. PURPOSE: We aimed to explore skeletal health in SS with bone mineral density (BMD), turnover, and microarchitecture. METHODS: Thirty-five patients with SS on stable replacement therapy for respective hormone deficiencies and 35 age- and BMI-matched controls were recruited. Hormonal profile and bone turnover markers (BTMs) were measured using electrochemiluminescence assay. Areal BMD and trabecular bone score were evaluated using DXA. Bone microarchitecture was assessed using a second-generation high-resolution peripheral quantitative computed tomography. RESULTS: The mean age of the patients was 45.5 ± 9.3 years with a lag of 8.3 ± 7.2 years prior to diagnosis. Patients were on glucocorticoid (94%), levothyroxine (94%), and estrogen-progestin replacement (58%). None had received prior growth hormone (GH) replacement. BTMs (P1NP and CTX) were not significantly different between patients and controls. Osteoporosis (26% vs. 16%, p = 0.01) and osteopenia (52% vs. 39%, p = 0.007) at the lumbar spine and femoral neck (osteoporosis, 23% vs. 10%, p = 0.001; osteopenia, 58% vs. 29%, p = 0.001) were present in greater proportion in SS patients than matched controls. Bone microarchitecture analysis revealed significantly lower cortical volumetric BMD (vBMD) (p = 0.02) at the tibia, with relative preservation of the other parameters. CONCLUSION: Low areal BMD (aBMD) is highly prevalent in SS as compared to age- and BMI-matched controls. However, there were no significant differences in bone microarchitectural measurements, except for tibial cortical vBMD, which was lower in adequately treated SS patients.

Differences in Vertebral Morphology and bone Mineral Density between Grade 1 Vertebral Fracture and Non-Fractured Participants in the Chinese Population.

PURPOSE: To investigate the difference in vertebral morphology and bone mineral density (BMD) between grade 1 VFs and non-fractured participants in the Chinese population to shed light on the clinical significance of grade 1 VFs from various perspectives. METHODS: This retrospective cohort study included patients who received a chest low-dose computed tomography (LDCT) scan for health examination and visited the First Affiliated Hospital of Zhengzhou University, Henan, China, from October 2019 to August 2022. Data were analyzed from March 2023 to July 2023. The main outcome of this study was the difference in morphological parameters and BMD between grade 1 VFs and non-fractured participants. The prevalence of grade 1 VFs in China populations was calculated. The difference in BMD of three fracture types in the Grade 1 group was also evaluated. RESULTS: A total of 3652 participants (1799 males, 54.85 ± 9.02 years, range, 40-92 years; 1853 females, 56.00 ± 9.08 years, range, 40-93 years) were included. The prevalence of grade 2 and 3 increase with age. The prevalence of grade 1 VFs gradually increases ≤ 50y to 60-69y group, but there is a decrease in the ≥ 70 years male group (6.6%) and a rise in the female group (25.5%). There was no significant statistical difference observed in vertebral shape indices (VSI) and BMD between the Grade 1 group and the no-fractured group aged < 50 years old except the wedge index in male. The biconcavity index did not differ between the non-fractured group and the Grade 1 group in men aged 50-59 years, whereas a significant statistical difference was observed in women. Additionally, the results of BMD were consistent with these findings. For the 40-59 years age group, there were significant differences between the compression deformity group and the other groups. CONCLUSIONS: The grade 1 group had higher VSI and lower BMD than the non-fractured group, suggesting an association between the Grade 1 group and osteoporosis in individuals aged over 50 for women and over 60 for men. Different fracture types have significant variations in BMD among middle-aged people. The prevalence of grade 1 VFs exhibits an age-related increase in both genders, with opposite trends observed between older males and females. We suggested VSI can aid physicians in the diagnosis of grade 1 VFs.

Effects of kinect-based virtual reality training on bone mineral density and fracture risk in postmenopausal women with osteopenia: a randomized controlled trial.

Osteopenia is a condition characterized by low bone mineral density (BMD) that increases fracture risk, particularly among postmenopausal women (PMW). This study aimed to determine the effects of Kinect-based VRT on BMD and fracture risk in PMW with osteopenia. The study was a prospective, two-arm, parallel-design, randomized controlled trial. The study enrolled 52 participants, 26 randomly assigned to each group. In the experimental group, Kinect-based VRT was provided thrice weekly for 24 weeks for 45 min/session. Both groups were instructed to engage in a daily 30-min walk outdoors. The fracture risk assessment tool (FRAX) was used to calculate fracture risk, and dual-energy X-ray absorptiometry was used to measure lumbar spine and femur neck BMD. Both variables were assessed at baseline and 24 weeks afterwards. After 24 weeks of Kinect-based VRT, the experimental group showed significant BMD increases in the right and left femoral necks and lumbar spine (p value < 0.001). In the control group, the BMD at the right and left femoral necks showed fewer significant changes (p value < 0.022 and 0.004, respectively). In the control group, lumbar spine BMD did not change (p = 0.57). The experimental group showed significantly lower FRAX scores for hip fracture prediction (HFP) and hip prediction of major osteoporotic (HPMO) at both femoral necks (p value < 0.001) than the control group (p = 0.05 and p = 0.01, respectively), but no significant change at the left femoral neck for HFP (p = 0.66) or HPMO (p = 0.26). These findings indicate that a Kinect-based VRT intervention resulted in significantly increased BMD and a reduced fracture risk, as predicted by HFP and HPMO measurements. These improvements were more pronounced in the experimental group than in the control group. Thus, Kinect-based VRT may be utilized as an effective intervention to improve BMD and reduce fracture risk in postmenopausal women with osteopenia.

Impact of metabolic syndrome on bone mineral density in men over 50 and postmenopausal women according to U.S. survey results.

Metabolic Syndrome (MetS) and bone mineral density (BMD) have shown a controversial link in some studies. This research aims to study their association in males over 50 and postmenopausal females using National Health and Nutrition Examination Survey (NHANES) data. Postmenopausal females and males over 50 were included in the study. MetS was defined by the National Cholesterol Education Program Adult Treatment Panel III guidelines. BMD values were measured at the thoracic spine, lumbar spine, and pelvis as the primary outcome. Weighted multivariate general linear models have been employed to explore the status of BMD in patients with MetS. Additionally, interaction tests and subgroup analyses were conducted. Utilizing the NHANES database from 2003 to 2006 and 2011-2018, we included 1924 participants, with 1029 males and 895 females. In postmenopausal women, after adjusting for covariates, we found a positive correlation between MetS and pelvic (ß: 0.030 [95%CI 0.003, 0.06]) and thoracic (ß: 0.030 [95%CI 0.01, 0.06]) BMD, though not for lumbar spine BMD (ß: 0.020 [95%CI - 0.01, 0.05]). In males over 50 years old, MetS was positively correlated with BMD in both Model 1 (without adjusting for covariates) and Model 2 (considering age and ethnicity). Specifically, Model 2 revealed a positive correlation between MetS and BMD at the pelvis (ß: 0.046 [95%CI 0.02, 0.07]), thoracic spine (ß: 0.047 [95%CI 0.02, 0.07]), and lumbar spine (ß: 0.040 [95%CI 0.02, 0.06]). Subgroup analysis demonstrated that the relationship between MetS and BMD remained consistent in all strata, underscoring the stability of the findings. In postmenopausal women, after adjusting for all covariates, a significant positive correlation was observed between MetS and BMD in the pelvis and thoracic spine, whereas this correlation was not significant for lumbar spine BMD. Conversely, in males, positive correlations between MetS and BMD at the lumbar spine, thoracic spine, and pelvis were identified in Model 2, which adjusted for age and ethnicity; however, these correlations disappeared after fully adjusting for all covariates. These findings highlight the potential moderating role of gender in the impact of MetS on BMD.

Bone health index in the assessment of bone health: The Generation R Study.

Bone Health Index (BHI) has been proposed as a useful instrument for assessing bone health in children. However, its relationship with fracture risk remains unknown. We aimed to investigate whether BHI is associated with bone mineral density (BMD) and prevalent fracture odds in children from the Generation R Study. We also implemented genome-wide association study (GWAS) and polygenic score (PGS) approaches to improve our understanding of BHI and its potential. In total, 4150 children (49.4 % boys; aged 9.8 years) with genotyped data and bone assessments were included in this study. BMD was measured across the total body (less head following ISCD guidelines) using a GE-Lunar iDXA densitometer; and BHI was determined from the hand DXA scans using BoneXpert®. Fractures were self-reported collected with home questionnaires. The association of BHI with BMD and fractures was evaluated using linear models corrected for age, sex, ethnicity, height, and weight. We observed a positive correlation between BHI and BMD (ρ = 0.32, p-value<0.0001). Further, every SD decrease in BHI was associated with an 11 % increased risk of prevalent fractures (OR:1.11, 95 % CI 1.00-1.24, p-value = 0.05). Our BHI GWAS identified variants (lead SNP rs1404264-A, p-value = 2.61 × 10-14) mapping to the ING3/CPED1/WNT16 locus. Children in the extreme tails of the BMD PGS presented a difference in BHI values of -0.10 standard deviations (95% CI -0.14 to -0.07; p-value<0.0001). On top of the demonstrated epidemiological association of BHI with both BMD and fracture risk, our results reveal a partially shared biological background between BHI and BMD. These findings highlight the potential value of using BHI to screen children at risk of fracture.

Impaired muscle parameters in adults with mild to severe types of osteogenesis imperfecta: a cross-sectional study.

Impaired muscle parameters may further compromise the already compromised skeleton in individuals with OI. This cross-sectional study aimed to compare muscle function and body composition in adults with various OI types and healthy controls. Sixty-eight adults with OI (mean age 42.2 yr; 27 men) and 68 healthy age- and sex-matched controls were recruited. Maximal isometric muscle force was assessed by handheld dynamometry (hand grip, hip flexors, shoulder abductors, and ankle dorsiflexors), muscle endurance by posture maintenance tests (shoulder abduction, hip flexion, and wall sit), and functional lower limb strength by 30-s chair rise test. In a sub cohort, dynamic muscle function (peak power and force) was assessed by a ground reaction force plate, and lean and fat mass, muscle and fat cross-sectional area (CSA), and muscle density by dual-energy X-ray absorptiometry and peripheral quantitative computed tomography. Multiple linear regression models were fitted with group (OI type I, III, IV/V, or controls), country, sex, and age in the fixed effects part. Overall, adults with various types of OI had lower isometric, endurance, and functional muscle strength (mean difference [MD] = OI type I: 19-43%, OI type IV/V: 25-68%, OI type III: 20-72%) compared to controls. Furthermore, adults with OI type I had lower dynamic muscle function (peak force [MD = 25-29%] and power [MD = 18-60%]), lean mass (MD = 10-17%), muscle CSA (MD = 9-21%), and muscle density (MD = 2-3%) but higher adiposity indices (MD = 24-42%) compared to controls. Functional lower limb strength and maximal muscle force were significantly different between OI types, whereas muscle endurance was not. To conclude, adults with OI present with markedly impaired muscle function which may partially be explained by their altered body composition. Our findings emphasize the need for proper assessment of various muscle parameters and (research into) appropriate and safe muscle strengthening approaches in this population.

Bone mineral density T-scores comparison between obese and non-obese individuals included in a Fracture Liaison Service following a recent fragility fracture.

We used data from a Fracture Liaison Service to compare the mean T-scores of obese and non-obese patients after a recent fragility fracture. After adjusting for age, sex, and diabetes mellitus, T-score values were significantly higher at all measurement sites in obese patients, with a mean difference of 1 SD. PURPOSE: This study aimed to compare the mean T-scores of obese and non-obese patients after recent fragility fractures. METHODS: Over a period of 5 and a half years, from January 2016 to May 2021, patients from a fracture liaison service were identified and their demographic characteristics, osteoporosis risk factors, BMD T-scores, and fracture sites were compared between obese (BMI ≥ 30 kg/m2) and non-obese (19 kg/m2 < BMI < 30 kg/m2) patients. RESULTS: A total of 712 patients were included (80.1% women; mean age 73.8 ± 11.3 years). Sixteen % had type 2 diabetes mellitus and 80% had a major osteoporotic fracture (MOF). 135 patients were obese and 577 non-obese, with obese patients younger (p < 0.001) and more frequently female (p = 0.03). Obese patients presented with fewer hip fractures (10% vs. 21%, p = 0.003) and more proximal humerus fractures (16% vs. 7%, p < 0.001) than non-obese patients. After adjusting for age, sex, and diabetes mellitus, BMD T-score values were significantly higher at all measurement sites (lumbar spine, total hip, and femoral neck) in obese patients than in non-obese patients for all types of fractures, with a mean difference of 1 standard deviation (p < 0.001 for all comparisons). The same results were observed in the population limited to MOF. CONCLUSIONS: Given the crucial role of BMD T-score in determining the need for anti-osteoporotic medication following fragility fractures, it is reasonable to question the existing T-score thresholds in obese patients.

External validation of a deep learning model for predicting bone mineral density on chest radiographs.

We developed a new model for predicting bone mineral density on chest radiographs and externally validated it using images captured at facilities other than the development environment. The model performed well and showed potential for clinical use. PURPOSE: In this study, we performed external validation (EV) of a developed deep learning model for predicting bone mineral density (BMD) of femoral neck on chest radiographs to verify the usefulness of this model in clinical practice. METHODS: This study included patients who visited any of the collaborating facilities from 2010 to 2020 and underwent chest radiography and dual-energy X-ray absorptiometry (DXA) at the femoral neck in the year before and after their visit. A total of 50,114 chest radiographs were obtained, and BMD was measured using DXA. We developed the model with 47,150 images from 17 facilities and performed EV with 2914 images from three other facilities (EV dataset). We trained the deep learning model via ensemble learning based on chest radiographs, age, and sex to predict BMD using regression. The outcomes were the correlation of the predicted BMD and measured BMD with diagnoses of osteoporosis and osteopenia using the T-score estimated from the predicted BMD. RESULTS: The mean BMD was 0.64±0.14 g/cm2 in the EV dataset. The BMD predicted by the model averaged 0.61±0.08 g/cm2, with a correlation coefficient of 0.68 (p<0.01) when compared with the BMD measured using DXA. The accuracy, sensitivity, and specificity of the model were 79.0%, 96.6%, and 34.1% for T-score < -1 and 79.7%, 77.1%, and 80.4% for T-score ≤ -2.5, respectively. CONCLUSION: Our model, which was externally validated using data obtained at facilities other than the development environment, predicted BMD of femoral neck on chest radiographs. The model performed well and showed potential for clinical use.

Bone density estimation using tissue heat capacity.

Osteoporosis onset is relatively asymptomatic, the condition often being identified only once a significant fracture occurs, leading to a potentially serious prognosis. Currently, early identification of osteoporosis is complicated by the difficulty in measuring bone density without using x-ray absorptiometry or quantitative ultrasound, so a simpler method for estimating bone density is needed. Given that bone is reported to have a lower specific heat than other tissues, we investigated the possibility of estimating bone density using this difference in tissue thermal properties. The tibia medial surface (shin) and medial malleolus (ankle) of 68 healthy volunteers were cooled using an ice bag, and skin surface temperatures and heat flow were recorded. These measurements were then used to calculate the heat energy transferred per unit temperature. Bone density was estimated by quantitative ultrasound using the T score OSISD, which is the participant's osteo sono-assessment index (OSI) compared to the average OSI of young adults. The heat energy transfer per unit temperature at the shin, but not the ankle, showed a significant negative correlation with T score OSISD (r = -0.413, p = 0.001). Multiple regression analysis showed that heat energy transfer per unit temperature at the shin was a significant predictor of T score OSISD, along with age and height. These results show that tissue thermal property measurements are useful for estimating bone density.

Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures.

OBJECTIVE: Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls. METHODS: In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived. RESULTS: Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686. CONCLUSION: Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging. ADVANCES IN KNOWLEDGE: CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk.

Osteopenia and Osteoporosis Screening Detection: Calcaneal Quantitative Ultrasound with and without Calibration Factor Comparison to Gold Standard Dual X-ray Absorptiometry.

BACKGROUND: osteoporosis is a worldwide major health problem that normally diagnosed in advanced stages. So, an early detection at preclinical stage is now an interesting issue. A key factor to early diagnosis the disease is the used of noninvasive bone densitometry. Dual energy x-ray absorptiometry (DXA) is the gold standard techniques for the proposed. However, the high cost, non-widely available and exposed to ionizing radiation are still a drawback of the machine. Therefore, a cheaper, smaller and non-ionizing device such quantitative ultrasound (QUS) is now a favor alternative method, but the possibility of used QUS measurement instead of DXA is still limited due to their uncertainties. So, the aim of our study was to calibrated the QUS with the DXA to allowing the possible to establish a calibration factor (CF) to improve the measured value closer to the standard method. METHODOLOGY: 135 healthy men and women aged 30-88 years were recruited for lumbar spine/femoral neck DXA and calcaneal QUS scanning. The Pearson's correlation between T- and Z-score from the two systems were studied. Moreover, the sensitivity, specificity and percentage of diagnosed accuracy for both with and without CF were calculated. RESULTS: The significant correlation between the two systems showed a positive trajectory in highly correlation (r = 0.784-0.899). Analyses showed a higher sensitivity, specificity and reduced the misdiagnosed rates when applied the CF in QUS values. CONCLUSIONS: QUS results showed a significantly correlated with DXA results for both lumbar spine and femoral neck sites with some percentage differences. These differences can be reduced by applied an individual specific machine CF to improve a QUS results. As identification of high risk of osteopenia and osteoporosis to reduce the demand of DXA propose, using a QUS alternative method can be a reliable that provide a cheaper and lack of ionizing radiation.

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Objective: To explore the correlation between 5 dimensions of personality, physical activity (PA), and bone mineral density (BMD) among college students. Methods: A total of 705 undergraduates (329 males and 376 females) from a sports university were recruited. Based on their sports training experience, the participants were divided into 6 major sports groups, including ball sports, skilled sports, competitive sports, track and field, leisure sports, and no sports. Students with professional sports training (ie, athletes) were categorized into ballgame, skilled, competitive, and track and field groups, while the rest (non-athletes) were placed in leisure and no sports groups. Ten-Item Personality Inventory in China (TIPI-C), or the 5-factor model of personality, was used to measure the 5 personality dimensions of openness, conscientiousness, extraversion, agreeableness, and neuroticism of the participants. Their daily level was measured with GT3X+ triaxial accelerometers over 7 continuous days. Then, parameter thresholds were established and the participants' PA was categorized as light (LPA), moderate (MPA), and vigorous (VPA). The bone mineral density (BMD) of arms, legs, and the total body was measured using dual-energy X-ray absorptiometry. The mediation effect of PA and that of the 5-factor model of personality were tested using PROCESS and Sobel tests. The correlation between the 5 personality dimensions, PA, and BMD was explored, with PA and the 5 personality dimensions as mediator variables. A comparison of PA and BMD was conducted across the 6 major sports groups. The correlation between PA of different intensities and BMD was also analyzed using Spearman's correlation. Results: Although there were 90 potential relationships between PA, the 5 personality dimensions, and BMD, only 3 were significant. When conscientiousness was used as an independent variable and MPA, as a mediating variable, statistically significant differences in PROCESS results were reported (P<0.01), with MPA mediating 17.3% of arm BMD, 19.4% of leg BMD, and 19.1% of total body BMD. Among male students, there was no significant difference in LPA among the 6 groups, but significant differences in MPA and VPA (P<0.05). Among female students, significant differences in LPA, MPA, and VPA were observed in all 6 groups and the differences between MPA and VPA were especially prominent (P<0.05). For both males and females, the differences in arm, leg, and total body BMD across the 6 groups were statistically significant (P<0.05), with these differences being more pronounced in females. There was no correlation between LPA and BMD in either sex. MPA and VPA were positively correlated with BMD, with MPA correlating with arm, leg, and total body BMD (males, Spearman's correlation [rs]: 0.11-0.14, P<0.05; females, rs: 0.20-0.23, P<0.01). VPA correlated with arm, leg, and total body BMD (males, rs: 0.11-0.23, P<0.05; females, rs: 0.26-0.30, P<0.01). Conclusion: MPA is associated with BMD in college students scoring high in the conscientiousness dimension of personality. In addition, there is a weak positive correlation between both MPA and VPA and BMD levels, with these associations being more pronounced in females.

DXA-based statistical models of shape and intensity outperform aBMD hip fracture prediction: A retrospective study.

Areal bone mineral density (aBMD) currently represents the clinical gold standard for hip fracture risk assessment. Nevertheless, it is characterised by a limited prediction accuracy, as about half of the people experiencing a fracture are not classified as at being at risk by aBMD. In the context of a progressively ageing population, the identification of accurate predictive tools would be pivotal to implement preventive actions. In this study, DXA-based statistical models of the proximal femur shape, intensity (i.e., density) and their combination were developed and employed to predict hip fracture on a retrospective cohort of post-menopausal women. Proximal femur shape and pixel-by-pixel aBMD values were extracted from DXA images and partial least square (PLS) algorithm adopted to extract corresponding modes and components. Subsequently, logistic regression models were built employing the first three shape, intensity and shape-intensity PLS components, and their ability to predict hip fracture tested according to a 10-fold cross-validation procedure. The area under the ROC curves (AUC) for the shape, intensity, and shape-intensity-based predictive models were 0.59 (95%CI 0.47-0.69), 0.80 (95%CI 0.70-0.90) and 0.83 (95%CI 0.73-0.90), with the first being significantly lower than the latter two. aBMD yielded an AUC of 0.72 (95%CI 0.59-0.82), found to be significantly lower than the shape-intensity-based predictive model. In conclusion, a methodology to assess hip fracture risk uniquely based on the clinically available imaging technique, DXA, is proposed. Our study results show that hip fracture risk prediction could be enhanced by taking advantage of the full set of information DXA contains.