Use of dual-energy X-ray absorptiometry (DXA) for diagnosis and fracture risk assessment; WHO-criteria, T- and Z-score, and reference databases

The association between the presence of kidney stones and the risk of developing osteoporosis: a NHANES-based cross-sectional study and Mendelian randomization analysis

PURPOSE

To investigate whether the presence of kidney stones increases the risk of developing osteoporosis.

METHODS

First, we performed an observational study on the basis of data from the National Health and Nutrition Examination Survey (NHANES; 2007-2020). Kidney stone patients were identified on the basis of their affirmative response to the question "Have you ever experienced kidney stones?" (KIQ026). Participants whose T score at the femoral neck was < -2.5 were defined as osteoporosis patients. Multivariable-adjusted logistic regression was used to assess the correlation between the presence of kidney stones and the risk of developing osteoporosis. Second, Mendelian randomization (MR) was applied to further investigate the causal relationship between the presence of kidney stones and the risk of developing osteoporosis. Genetic instruments were obtained from large genome-wide association studies (GWASs) from the UK Biobank and FinnGen Biobank. Inverse-variance weighting (IVW) was the primary analytical method used.

RESULTS

After adjustment for demographic and other covariates, a significant association between the presence of kidney stones and the risk of developing osteoporosis was detected (OR 1.778, CI: 1.345-2.351, P < 0.001). The MR results further revealed that genetically speaking, the presence of kidney stones was causally associated with a greater risk of developing osteoporosis (IVW: OR 1.088, CI: 1.015-1.167, P < 0.05).

CONCLUSION

The presence of kidney stones is associated with an increased risk of developing osteoporosis. Further prospective cohort studies are needed to validate our results.

[18F]NaF PET/CT Imaging of Iliac Bones to Assess Bone Turnover

PURPOSE

This study investigated the effects of laterality, age, gender, BMI, and physical activity level on iliac bone turnover using [18F]NaF PET/CT.

PROCEDURES

Fifty-nine males and 44 females from the CAMONA study were analyzed. A region of interest (ROI) was drawn to segment the iliac bone using Hounsfield unit thresholds and morphological closing algorithm. [18F]NaF SUVmean was compared between the left and right iliac bones using a paired t-test, while Pearson correlation coefficient assessed changes with age, BMI, and physical activity level.

RESULTS

[18F]NaF uptake was higher in right iliac bone than left in males, females, and the combined-group. In males, SUVmean was 2.98 ± 1.63 (1.1-7.87) on left and 3.71 ± 1.49 (1.49-3.7) on right. In females, SUVmean was 2.59 ± 1.14 (0.88-6.27) on left and 3.72 ± 1.04 (2.22-6.51) on right. Combined, SUVmean was 2.81 ± 1.44 (0.88-7.87) on left and 3.71 ± 1.31 (0.89-8.07) on right. [18F]NaF uptake negatively correlated with age (right: r = - 0.27, P = 0.006; left: r = - 0.22, P = 0.02), stronger in females (right: r = - 0.30, P = 0.04; left: r = - 0.31, P = 0.04) than males (right: r = - 0.26, P = 0.04; left: r = - 0.18, P = 0.18). SUVmean correlated positively with BMI in males (right: r = 0.47, P = 0.0002; left: r = 0.38, P = 0.0027), females (right: r = 0.36, P = 0.0168; left: r = 0.30, P = 0.0505), and combined-group (right: r = 0.43, P < 0.0001; left: r = 0.37, P = 0.0001). No significant correlation was found between SUVmean and physical activity in males, while in females, a negative correlation was observed on left (r = - 0.37, P = 0.0390) but not on right (r = - 0.27, P = 0.1302), and when combined, the correlation remained significant on left (r = - 0.24, P = 0.0372) but not on right (r = - 0.16, P = 0.1541).

CONCLUSIONS

[18F]NaF uptake was higher in the right iliac bone and declined with age, particularly in females. The positive correlation between SUVmean and BMI; and the negative correlation between SUVmean and physical activity suggest metabolic influences on bone turnover. [18F]NaF PET/CT may serve as a tool for assessing bone metabolism and turnover in asymptomatic individuals.

Prediction of abnormal bone mass with a pericoronary adipose tissue Attenuation model

BACKGROUND

The aim is to explore the value of pericoronary adipose tissue (PCAT) attenuation in predicting abnormal bone mass by establishing a prediction model.

MATERIALS AND METHODS

361 patients with coronary computed tomography angiography (CCTA) and quantitative computed tomography (QCT) scans were retrospectively recruited. 311 patients from institution 1 from July 2021 to January 2023 were divided into a training cohort (n = 217) and an internal cohort (n = 94). The external cohort comprised 50 patients from institution 2 from January 2023 to August 2023. Clinical variables and PCAT attenuation of the major epicardial vessels were obtained. Univariate and multivariate logistic regression analyses were used to identify factors with statistical significance. Model 1 was constructed based on clinical variables. Model 2 was constructed by combining the clinical variables with the PCAT attenuation. The performances of the models were assessed using receiver operating characteristic curve analysis, calibration curves and decision curve analysis (DCA).

RESULTS

Age, gender, coronary artery disease reporting and data system (CAD-RADS), statins and RCAPCAT were found to be significant predictors of abnormal bone mass. The area under the curve (AUC) of Model 2 was superior to that of Model 1 in the training cohort (AUC: 0.959 vs. 0.920), internal (AUC: 0.943 vs. 0.890) and external validation cohorts (AUC: 0.889 vs. 0.812). The calibration curves and DCA indicated that Model 2 had the higher clinical value.

CONCLUSION

The model incorporating clinical factors and RCAPCAT has good performance in predicting bone mass abnormalities.

Associations between Per- and Polyfluoroalkyl Substances Exposures and Bone Mineral: A Systematic Review and Best Evidence Synthesis

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants known for their bioaccumulative nature. Reduced bone mineral density (BMD) is associated with an increased risk of developing osteoporosis. This pioneering study aims to assess the effects of different PFAS compounds on bone mineral. We conducted searches on online databases. Inclusion criteria included the presence of associations between perfluorooctanoic acid (PFOA), perfluorooctanesulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) and BMD, BMD z-score, and bone mineral content (BMC). Meta-analyses were performed. Best evidence synthesis (BES) was performed to summarize the results. The results of BES showed that the evidence of PFOS, PFOA and PFNA with reduced bone mineral were moderate. The variability in methods for assessing bone mineral and sex differences are potential sources of heterogeneity in the results. Meta analysis showed that PFOA was associated with BMD (β -0.01, 95% CI -0.01 to -0.00; I 2 = 0%). Subgroup analysis by sex showed that PFOS (β -0.01, 95% CI -0.01 to -0.00; I 2 = 50%), PFOA (β -0.01, 95% CI -0.01 to +0.00; I 2 = 29%) were negatively correlated with BMD. This systematic review and BES revealed negative correlations between exposure to PFOS, PFOA, PFNA and bone mineral. Sex emerged as a potential factor affecting the negative effects of PFAS on bone mineral. The damage of PFAS to bone mineral still requires further exploration.

Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT

RATIONALE AND OBJECTIVES

To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classification.

MATERIALS AND METHODS

A total of 456 participants were retrospectively included and were divided into a development cohort comprising 355 patients, with a 7:3 ratio randomly assigned to the training and validation cohorts, and a test cohort comprising 101 patients. The automatic segmentation model for the proximal femur was trained using VB-Net. The Dice similarity coefficient (DSC) and volume difference (VD) were employed to evaluate the performance of the segmentation model. A three-classification predictive model for assessing bone mineral status was constructed utilizing radiomic analysis. The diagnostic performance of the radiomics model was assessed using the area under the curve (AUC), sensitivity, and specificity.

RESULTS

The automatic segmentation model for the proximal femur demonstrated excellent performance, achieving DSC values of 0.975 ± 0.012 and 0.955 ± 0.137 in the validation and test cohorts, respectively. In the test cohort, the radiomics model utilizing the random forest (RF) classifier achieved AUC values, sensitivity, and specificity of 0.924 (95% CI: 0.854-0.967), 0.846 (95% CI: 0.719-0.931), and 0.837 (95% CI: 0.703-0.927) for the identification of normal bone mass. For the identification of osteoporosis, the corresponding metrics were 0.960 (95% CI: 0.913-1.000), 0.947 (95% CI: 0.740-0.999), and 0.963 (95% CI: 0.897-0.992). In the case of osteopenia, the corresponding metrics were 0.828 (95% CI: 0.747-0.909), 0.767 (95% CI: 0.577-0.901), and 0.746 (95% CI: 0.629-0.842).

CONCLUSION

A three-classification predictive model combining a deep learning-based automatic segmentation of the proximal femur and a radiomics-based bone status classification on LDCT images can be used for the opportunistic detection of osteoporosis.

U-Net-Based Deep Learning Hybrid Model: Research and Evaluation for Precise Prediction of Spinal Bone Density on Abdominal Radiographs

Osteoporosis is a metabolic bone disorder characterized by the progressive loss of bone mass, which significantly increases the risk of fractures. While dual-energy X-ray absorptiometry is the standard technique for assessing bone mineral density, its use is limited in high-risk female populations. Additionally, quantitative computed tomography offers three-dimensional evaluations of bone mineral density but is costly and prone to motion artifacts. To overcome these limitations, this study proposes a hybrid model integrating U-Net and artificial neural networks, specifically focusing on abdominal X-ray images in the anteroposterior view for detailed skeletal analysis and improved accuracy in L2 vertebra mineral density measurement. The model targets female patients, who are at a higher risk for spinal disorders and osteoporosis. The U-Net model is employed for image preprocessing to reduce background noise and enhance bone tissue features, followed by analysis with the artificial neural network model to predict bone mineral density through nonlinear regression. The performance of the model, demonstrated by a high correlation coefficient of 0.77 and a low mean absolute error of 0.08 g per square centimeter, highlights its significance and effectiveness, particularly in comparison to dual-energy X-ray absorptiometry.

Utility of osteoporosis screening based on estimation of bone mineral density using bidirectional chest radiographs with deep learning models

Introduction

Osteoporosis increases the risk of fragility fractures, especially of the lumbar spine and femur. As fractures affect life expectancy, it is crucial to detect the early stages of osteoporosis. Dual X-ray absorptiometry (DXA) is the gold standard for bone mineral density (BMD) measurement and the diagnosis of osteoporosis; however, its low screening usage is problematic. The accurate estimation of BMD using chest radiographs (CXR) could expand screening opportunities. This study aimed to indicate the clinical utility of osteoporosis screening using deep-learning-based estimation of BMD using bidirectional CXRs.

Methods

This study included 1,624 patients aged ≥ 20 years who underwent DXA and bidirectional (frontal and lateral) chest radiography at a medical facility. A dataset was created using BMD and bidirectional CXR images. Inception-ResNet-V2-based models were trained using three CXR input types (frontal, lateral, and bidirectional). We compared and evaluated the BMD estimation performances of the models with different input information.

Results

In the comparison of models, the model with bidirectional CXR showed the highest accuracy. The correlation coefficients between the model estimates and DXA measurements were 0.766 and 0.683 for the lumbar spine and femoral BMD, respectively. Osteoporosis detection based on bidirectional CXR showed higher sensitivity and specificity than the models with single-view CXR input, especially for osteoporosis based on T-score ≤ -2.5, with 92.8% sensitivity at 50.0% specificity.

Discussion

These results suggest that bidirectional CXR contributes to improved accuracy of BMD estimation and osteoporosis screening compared with single-view CXR. This study proposes a new approach for early detection of osteoporosis using a deep learning model with frontal and lateral CXR inputs. BMD estimation using bidirectional CXR showed improved detection performance for low bone mass and osteoporosis, and has the potential to be used as a clinical decision criterion. The proposed method shows potential for more appropriate screening decisions, suggesting its usefulness in clinical practice.

Radiation Diagnostics of the Maxillofacial Region and Skeleton Bone Density in the Case of Vitamin D Insufficiency: A Pilot Study

(1) Background: A decrease in bone mineral density has been noted not only in at-risk patients (e.g., postmenopausal women) but also in young and middle-aged individuals due to changes in lifestyle. The aim of the study was to find a possible correlation for dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) with cone beam computed tomography (CBCT) of the jaws. (2) Methods: A total of 24 patients (14 women and 10 men aged 25 to 50 years) with partial secondary tooth loss and vitamin D insufficiency underwent cone beam computed tomography of the jaws and skeletal mineral density assessment using DXA (n = 12) and QCT (n = 12). (3) Results: When conducting CBCT of the jaws, a predominance of bone tissue type D3 (350-850 Hu) on the upper jaw (p > 0.05 (F = 0.68) and D2 (850-1350 Hu) on the lower jaw (p > 0.05 (F = 1) was revealed. According to the results of QCT densitometry of the skeleton, signs of osteopenia were found in four patients (with vitamin D3 deficiency) (33%) according to DXA; signs of osteopenia were found in six patients (with severe deficiency and deficiency of vitamin D3) (50%). The difference between QCT and DXA was not significant (p > 0.05) for each group. The significant strong correlation between CBCT and DXA or QCT was not found (p > 0.05). (4) Conclusions: Primary changes in bone density can be detected earlier in the dental system using cone beam computed tomography of the jaws. At the same time, the question of using a specific densitometry method-DXA or QCT-remains open, as their results correlating with CBCT optical density was not approved.

Deep learning opportunistic screening for osteoporosis and osteopenia using radiographs of the foot or ankle - A pilot study

BACKGROUND

The gold standard method for diagnosing low bone mineral density (BMD) is using dual-energy X-ray absorptiometry (DXA) however, most patients with low BMD are often not screened. We aimed to create a deep learning (DL) model to screen for osteoporosis/osteopenia in patients by using radiographs of the foot or ankle.

METHOD

This is a retrospective cross-sectional study of patients aged ≥50 years who received X-rays of the foot or ankle and DXA (gold-standard) within 12 months. The 907 (White (96.7 %), Black (1.8 %) and Asian (0.4 %)) patients (3109 radiographs) were randomized (80:20) into training/validation and test datasets, and results were assessed by patient. We developed a novel DL model that extracted deep features from the radiographs of the foot and ankle using a customized architecture. The diagnostic performance of this DL model to predict if a patient had low BMD (osteopenic/osteoporotic) or normal BMD based on DXA, was evaluated with the area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

Mean patient age (standard deviation) was 66.9(9.0) years, and 84.6 % were female. 81.3 % and 18.7 % of patients in the training/validation dataset, and 81.5 % and 18.5 % of patients in the test datasets were osteopenic/osteoporotic and normal respectively. The DL model had an AUC of 0.87 (95% CI (0.85, 0.94), sensitivity of 89.89 %, specificity of 83.65 %, PPV of 90.78 % and NPV of 74.14 % in the test dataset. The model had an accuracy of 94.65 % in the training/validation dataset and 89.89 % in the test datasets.

CONCLUSION

Our DL model has the potential to identify patients with osteopenia/osteoporosis using foot or ankle radiographs with high accuracy.

Optimized surveillance frequency for low bone mineral density (BMD) screening using dual-energy X-ray absorptiometry (DXA) in patients after lung transplant

BACKGROUND

Approximately 2,700 lung transplants are performed annually in the United States. These patients are at increased risk of developing low bone mineral density (BMD) (osteopenia/osteoporosis) and subsequent fractures. Dual-energy X-ray absorptiometry (DXA) is the most common method used for screening for low BMD; however, the optimal surveillance frequency for low BMD using DXA is unknown.

METHODS

We evaluated the change in femoral neck, total femur, L1, L2, L3, and L4 BMD after lung transplant in a retrospective cohort of 259 patients (69.9% male) who were followed with serial DXA scans for a median of 725 (interquartile range [361-1,116]) days after transplant. Generalized linear mixed-effects models adjusting for sex, time, time-squared, baseline osteopenia/osteoporosis, active rejection, and their interaction terms were used to model the rate of change of BMD at each site. The final multivariable models for the femoral neck, L1, and L4 BMD measurements had random slopes and intercepts, and the models for the total hip, L2, and L3 measurements had random slopes.

RESULTS

Sixty-five percent of the patients undergoing lung transplants had osteopenia or osteoporosis before transplant. Men exhibited higher baseline BMD levels compared to women at all sites (p < 0.001 for all). After the transplant, the greatest rate of BMD decrease was at the femoral neck. Although patients with low BMD had significantly lower baseline BMDs (p < 0.001 for all), they experienced a slower rate of BMD decrease at all sites compared to patients with normal BMD at baseline (p < 0.001 for all). All patients received corticosteroids. Patients with low BMD at baseline had significantly higher odds of receiving bisphosphonate therapy (odds ratio = 3.95, 95% confidence interval [CI] [1.44, 13.51], p = 0.003). We estimated that a significant change in the femoral neck BMD would be expected to occur within 409 days (95% CI [131, 708]) and again at 867 days (95% CI [551, 1,216]) after lung transplant.

CONCLUSIONS

Patients undergoing lung transplant should be screened annually with DXA for the first 2 years after transplant, consistent with the current International Society for Heart and Lung Transplantation guidelines.

Mandible bone mineral density estimation using spectral panoramic X-ray imaging

Purpose

This study demonstrated the feasibility of obtaining mandible bone mineral density (BMD) scores using spectral panoramic imaging.

Materials and Methods

Areal BMD scores were measured from the body and angle of the mandible in 3 anthropomorphic head phantoms using a spectral panoramic system (Planmeca Promax Mid, Planmeca Oy, Helsinki, Finland) equipped with a DC-Vela detector (Varex Imaging Corporation, Salt Lake City, USA). These results were compared to synthetic panoramic images generated from dual-energy CT acquisitions. Reproducibility was evaluated by repeatedly scanning 1 phantom with minor patient positioning errors, and the linearity of the BMD scores was assessed using calcium inserts in a Gammex 472 phantom (Sun Nuclear, Melbourne, USA).

Results

The experimental and synthetic panoramic images appeared visually similar. The mean synthetic score was 0.640 g/cm2, and the anthropomorphic phantoms produced a root mean squared error of 0.0292 g/cm2 with a correlation coefficient of 0.969. Typical patient positioning errors did not substantially increase the error, which measured 0.0296 g/cm2 and 0.0474 g/cm2 for the left and right sides, respectively. Linearity tests using the Gammex phantom yielded a correlation coefficient of 0.998 for BMD scores ranging from 0.03 to 2.7 g/cm2.

Conclusion

The BMD data obtained from spectral panoramic imaging are consistent with both dual-energy CT and Gammex phantom measurements. Consequently, spectral panoramic imaging shows potential as a method for osteoporosis screening, leveraging the widespread use of panoramic imaging.

Patterns and Correlates of Bone Mineral Density Parameters Measured Using Calcaneus Quantitative Ultrasound in Chinese Adults

Background: Monitoring bone mineral density (BMD) in adults is critical for early detection of osteoporosis and prevention of fracture, for which quantitative ultrasound (QUS) is a good non-invasive tool. We examined the associations of QUS measures, including stiffness index (SI) and T-score, with socio-demographic, lifestyle, and anthropometric correlates and risk of subsequent fracture. Methods: Calcaneal QUS was performed using GE's Lunar Achilles EXPII among 24,651 adults (mean age 59.5 years, 61.7% women) from the China Kadoorie Biobank study. Socio-demographic and lifestyle information was collected using an interviewer-administered electronic questionnaire, and anthropometrics were measured following standard protocols. Incidence of fracture and osteoporosis was recorded via linkage with nationwide health insurance database. Linear and Cox regression analyses were conducted, adjusting for potential confounders. Results: On average, men had higher SI (92.8 vs. 86.0) but lower T-score (-0.85 vs. -0.64) than women. In both men and women, advanced age and smoking were inversely associated with SI and T-score, while physical activity and tea drinking were positively so (p < 0.0001 for all). Except for height, all other anthropometric measures were significantly and positively associated with both BMD measures. With each SD lower SI, the risk of subsequent fracture was 26% (95% confidence interval: 10-44%) and 40% (25-57%) higher in men and women, and the corresponding associations of T-score were identical. Conclusions: Among Chinese adults, the SI and T-score provided by Achilles EXPII had similar patterns and predictive values for subsequent fracture, despite the T-score for men and women not being directly comparable because of gender-specific references used. Future studies are needed to confirm or refute the causality of relationship between lifestyle and anthropometric factors and BMD.

Relationship Among Fragility Fractures and the Overall Cardiovascular Burden in Endogenous Cushing Syndrome

Context

Patients with endogenous Cushing syndrome (CS), in addition to significant cardiovascular morbidity, are burdened by a high prevalence of fragility fractures. Bone mineral density (BMD) alone poorly predicts the risk of fracture, and the implementation of trabecular bone score (TBS) is supported only by scant evidence. Indeed, reliable predictors of fractures in endogenous CS are still lacking.

Objective

This work aimed to analyze the prevalence and the potential predictors of fragility fractures in our patients with CS.

Methods

A monocentric, retrospective, cross-sectional study. A total of 51 patients with overt CS were enrolled. Main outcome measures included biochemical evaluation, BMD measurement, TBS evaluation, fracture presence, body composition evaluation, and arterial intima-media thickness (IMT) assessment.

Results

Fragility fractures were found in 62.7% of patients at diagnosis. Fractured patients exhibited lower spine T-score (P = .03), longer disease duration (P = .025), higher waist circumference (P = .006), and predominantly male sex (P = .008). Increased serum uric acid levels (P = .001), greater IMT (P = .017), and higher prevalence of venous thromboembolism events (31.3% vs 5.3%, P = .037) and atherosclerotic plaques (47% vs 5.3%, P = .002) were described in the fracture group.Multivariable logistic regression identified the presence of atherosclerosis (OR 13.35; 95% CI 1.154-154.34, P = .038) and osteoporosis (OR 11.30; 95% CI 1.55-82.56, P = .017) as independent predictors. TBS values were inversely correlated with body mass index, fat and lean mass, and serum uric acid, and positively correlated with high-density lipoprotein cholesterol.

Conclusion

CS patients with higher overall burden of cardiovascular morbidity are more prone to experience fragility fractures.

Association of serum alkaline phosphatase levels with bone mineral density, osteoporosis prevalence, and mortality in US adults with osteoporosis: evidence from NHANES 2005-2018

This study examined the association of serum total alkaline phosphatase (T-ALP) with bone mineral density (BMD) and osteoporosis prevalence in the general population, and investigated its association with mortality in individuals with osteoporosis, using data from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018. Elevated serum T-ALP levels were significantly associated with both reduced BMD and an increased risk of osteoporosis in all participants. Moreover, elevated T-ALP levels were linked to higher all-cause mortality among individuals with osteoporosis during this period.

INTRODUCTION

The evidence regarding the association between serum T-ALP, BMD and osteoporosis prevalence in general population is incomplete, and limited evidence is available concerning its association with mortality among individuals with osteoporosis. The study investigated the association of serum T-ALP with BMD and osteoporosis prevalence in the general population, and examined its association with mortality in individuals with osteoporosis.

METHODS

All participants were adults from the NHANES (2005-2018), and mortality data were obtained from the National Death Index up to December 31, 2019. Firstly, the association of serum T-ALP with BMD and osteoporosis risk was assessed using linear regression model, subgroup analysis, analysis of covariance and weighted logistic regression model, respectively. Secondly, survival analysis including Kaplan-Meier curves, Cox proportional hazards models, and restricted cubic spline regression models were utilized to analyze the relationship between serum T-ALP levels and mortality risk.

RESULTS

The study included 13,724 participants aged 18 to 85 years, and 944 were diagnosed with osteoporosis, among whom 221 died during a median of 133 months follow-up. Totally, elevated serum T-ALP was significantly associated with low BMD in femoral neck and lumbar spine, and the results exhibited consistency across diverse age, genders, races, and BMI subgroups. Moreover, for each 1 SD increase in T-ALP, there was a 0.5% increase in the prevalence of osteoporosis [OR (95%CI): 1.005 (1.005, 1.005), p < 0.001]. Among individuals with osteoporosis, for every 1 SD increase in T-ALP, the all-cause mortality increased by 0.4% [HR (95%CI):1.004 (1.002, 1.006), p < 0.001]. Meanwhile, comparing participants with highest serum T-ALP levels (> 79 IU/L) to those with lowest levels (< 53 IU/L) further raised the prevalence of osteoporosis [OR (95%CI):1.292 (1.021, 1.636), p = 0.033] and all-cause mortality [HR (95% CI):1.232 (1.041, 1.459), p = 0.015].

CONCLUSIONS

Based on a representative sample of US adults, elevated serum T-ALP levels were found to be significantly associated with both reduced BMD and an increased risk of osteoporosis across all participants, as well as with a higher all-cause mortality in individuals with osteoporosis.

Opportunistic screening of osteoporosis by CT scan compared to DXA: A systematic review and meta-analysis

The efficacy of opportunistic osteoporosis screening with computed tomography (CT) scans obtained for other indications has not yet been implemented by the current guidelines. We aimed to compile available evidence on the efficacy of osteoporosis screening with CT scans obtained for other indications compared with dual X-ray absorptiometry (DXA). Studies comparing the diagnostic performance of the CT scan with the DXA published before 2023 were retrieved. We conducted a bias assessment using the Newcastle-Ottawa Scale for cross-sectional studies. Correlation coefficients (CC), area under the curve (AUC), sensitivity, and specificity of the CT scans compared with the DXA were meta-analyzed with random effects modeling. 41 studies fulfilled the inclusion/exclusion criteria. The included studies reported weak to very strong CC (0.35 to 0.95) and low to high accuracy for opportunistic osteoporosis screening with CT scans. The meta-analysis showed a moderate pooled CC of 0.59 (95 % CI: 0.53-0.64, P-value<0.001), and a relatively high AUC of 0.81 (95 % CI: 0.78-0.84, P-value<0.001). Subgroup analysis based on age and menopausal status did not show significant between-group differences. Significantly higher accuracy measures were estimated for CT scans of the proximal femur compared to other anatomic regions (CC: 0.70, 95 % CI: 0.57-0.82; AUC: 0.79, 95 % CI: 0.72-0.87), North American cases (CC: 0.66, 95 % CI: 0.52-0.80; AUC: 0.82, 95 % CI: 0.82-0.83), and populations with a higher percentage of women (CC: 0.60, 95 % CI: 0.52-0.69; AUC: 0.86, 95 % CI: 0.83-0.89). We observed a moderate performance of opportunistic osteoporosis screening with CT scans obtained for other indications.

Effect of donepezil on bone metabolism among older adults with Alzheimer's disease

Older adults with Alzheimer's disease (AD), in addition to significant cognitive disability, have twice the risk of fracture compared to those with normal cognition. Fractures among older adults with AD are associated with substantial morbidity, loss of physical function, and significant mortality. Prior studies have shown a decreased risk of fracture among those taking acetylcholinesterase inhibitors, such as donepezil. With both cognitive and non-cognitive benefits, donepezil would be a valuable component in a fracture prevention program for older adults with AD. Though anti-amyloid therapies are now clinically available, donepezil may still have non-cognitive benefits. However, the specific effects of donepezil on bone metabolism are unknown. We have designed this randomized, double-blind, placebo-controlled clinical trial to investigate the effect of AD treatment with donepezil on bone metabolism. The study will measure the change in bone mineral density, bone turnover markers, and bone quality related to 12-months of donepezil therapy. This will be the first known study of changes in bone metabolism among older adults with AD.

Association between modified dietary inflammation index score and lumbar vertebrae bone mineral density in patients with hypertension: data from NHANES-a population-based study

BACKGROUND

The modified Dietary Inflammation Index Score (M-DIS) is a scoring system used to quantify the inflammatory effects of nutrients and foods. Inflammation may affect Bone Mineral Density (BMD) and increase the risk of osteoporosis and fractures. The purpose of this study was to utilize data from the National Health and Nutrition Examination Survey (NHANES) to evaluate the relationship between M-DIS and lumbar vertebrae BMD in patients with hypertension.

METHODS

Data from 2007 to 2008, 2009-2010, 2013-2014 and 2017-2018 NHANES cycles were collected for secondary analysis. Information provided by NHANES participants included complete dietary intake interviews and BMD measurements. M-DIS was calculated based on dietary intake interviews. Dual energy X-ray absorptiometry (DXA) was used to evaluate the average BMD of lumbar vertebrae (L1-L4). As an indicator of bone health, weighted multiple logistic regression and restricted spline analysis were utilized to study the relationship between M-DIS and lumbar vertebrae BMD in American patients with hypertension.

RESULTS

A total of 3864 participants aged ≥ 20 years with complete data were included in this study. The proportion of osteopenia in the lumbar spine was 7.2%. After adjusting for confounding factors, negative correlations were observed between the BMD of each vertebral and its average BMD with M-DIS. In Model 3, the relationship between mean lumbar BMD and M-DIS was β = - 0.0103 (95% CI - 0.0160 to - 0.0046, P < 0.001). Notably, L1 showed a particularly significant negative correlation with β = - 0.0120 (95% CI - 0.0172 to - 0.0067, P < 0.001), while the proportion of osteopenia was highest in the L3 vertebra, accounting for 8.3%. Higher M-DIS was positively correlated with the incidence of osteopenia (OR 0.595, 95% CI 0.371-0.965, P = 0.041). Further analyses revealed that in hypertensive patients, elevated M-DIS in women was associated with lower lumbar BMD (P for nonlinearity = 0.093), while this trend was not significant in hypertensive men.

CONCLUSIONS

The results of this study suggest that a higher M-DIS (pro-inflammatory diet) is significantly associated with BMD in females with hypertension. These results indicate that female with hypertension who prefer a pro-inflammatory diet may be at an increased risk of osteopenia, highlighting the necessity for tailored dietary recommendations.

Prevalence, characteristics, and associated risk factors of plantar heel pain in americans : The cross-sectional NHANES study

By analyzing data from NHANES, we aimed to evaluate the prevalence, characteristics, and associated factors of plantar heel pain in Americans aged 20 or above.

INTRODUCTION

Plantar heel pain is a prevalent problem that affects a substantial number of adults and significantly impairing their quality of life.

OBJECTIVE

To investigate the prevalence and characteristics of plantar heel pain, exploring the associated risk factors.

METHODS

This is a cross-sectional study. We analyzed data from 4957 individuals aged 20 or above who participated in the 2009-2010 NHANES.

RESULTS

Among the total 4957 US participants ≥ 20 years of age, 549 (11.1%) participants reported plantar heel pain. There was a significant difference in distribution between female and male (p = 0.002). Furthermore, participants aged between 50 and 65 years had the highest plantar heel pain prevalence of 14.5% among the entire population, however, among the female participants, those aged ≥ 65 years demonstrated the highest prevalence (19.8%) of plantar heel pain. In addition, compared to those with BMI < 25 kg/m2, BMI with 25-30 kg/m2 had 1.5-fold risk of plantar heel pain(OR:1.50, 95%CI:1.10-2.05), while BMI with 30-35 kg/m2 had a 2.1-fold higher risk and those with BMI ≧ 35 kg/m2 had a 2.7-fold risk to experience plantar heel pain. Age, BMI, female (OR:1.35, 95%CI:1.07-1.70), kidney stones history (OR:1.52, 95%CI:1.09-2.11), hypertension (OR:1.54, 95%CI:1.20-1.96) and osteoporosis (OR:1.75, 95%CI:1.10-2.78) were independent risk factors for plantar heel pain. Further subgroup analysis indicated that osteoporosis is the independent risk factor for women (OR:2.00, 95%CI:1.19-3.37) but not men (OR:0.65, 95%CI:0.15-2.86) for plantar heel pain.

CONCLUSION

Our findings might offer evidences for the prevention and treatment of plantar heel pain. Further prospective studies are needed to confirm our findings.

Trabecular bone score as an assessment tool to identify the risk of vertebral fractures in SAPHO syndrome

This is the first study to report that TBS seems not only unaffected by bone artifacts, but also is superior to BMD in the discrimination of vertebral fractures in SAPHO patients, which highlights the importance of adding TBS measurement to DXA images in routine clinical evaluation.

PURPOSE

To investigate the impact of bone artifacts on trabecular bone score (TBS) and lumbar spine (LS) bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) and analyze the clinical utility of TBS evaluation for vertebral fracture (VF) risk assessment in SAPHO patients compared with BMD assessment.

METHODS

Seventy SAPHO patients (mean age 50.1 (10.7) years, 81% women) and an equal number of age- and sex-matched controls were enrolled. TBS and BMD were assessed using DXA. Bone artifacts and VF of the spine were evaluated using whole-spine CT. Univariate logistic regression analysis was performed to identify factors associated with VF. Odds ratios (ORs) per standard deviation decrease in TBS and BMDs were estimated from logistic regression models with adjustment for age.

RESULTS

In patients with bone artifacts, TBS, but not LS BMD, was lower than matched controls, and in those without bone artifacts, both BMDs and TBS were lower than controls. After adjustment, LS BMD was significantly lower in the SAPHO group than in controls. TBS and LS BMD (OR [95% confidence interval], 12.0 [3.6, 40.4] and 4.7 [2.0, 10.9]) showed statistically significant ORs but the others did not. For evaluating VF in SAPHO patients, TBS showed the greatest AUC in the ROC curve, with a value of 0.920 compared with 0.777, 0.690, and 0.652 for LS, FN, and TH BMD, respectively.

CONCLUSION

TBS seems not to be influenced by bone artifacts in opposition to LS BMD and has a better discriminatory value than BMD for VF in SAPHO patients.

Systemic Immune-Inflammation-Based Biomarker and Fragility Fractures in People Living With HIV: A 10-Year Follow-Up Cohort Study in China

Fragility fractures are a significant concern among people living with HIV(PLWH) due to the combined effects of chronic inflammation, immune dysregulation, and antiretroviral therapy. Traditional biomarkers have limited predictive value for fragility fractures in this population. This study aims to evaluate the systemic immune inflammation-based scores as novel biomarkers for predicting fragility fractures in PLWH in China. We conducted a cohort study of PLWH in the orthopedic department of Beijing Ditan Hospital from January 2011 to September 2023. We monitored fragility fractures and collected data on demographics, clinical characteristics, and laboratory parameters. Multivariate Cox and logistic regression models were used to assess the predictive value of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) for fragility fractures. Restricted cubic splines (RCS) were employed to explore potential nonlinear relationships, and subgroup analyses were conducted to examine the stability of these associations. During a median follow-up of 5.5 years, our study included 1148 PLWH patients, and 204 patients (17.8%) experienced fragility fractures. After adjusting for all covariates, SII and SIRI were identified as independent risk factors for fragility fractures in PLWH, whereas NLR, PLR, and MLR were not. Patients with higher levels of SII and SIRI had a significantly increased risk of fragility fractures compared to those with lower levels (HR: 1.96, 95% CI: 1.24-3.10, p = 0.004; HR: 1.83, 95% CI: 1.16-2.88, p = 0.009). RCS analysis indicated a stable linear relationship between SIRI and fragility fractures. Furthermore, KM curves demonstrated that patients with higher SII and SIRI scores had a higher likelihood of experiencing fragility fractures. Our research shows that SII and SIRI are promising biomarkers for predicting fragility fractures in PLWH. Clinicians should consider incorporating SIRI into clinical practice to improve fracture risk stratification and guide preventive strategies for this vulnerable population.

Association of hemoglobin-to-red blood cell distribution width ratio and bone mineral density in older adults

BACKGROUND

Hemoglobin-to-Red Cell Distribution Width Ratio (HRR) represents novel prognostic markers for diseases. However, there remains a lack of systematic research into the relationship between HRR and Bone Mineral Density (BMD) or osteoporosis in older adults.

METHODS

This study utilized information from the NHANES database, selecting individuals over 50 years of age with complete femoral DXA scans and full blood counts. The relationship between HRR and femoral BMD was investigated using weighted linear models and restricted cubic spline (RCS) models. Moreover, the association between HRR and osteoporosis was further explored using logistic regression models and RCS models, with subgroup analysis conducted to test the robustness of the results.

RESULTS

This study included a total of 7,149 participants, and the BMD of the group with higher HRR was significantly greater than that of the group with lower HRR. Weighted linear regression analysis found a linear positive correlation between HRR and femoral BMD. When HRR was converted from a continuous variable to a categorical variable, this relationship remained stable. In addition, multivariate logistic regression analysis showed that for each 1-unit increase in HRR, the prevalence of osteoporosis significantly decreased (OR = 0.25, 95% CI: 0.12-0.51), further confirming the findings of this study. Subgroup analysis showed that this association was not significantly affected by confounding factors across different populations.

CONCLUSION

HRR may serve as one of the potential indicators for evaluating BMD and assessing the prevalence of osteoporosis in the elderly. Elevating HRR levels may play a crucial role in the prevention and slowing of osteoporosis progression.

[Osteoporosis-Definition, risk assessment, diagnosis, prevention and treatment (update 2024) : Guidelines of the Austrian Society for Bone and Mineral Research]

BACKGROUND

Austria is among the countries with the highest incidence and prevalence of osteoporotic fractures worldwide. Guidelines for the prevention and management of osteoporosis were first published in 2010 under the auspices of the then Federation of Austrian Social Security Institutions and updated in 2017. The present comprehensively updated guidelines of the Austrian Society for Bone and Mineral Research are aimed at physicians of all specialties as well as decision makers and institutions in the Austrian healthcare system. The aim of these guidelines is to strengthen and improve the quality of medical care of patients with osteoporosis and osteoporotic fractures in Austria.

METHODS

These evidence-based recommendations were compiled taking randomized controlled trials, systematic reviews and meta-analyses as well as European and international reference guidelines published before 1 June 2023 into consideration. The grading of recommendations used ("conditional" and "strong") are based on the strength of the evidence. The evidence levels used mutual conversions of SIGN (1++ to 3) to NOGG criteria (Ia to IV).

RESULTS

The guidelines include all aspects associated with osteoporosis and osteoporotic fractures, such as secondary causes, prevention, diagnosis, estimation of the 10-year fracture risk using FRAX®, determination of Austria-specific FRAX®-based intervention thresholds, drug-based and non-drug-based treatment options and treatment monitoring. Recommendations for the office-based setting and decision makers and institutions in the Austrian healthcare system consider structured care models and options for osteoporosis-specific screening.

CONCLUSION

The guidelines present comprehensive, evidence-based information and instructions for the treatment of osteoporosis. It is expected that the quality of medical care for patients with this clinical picture will be substantially improved at all levels of the Austrian healthcare system.

Diagnostic performance of radiomics for predicting osteoporosis in adults: a systematic review and meta-analysis

This study aimed to assess the diagnostic accuracy of radiomics for predicting osteoporosis and the quality of radiomic studies. The study protocol was prospectively registered on PROSPERO (CRD42023425058). We searched PubMed, EMBASE, Web of Science, and Cochrane Library databases from inception to June 1, 2023, for eligible articles that applied radiomic techniques to diagnosing osteoporosis or abnormal bone mass. Quality and risk of bias of the included studies were evaluated with radiomics quality score (RQS), METhodological RadiomICs Score (METRICS), and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tools. The data analysis utilized the R program with mada, metafor, and meta packages. Ten retrospective studies with 5926 participants were included in the systematic review and meta-analysis. The overall risk of bias and applicability concerns for each domain of the studies were rated as low, except for one study which was considered to have a high risk of flow and time bias. The mean METRICS score was 70.1% (range 49.6-83.2%). There was moderate heterogeneity across studies and meta-regression identified sources of heterogeneity in the data, including imaging modality, feature selection method, and classifier. The pooled diagnostic odds ratio (DOR) under the bivariate random effects model across the studies was 57.22 (95% CI 27.62-118.52). The pooled sensitivity and specificity were 87% (95% CI 81-92%) and 87% (95% CI 77-93%), respectively. The area under the summary receiver operating characteristic curve (AUC) of the radiomic models was 0.94 (range 0.8 to 0.98). The results supported that the radiomic techniques had good accuracy in diagnosing osteoporosis or abnormal bone mass. The application of radiomics in osteoporosis diagnosis needs to be further confirmed by more prospective studies with rigorous adherence to existing guidelines and multicenter validation.

Transmenopausal changes in cortical bone quality

Bone's resistance to fracture depends on its amount and quality, the latter including its structural and material/compositional properties. Bone material properties are dependent on bone turnover rates, which are significantly elevated immediately following menopause. Previously published data reported that following menopause, the amount of organic matrix synthesized at actively forming surfaces is significantly decreased, while glycosaminoglycan content was also modulated at resorbing surfaces, in the cancellous compartment. In the present study, we used Raman microspectroscopic analysis of paired iliac crest biopsies obtained before and shortly after menopause (1 year after cessation of menses) in healthy females to investigate changes in material/compositional properties due to menopause, in the cortical compartment. Specifically, the mineral/matrix ratio, the relative proteoglycan content, the mineral maturity/crystallinity, and the relative pyridinoline collagen cross-link content were determined at actively forming intracortical surfaces (osteons) as a function of tissue age, as well as in interstitial bone. Results indicated that it is the freshly synthesized organic matrix content that significantly declines following menopause, in agreement with what was previously reported for the cancellous compartment. This decline was not evident in the freshly deposited mineral content. None of the compositional/quality properties were altered following menopause either. Finally, no differences in any of the monitored parameters were evident in cortical interstitial bone.

Intrarater and Interrater Reliability of Quantitative Ultrasound Speed of Sound by Trained Raters at the Distal Radius in Postmenopausal Women

BACKGROUND AND PURPOSE

Quantitative ultrasound (QUS) performed at the distal radius shows potential as an effective tool for evaluating fracture risk, especially in postmenopausal women, but the reliability of this tool has not been reported in this patient population. This study investigated the within-day intrarater and interrater reliability of trained raters performing QUS measures at the distal radius of postmenopausal community-dwelling women.

METHODS

Eighteen women between the ages of 56 and 87 years were recruited from senior centers in the Greenville area of South Carolina and consented to participate. A QUS bone sonometer was used in this study; the trained raters performed 3 repeated speed of sound (SOS) measures at the nondominant radius of each participant on the same day. Intraclass correlation coefficients (ICCs) were calculated (model 3,1 for intrarater and 2,3 for interrater reliability) to determine the reliability within and between raters. In addition, we calculated the standard error of measurement (SEM) and the minimal detectable change at 95% confidence interval (MDC 95 ).

RESULTS

The within-day intrarater reliability was excellent for both physical therapist raters (ICC (3,1) ranging from 0.93 to 0.91). The SEM and MDC for the within-day intrarater reliability measures were small for both raters (SEM = 36.79-38.75 or 0.92%-0.97% of the pooled mean; MDC 95  = 101.99-107.40). The interrater reliability for SOS measurements using radial QUS was good with an ICC (2,3) of 0.77 (95% CI, 0.36-0.92) for 3 averaged measures. The SEM and MDC were larger for the interrater reliability measures (SEM = 62.79 or 1.57% of the pooled mean; MDC 95  = 174.05).

CONCLUSIONS

Quantitative ultrasound SOS measurement at the distal radius showed excellent within-day intrarater and good interrater (when 3 measures were averaged) reliability in community-dwelling postmenopausal women. The SEM and MDC 95 were also low for interrater reliability when a mean of 3 trials was used. This study is the first to demonstrate that this particular QUS device at the radius may be a reliable fracture risk screening tool for postmenopausal women.

Identifying Key Genes and Their Associated Molecular Pathways in Lupus Nephritis-Osteoporosis: An In-Silico Analysis

Nephritis and osteoporosis are debilitating medical conditions that significantly impact human health and reduce quality of life. To develop potential therapeutic strategies for these disorders necessitates understanding the genetic and molecular mechanisms. Here, we employed bioinformatics techniques purposed to find key genes and associated pathways responsible for nephritis-osteoporosis comorbidity. Six microarray datasets of systemic lupus erythematosus (SLE) and osteoporosis were retrieved from the Gene Expression Omnibus (GEO) database. Post normalization of data sets LIMMA package was utilized for differential expression analysis, among the datasets 44 differentially expressed genes (DEGs) were identified. The identified 44 genes were further analyzed for gene ontology (GO) where it was found that these genes are involved in defense response, organism interactions, and response to external stimuli. In predicting the molecular function, they were involved in several biological processes including binding to lipopolysaccharides and having peptidase and hydrolase activities. Firstly, the identified genes were primarily associated with certain granules such as specific granules and secretory granules in the aspect of cellular components. Enrichment analysis pointed out the potential pathways linked to the immune system, neutrophil degranulation, innate immunity, and immune response to tuberculosis. To examine interactions among DEGs, a complex protein-protein interaction (PPI) network was built, resulting in the identification of seven hub genes, CXCL8, ELANE, LCN2, MMP8, IFIT1, MX1, and ISG15. The study suggests that these elucidated hub genes might have high potential to be exploited as promising biomarkers and therapeutic targets in nephritis-osteoporosis. Taken together, this study provided deeper insights into the genetic and molecular basis for the comorbidity of nephritis and osteoporosis.

A few-shot learning framework for the diagnosis of osteopenia and osteoporosis using knee X-ray images

OBJECTIVE

We developed a few-shot learning (FSL) framework for the diagnosis of osteopenia and osteoporosis in knee X-ray images.

METHODS

Computer vision models containing deep convolutional neural networks were fine-tuned to enable generalization from natural images (ImageNet) to chest X-ray images (normal vs. pneumonia, base images). Then, a series of automated machine learning classifiers based on the Euclidean distances of base images were developed to make predictions for novel images (normal vs. osteopenia vs. osteoporosis). The performance of the FSL framework was compared with that of junior and senior radiologists. In addition, the gradient-weighted class activation mapping algorithm was used for visual interpretation.

RESULTS

In Cohort #1, the mean accuracy (0.728) and sensitivity (0.774) of the FSL models were higher than those of the radiologists (0.512 and 0.448). A diagnostic pipeline of FSL model (first)-radiologists (second) achieved better performance (0.653 accuracy, 0.582 sensitivity, and 0.816 specificity) than radiologists alone. In Cohort #2, the diagnostic pipeline also showed improved performance.

CONCLUSIONS

The FSL framework yielded practical performance with respect to the diagnosis of osteopenia and osteoporosis in comparison with radiologists. This retrospective study supports the use of promising FSL methods in computer-aided diagnosis tasks involving limited samples.

DXA evaluation of bone fragility 2 years after bariatric surgery in patients with obesity

Purpose

The primary objective was to evaluate bone fragility on dual X-ray absorptiometry (DXA) in patients with obesity before and 2 years after bariatric surgery. The secondary objective was to identify risk factors for the development of a bone mineral density ≤ -2 SD at 2 years.

Methods

This descriptive study included patients with obesity who underwent DXA before and 2 years (±6 months) after bariatric surgery. The BMD and the T-score were assessed at the lumbar spine, femoral neck and total hip. Data on body composition on DXA were also collected. The diagnosis of osteoporosis was retained for a T-score ≤ - 2.5 SD at any measured location. Osteopenia, or low bone mass, was defined by -2.5 SD < T-score ≤ -1 SD.

Results

Among the 675 included patients, 77.8 % were women, with a mean age of 49.5 years (±11.1). After bariatric surgery, there were significantly more patients with osteoporosis: 3.6 % vs. 0.9 % (p = 0.0001). Multivariate analysis revealed that the risk factors for developing a bone mineral density ≤ -2 SD 2 years after bariatric surgery in patients with normal BMD before surgery were age and lower lean and fat mass before the surgery (OR = 1.07, 95%CI = [1.03-1.12], OR = 0.83, 95%CI = [0.77-0.91], OR = 1.08, 95%CI = [1.02-1.15], respectively).

Conclusion

There was a significantly higher prevalence of osteoporosis and low bone mass 2 years after bariatric surgery. Older age and lower lean and fat mass at baseline were risk factors for the development of a BMD ≤ -2SD at 2 years.

Estrogen deficiency induces changes in bone matrix bound water that do not closely correspond with bone turnover

Postmenopausal osteoporosis, marked by estrogen deficiency, is a major contributor to osteoporotic fractures, yet early prediction of fractures in this population remains challenging. Our goal was to explore the temporal changes in bone-specific inflammation, oxidative stress, bone turnover, and bone-matrix water, and their relationship with estrogen deficiency-induced modifications in bone structure and mechanical properties. Additionally, we sought to determine if emerging clinically translatable imaging techniques could capture early bone modifications prior to standard clinical imaging. Two-month-old female Sprague Dawley rats (n = 48) underwent ovariectomy (OVX, n = 24) or sham operations (n = 24). A subgroup of n = 8 rats per group was sacrificed at 2-, 5-, and 10-weeks post-surgery to assess the temporal relationships of inflammation, oxidative stress, bone turnover, bone matrix water, mechanics, and imaging outcomes. OVX rats exhibited higher body weight compared to sham rats at all time points. By 5-weeks, OVX animals showed elevated markers of inflammation and oxidative stress in cortical bone, which persisted throughout the study, while cortical bone formation rate did not differ from sham until 10-weeks. DXA outcomes did not reveal differences between OVX and sham at any time point. Bound water, assessed using ultrashort echo time magnetic resonance imaging (UTE MRI), was lower in OVX at the earliest time point (2-weeks) and reduced again at 10-weeks with no difference at 5-weeks. These data demonstrate that bound water assessment using novel UTE MRI technology was lower at the earliest time point following OVX. However, no temporal relationship with bone turnover, inflammation, or oxidative stress was observed at the time points assessed in this study. These findings underscore both the increased need to understand bone hydration changes and highlight the usefulness of UTE MRI for non-invasive bone hydration measurements.

Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis

INTRODUCTION

Artificial intelligence (AI)-based systems using chest images are potentially reliable for diagnosing osteoporosis.

METHODS

We performed a systematic review and meta-analysis to assess the diagnostic accuracy of chest X-ray and computed tomography (CT) scans using AI for osteoporosis in accordance with the diagnostic test accuracy guidelines. We included any type of study investigating the diagnostic accuracy of index test for osteoporosis. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, and IEEE Xplore Digital Library on November 8, 2023. The main outcome measures were the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) for osteoporosis and osteopenia. We described forest plots for sensitivity, specificity, and AUC. The summary points were estimated from the bivariate random-effects models. We summarized the overall quality of evidence using the Grades of Recommendation, Assessment, Development, and Evaluation approach.

RESULTS

Nine studies with 11,369 participants were included in this review. The pooled sensitivity, specificity, and AUC of chest X-rays for the diagnosis of osteoporosis were 0.83 (95% confidence interval [CI] 0.75, 0.89), 0.76 (95% CI 0.71, 0.80), and 0.86 (95% CI 0.83, 0.89), respectively (certainty of the evidence, low). The pooled sensitivity and specificity of chest CT for the diagnosis of osteoporosis and osteopenia were 0.83 (95% CI 0.69, 0.92) and 0.70 (95% CI 0.61, 0.77), respectively (certainty of the evidence, low and very low).

CONCLUSIONS

This review suggests that chest X-ray with AI has a high sensitivity for the diagnosis of osteoporosis, highlighting its potential for opportunistic screening. However, the risk of bias of patient selection in most studies were high. More research with adequate participants' selection criteria for screening tool will be needed in the future.

Association of dietary carbohydrate intake with bone mineral density, osteoporosis and fractures among adults without diabetes: Evidence from National Health and Nutrition Examination Survey

Background

The impact of dietary carbohydrate intake on bone health remains a subject of controversy, potentially influenced by individuals with diabetic osteoporosis who exhibit normal or elevated bone mineral density (BMD). The cross-sectional study was conducted to explore the association between carbohydrate intake and BMD, osteoporosis and fractures among adults without diabetes, based on the National health and nutrition examination survey (NHANES).

Methods

Participants were from the NHANES 2005-2010, excluding individuals with diabetes and those with incomplete data. The association between carbohydrate intake and BMD was analyzed using Spearman correlation, linear regression analysis and subgroup analysis, respectively. The association between carbohydrate intake and osteoporosis/fractures was analyzed using weighted logistic regression analysis.

Results

A total of 7275 adult participants were included and their dietary carbohydrate intake was inversely associated with BMD in the total femur [β = -0.20 95%CI (-0.30, -0.10); p < 0.001], femoral neck [β = -0.10 95%CI (-0.20, -0.00); p = 0.002], and lumbar spine [β = -0.10 95%CI (-0.20, -0.00); p = 0.004]. Stratified analysis indicated that individuals aged 65 and over, women, and non-Hispanic whites were more likely to have lower BMD. Furthermore, a higher intake of dietary carbohydrates was associated with an increased risk of osteoporosis [OR = 1.001 95%CI (1.001, 1.001); p < 0.001] and fractures at the hip [OR = 1.005 95%CI (1.005, 1.005); p < 0.001], wrist [OR = 1.001 95%CI (1.001, 1.001), p < 0.001], and spine [OR = 1.003 95%CI(1.003, 1.003); p < 0.001].

Conclusions

A higher carbohydrate diet is associated with lower BMD and a higher risk of osteoporosis and fractures among adults without diabetes, and a higher carbohydrate consumption show a stronger effect in individuals aged 65 and over, women, and non-Hispanic whites.

Diversity of the diet is correlated with osteoporosis in post-menopausal women: an Iranian case-control study

Background

Proper nutrition is a crucial factor in preventing osteoporosis, a significant pathological cause linked to skeletal weakness; this study investigated the relationship between dietary diversity score and food group diversity score with osteoporosis in postmenopausal women.

Methods

This case-control study was conducted on 378 menopausal women aged 45-85 in Tehran, Iran. The age-matching method to control the confounding effect of age was used. The method of dual-energy X-ray absorptiometry (DXA) was used for assessing the bone mineral density of lumbar vertebrae and femoral neck. The bone mass status was evaluated with WHO criteria. All subjects were divided into the osteoporosis group and the non-osteoporosis group according to their T-score. A convenience sampling method was utilized to select the participants, which included two groups: case (n = 189) and control (n = 189). Data was collected using demographic and anthropometric information questionnaires, a valid 147 item food frequency questionnaire, and a physical activity questionnaire. Statistical analyses were conducted using SPSS-26, and p-values less than 0.05 were deemed to be statistically significant.

Results

The results indicated significant differences in weight, body mass index, physical activity, smoking, and alcohol use between the two groups. The mean ± standard deviation of dietary diversity score (DDS) was lower in participants with osteoporosis (case) (3.31 ± 1.26) than in control (4.64 ± 1.33) (p < 0.001). The mean ± standard deviation of diversity score of cereals, fruits, and vegetables in the osteoporosis group (respectively: 0.71 ± 0.21, 0.94 ± 0.76, and 0.45 ± 0.44) was less than the control group (respectively: 0.80 ± 0.21, 1.64 ± 0.55 and 0.87 ± 0.42) (p < 0.001). After adjusting the confounding variables, the risk of osteoporosis had an inverse relationship with the diversity score of vegetable (OR = 0.16; 95%CI: 0.07-0.35), bread and cereal (OR = 0.21; 95% CI: 0.05-0.87) and fruit (OR = 0.35; 95%CI: 0.22-0.56) (p < 0.05). Nevertheless, no discernible correlation was seen between the tertiles of DDS, dairy and meat diversity score, and osteoporosis.

Conclusion

We found a correlation between the diversity score of fruits, vegetables, and grains and osteoporosis. However, there is no significant correlation between the DDS triads and the diversity score of dairy products and meats with osteoporosis.

Patients with Periprosthetic Femoral Hip Fractures are Commonly Classified as Having Osteoporosis Based on DXA Measurements

Periprosthetic femoral hip fractures are subject to an increasing incidence and are often considered to be related to osteoporosis. However, there are no available studies that have determined the frequency of osteoporosis in affected patients using gold standard dual-energy X-ray absorptiometry (DXA). In this retrospective comparative study, we analyzed the DXA results of 40 patients with periprosthetic femoral hip fractures who were treated surgically in our department. DXA measurements were performed at the total hip and the lumbar spine to determine bone mineral density T-scores. Data were compared to two age-, sex-, and BMI-matched control groups in which patients underwent DXA prior to aseptic revision surgery for other causes or primary THA (consisting of 40 patients each). The mean T-score in the periprosthetic fracture cohort was significantly lower (- 1.78 ± 1.78) than that of the aseptic revision (- 0.65 ± 1.58, mean difference - 1.13 [95% CI - 1.88 to - 0.37]; p = 0.001) and the primary THA cohort (- 0.77 ± 1.34, mean difference - 1.01 [95% CI - 1.77 to - 0.26]; p = 0.005). Accordingly, osteoporosis was detected more frequently (45%) in the fracture cohort compared to patients undergoing aseptic revision (12.5%) and primary THA (10%). In conclusion, almost half of the patients with periprosthetic femoral hip fractures have osteoporosis according to DXA measurements. A regular assessment of bone health in THA enables identification of patients with osteoporosis who likely benefit from initiation of osteoporosis medication and cemented stem fixation.

Association between arteriosclerosis index and lumbar bone mineral density in U.S adults: a cross-sectional study from the NHANES 2011-2018

Background

The arteriosclerosis index, defined as the ratio of non-high density lipoprotein cholesterol to high density lipoprotein cholesterol (NHHR), has emerged as a novel biomarker for various diseases. The relationship between NHHR and lumbar bone mineral density (BMD) has not been previously examined.

Methods

This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018. NHHR was calculated as (total cholesterol-high-density lipoprotein cholesterol)/high-density lipoprotein cholesterol. Lumbar BMD was calculated to Z scores. Weighted multivariate linear regression, subgroup analysis, interaction analysis, generalized additive model, and two-piecewise linear regression were used.

Results

A total of 8,602 participants were included. The negative association between NHHR and lumbar BMD was consistent and significant (Model 1: β = -0.039, 95% CI: -0.055, -0.023, p < 0.001; Model 2: β = -0.045, 95% CI: -0.062, -0.027, p < 0.001; Model 3: β = -0.042, 95% CI: -0.061, -0.023, p < 0.001). The linear relationship between NHHR and lumbar BMD was significantly influenced by body mass index (p for interaction = 0.012) and hypertension (p for interaction = 0.047). Non-linear associations between NHHR and lumbar BMD Z scores were observed in specific populations, including U-shaped, reverse U-shaped, L-shaped, reverse L-shaped, and U-shaped relationships among menopausal females, underweight participants, those with impaired glucose tolerance, those with diabetes mellitus and those taking anti-hyperlipidemic drugs, respectively.

Conclusions

NHHR exhibited a negative association with lumbar BMD, but varying across specific populations. These findings suggest that NHHR should be tailored to individual levels to mitigate bone loss through a personalized approach. Individuals at heightened risk of cardiovascular disease should focus on their bone health.

Ultrashort echo time MRI detects significantly lower collagen but higher pore water in the tibial cortex of female patients with osteopenia and osteoporosis

Ultrashort echo time (UTE) MRI can quantify the major proton pool densities in cortical bone, including total (TWPD), bound (BWPD), and pore water (PWPD) proton densities, as well as the macromolecular proton density (MMPD), associated with the collagen content, which is calculated using macromolecular fraction (MMF) from UTE magnetization transfer (UTE-MT) modeling. This study aimed to investigate the differences in water and collagen contents in tibial cortical bone, between female osteopenia (OPe) patients, osteoporosis (OPo) patients, and young participants (Young). Being postmenopausal and above 55 yr old were the inclusion criteria for OPe and OPo groups. The tibial shaft of 14 OPe (72.5 ± 6.8 yr old), 31 OPo (72.0 ± 6.4 yr old), and 31 young subjects (28.0 ± 6.1 yr old) were scanned using a knee coil on a clinical 3T scanner. Basic UTE, inversion recovery UTE, and UTE-MT sequences were performed. Investigated biomarkers were compared between groups using Kruskal-Wallis test. Spearman's correlation coefficients were calculated between the TH DXA T-score and UTE-MRI results. MMF, BWPD, and MMPD were significantly lower in OPo patients than in the young group, whereas T1, TWPD, and PWPD were significantly higher in OPo patients. The largest OPo/Young average percentage differences were found in MMF (41.9%), PWPD (103.5%), and MMPD (64.0%). PWPD was significantly higher (50.7%), while BWPD was significantly lower (16.4%) in OPe than the Young group on average. MMF was found to be significantly lower (27%) in OPo patients compared with OPe group. T1, MMF, TWPD, PWPD, and MMPD values significantly correlated with the TH DXA T-scores (provided by the patients and only available for OPe and OPo patients). DXA T-score showed the highest correlations with PWPD (R = 0.55) and MMF (R = 0.56) values. TWPD, PWPD, and MMF estimated using the UTE-MRI sequences were recommended to evaluate individuals with OPe and OPo.

Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks

Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis, it is expensive and not widely available. In contrast, kidney-ureter-bladder (KUB) radiographs are inexpensive and frequently ordered in clinical practice. Thus, it is a potential screening tool for osteoporosis. In this study, we explored the possibility of predicting the bone mineral density (BMD) and classifying high-risk patient groups using KUB radiographs. We proposed DeepDXA-KUB, a deep learning model that predicts the BMD values of the left hip and lumbar vertebrae from an input KUB image. The datasets were obtained from Taiwanese medical centers between 2006 and 2019, using 8913 pairs of KUB radiographs and DXA examinations performed within 6 months. The images were randomly divided into training and validation sets in a 4:1 ratio. To evaluate the model's performance, we computed a confusion matrix and evaluated the sensitivity, specificity, accuracy, precision, positive predictive value, negative predictive value, F1 score, and area under the receiver operating curve (AUROC). Moderate correlations were observed between the predicted and DXA-measured BMD values, with a correlation coefficient of 0.858 for the lumbar vertebrae and 0.87 for the left hip. The model demonstrated an osteoporosis detection accuracy, sensitivity, and specificity of 84.7 %, 81.6 %, and 86.6 % for the lumbar vertebrae and 84.2 %, 91.2 %, and 81 % for the left hip, respectively. The AUROC was 0.939 for the lumbar vertebrae and 0.947 for the left hip, indicating a satisfactory performance in osteoporosis screening. The present study is the first to develop a deep learning model based on KUB radiographs to predict lumbar spine and femoral BMD. Our model demonstrated a promising correlation between the predicted and DXA-measured BMD in both the lumbar vertebrae and hip, showing great potential for the opportunistic screening of osteoporosis.

Phantomless calibration of CT scans for hip fracture risk prediction in silico: Comparison with phantom-based calibration

Finite element models built from quantitative computed tomography images rely on element-wise mapping of material properties starting from Hounsfield Units (HU), which can be converted into mineral densities upon calibration. While calibration is preferably carried out by scanning a phantom with known-density components, conducting phantom-based calibration may not always be possible. In such cases, a phantomless procedure, where the scanned subject's tissues are used as a phantom, is an interesting alternative. The aim of this study was to compare a phantom-based and a phantomless calibration method on 41 postmenopausal women. The proposed phantomless calibration utilized air, adipose, and muscle tissues, with reference equivalent mineral density values of -797, -95, and 38 mg/cm3, extracted from a previously performed phantom-based calibration. A 9-slice volume of interest (VOI) centred between the femoral head and knee rotation centres was chosen. Reference HU values for air, adipose, and muscle tissues were extracted by identifying HU distribution peaks within the VOI, and patient-specific calibration was performed using linear regression. Comparison of FE models calibrated with the two methods showed average relative differences of 1.99% for Young's modulus1.30% for tensile and 1.34% for compressive principal strains. Excellent correlations (R2 > 0.99) were identified for superficial maximum tensile and minimum compressive strains. Maximum normalised root mean square relative error (RMSRE) values settled at 4.02% for Young's modulus, 2.99% for tensile, and 3.22% for compressive principal strains, respectively. The good agreement found between the two methods supports the adoption of the proposed methodology when phantomless calibration is needed.

Clinical Validation of a Deep Learning-Based Software for Lumbar Bone Mineral Density and T-Score Prediction from Chest X-ray Images

Screening for osteoporosis is crucial for early detection and prevention, yet it faces challenges due to the low accuracy of calcaneal quantitative ultrasound (QUS) and limited access to dual-energy X-ray absorptiometry (DXA) scans. Recent advances in AI offer a promising solution through opportunistic screening using existing medical images. This study aims to utilize deep learning techniques to develop a model that analyzes chest X-ray (CXR) images for osteoporosis screening. This study included the AI model development stage and the clinical validation stage. In the AI model development stage, the combined dataset of 5122 paired CXR images and DXA reports from the patients aged 20 to 98 years at a medical center was collected. The images were enhanced and filtered for hardware retention such as pedicle screws, bone cement, artificial intervertebral discs or severe deformity in target level of T12 and L1. The dataset was then separated into training, validating, and testing datasets for model training and performance validation. In the clinical validation stage, we collected 440 paired CXR images and DXA reports from both the TCVGH and Joy Clinic, including 304 pared data from TCVGH and 136 paired data from Joy Clinic. The pre-clinical test yielded an area under the curve (AUC) of 0.940, while the clinical validation showed an AUC of 0.946. Pearson's correlation coefficient was 0.88. The model demonstrated an overall accuracy, sensitivity, and specificity of 89.0%, 88.7%, and 89.4%, respectively. This study proposes an AI model for opportunistic osteoporosis screening through CXR, demonstrating good performance and suggesting its potential for broad adoption in preliminary screening among high-risk populations.

PoCOsteo: generic novel platform for bone turnover marker measurement & monitoring

Despite the increasing efforts in improving bone health assessments, current diagnostics suffer from critical shortcomings. The present article therefore describes a multiplex label-free immunosensor designed and validated for the assessment of two bone turnover markers (BTMs), namely beta isomerized C-terminal telopeptide of type I collagen (CTx) and Procollagen I Intact N-Terminal (PINP), the combination of which is needed to illustrate an accurate overview of bone health. The immunosensor was then tested outside and inside of a microsystem, with the aim of becoming compatible with a point of care system fabricated for automated assessment of these biomarkers later-on at patient side. Custom-made monoclonal antibodies were specifically designed for this purpose in order to guarantee the selectivity of the immunosensor. In the final platform, a finger prick blood sample is introduced into the microfluidic manifolds without any need for sample preparation step, making the tool suitable for near patient and outside of the central laboratory applications. The platform was exploited in 30 real blood samples with the results validated using electrochemiluminescence immunoassay. The results revealed the platform was capable of measuring the target analyte with high sensitivity and beyond the recommended clinical reference range for each biomarker (CTx: 104-1028 ng L-1 and PINP: 16-96 μg L-1, correspondingly). They also showed the platform to have a limit of detection of 15 (ng L-1) and 0.66 (μg L-1), a limit of quantification of 49 (ng L-1) and 2.21 (μg L-1), and an inter- and intra-assay coefficient of variance of 5.39-6.97% and 6.81-5.37%, for CTx and PINP respectively, which is comparable with the gold standard. The main advantage of the platform over the state-of-the art was the capability of providing the results for two markers recommended for assessing bone health within 15 minutes and without the need for skilled personnel or costly infrastructure.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study

BACKGROUND

There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling.

METHODS

A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening.

RESULTS

At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%.

CONCLUSIONS

The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Pronounced cortical porosity and sex-specific patterns of increased bone and osteocyte lacunar mineralization characterize the human distal fibula with aging

The high occurrence of distal fibula fractures among older women suggests a potential link to impaired bone health. Here we used a multiscale imaging approach to investigate the microarchitecture, mineralization, and biomechanics of the human distal fibula in relation to age and sex. Micro-computed tomography was performed to analyze the local volumetric bone mineral density and various microarchitectural parameters of the trabecular and the cortical compartment. Bone mineral density distribution and osteocyte lacunar parameters were quantified using quantitative backscattered electron imaging in periosteal, endocortical, and trabecular regions. Additionally, cortical hardness and Young's modulus were assessed by nanoindentation. While cortical porosity strongly increased with age independent of sex, trabecular microarchitecture remained stable. Notably, nearly half of the specimens showed non-bony hypermineralized tissue located at the periosteum, similar to that previously detected in the femoral neck, with no consistent association with advanced age. Independent of this finding, cortical and trabecular mineralization, i.e., mean calcium content, as well as endocortical tissue hardness increased with age in males but not females. Importantly, we also observed mineralized osteocyte lacunae that increased with age specifically in females. In conclusion, our results indicate that skeletal aging of the distal fibula is signified not only by pronounced cortical porosity but also by an increase in mineralized osteocyte lacunae in females. These findings may provide an explanation for the increased occurrence of ankle fractures in older women.

Deep learning in the radiologic diagnosis of osteoporosis: a literature review

OBJECTIVE

Osteoporosis is a systemic bone disease characterized by low bone mass, damaged bone microstructure, increased bone fragility, and susceptibility to fractures. With the rapid development of artificial intelligence, a series of studies have reported deep learning applications in the screening and diagnosis of osteoporosis. The aim of this review was to summary the application of deep learning methods in the radiologic diagnosis of osteoporosis.

METHODS

We conducted a two-step literature search using the PubMed and Web of Science databases. In this review, we focused on routine radiologic methods, such as X-ray, computed tomography, and magnetic resonance imaging, used to opportunistically screen for osteoporosis.

RESULTS

A total of 40 studies were included in this review. These studies were divided into three categories: osteoporosis screening (n = 20), bone mineral density prediction (n = 13), and osteoporotic fracture risk prediction and detection (n = 7).

CONCLUSIONS

Deep learning has demonstrated a remarkable capacity for osteoporosis screening. However, clinical commercialization of a diagnostic model for osteoporosis remains a challenge.

Development and Validation of a Nomogram Model for Individualizing the Risk of Osteopenia in Abdominal Obesity

OBJECTIVE

This study was aimed to create and validate a risk prediction model for the incidence of osteopenia in individuals with abdominal obesity.

METHODS

Survey data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2013-2014 and 2017-2018 was selected and included those with waist circumferences ≥102 m in men and ≥88 cm in women, which were defined as abdominal obesity. A multifactor logistic regression model was constructed using LASSO regression analysis to identify the best predictor variables, followed by the creation of a nomogram model. The model was then verified and evaluated using the consistency index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA). Results Screening based on LASSO regression analysis revealed that sex, age, race, body mass index (BMI), alkaline phosphatase (ALP) and Triglycerides (TG) were significant predictors of osteopenia development in individuals with abdominal obesity (P < 0.05). These six variables were included in the nomogram. In the training and validation sets, the C indices were 0.714 (95 % CI: 0.689-0.738) and 0.701 (95 % CI: 0.662-0.739), respectively, with corresponding AUCs of 0.714 and 0.701. The nomogram model exhibited good consistency with actual observations, as demonstrated by the calibration curve. The DCA nomogram showed that early intervention for at-risk populations has a net positive impact.

CONCLUSION

Sex, age, race, BMI, ALP and TG are predictive factors for osteopenia in individuals with abdominal obesity. The constructed nomogram model can be utilized to predict the clinical risk of osteopenia in the population with abdominal obesity.

Areal bone mineral density is not associated with femoral stem subsidence in patients younger than 70 years undergoing total hip arthroplasty

INTRODUCTION

Femoral stem subsidence is a known complication after uncemented total hip arthroplasty (THA). The purpose of this study was to determine the frequency of osteoporosis and to investigate the relationship between areal bone mineral density (aBMD) and subsidence in a cohort of patients younger than 70 years.

METHODS

One hundred consecutive patients (age 60 ± 6 years; 52 female, 48 male) undergoing uncemented THA using a collarless press fit femoral stem were retrospectively reviewed. Dual-energy X-ray absorptiometry (DXA) was performed preoperatively at the proximal femur and lumbar spine, and if not feasible at these sites, at the distal radius. DXA results were compared to a cohort of 100 patients ≥ 70 years scheduled for cemented THA. Age, sex, and body mass index (BMI), canal flare index (CFI), and canal fill ratio (CFR) were assessed. Analysis of stem subsidence and migration was performed on standardized, calibrated radiographs obtained postoperatively and at follow-up.

RESULTS

The frequency of osteoporosis was considerably lower in the study cohort compared to patients ≥ 70 years (7% vs. 19%, p = 0.02). Illustrated by the high CFR (mean 96 ± 4%) in the mid-stem region, a sufficient press fit was achieved. After a mean follow-up of 7.4 months, the mean stem subsidence was 0.9 ± 0.9 mm. Only two patients had subsidence greater than 3 mm, one of whom was morbidly obese and the other diagnosed with severe osteoporosis. There were no correlations between any of the parameters (CFI, CFR, age, sex, BMI) and femoral stem subsidence. In addition, aBMD T-scores showed no correlations with subsidence.

CONCLUSION

aBMD by DXA does not appear to be associated with stem subsidence in patients younger than 70 years and with adequate press fit.

Skeletal Status in Patients Scheduled for Elective Lumbar Spine Surgery: Comparison of Discectomy, Decompression, Fusion, and Revision

STUDY DESIGN

Retrospective Cohort Study.

OBJECTIVES

To investigate and compare the prevalence of low bone mineral density (BMD) and abnormal laboratory bone metabolism parameters in patients undergoing elective primary discectomy, decompression, and fusion and to outline possible differences in these parameters between patients undergoing revision for skeletal vs non-skeletal complications.

METHODS

We retrospectively evaluated BMD measurements by dual-energy x-ray absorptiometry (DXA) in 389 consecutive patients scheduled for elective lumbar spine surgery. Next to demographic characteristics, laboratory bone metabolism parameters were assessed. Group comparisons were performed between primary discectomy, decompression, and fusion. In patients scheduled for revision surgery after fusion, potential differences in the skeletal status between those with skeletal vs non-skeletal complications were analyzed.

RESULTS

Osteoporosis by T-score was detected in 6.7%, 11.0% and 14.7% of the patients undergoing discectomy, decompression and fusion, respectively. While vitamin D deficiency (67.6%) and hyperparathyroidism (16.4%) were frequently detected, no differences in laboratory bone metabolism markers could be found between the groups. Female sex (P<.001), higher age (P=.01) and lower BMI (P<.001) were associated with lower BMD. In the cohort of patients undergoing revision surgery due to complications after fusion, those with skeletal complications did not differ in BMD or bone metabolism from those with non-skeletal complications.

CONCLUSIONS

Osteoporosis represents a relevant comorbidity in patients scheduled for elective spine surgery, which is why DXA should be routinely performed in these patients. However, DXA may provide limited information in identifying patients at increased risk for skeletal complications after fusion.

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Mineral Density Assessment From Low-Dose Chest Computed Tomography

RATIONALE AND OBJECTIVES

To develop an intelligent diagnostic model for osteoporosis screening based on low-dose chest computed tomography (LDCT). The model incorporates automatic deep-learning thoracic vertebrae of cancellous bone (TVCB) segmentation model and radiomics analysis.

MATERIALS AND METHODS

A total of 442 participants who underwent both LDCT and quantitative computed tomography (QCT) examinations were enrolled and were randomly allocated to the training, internal testing, and external testing cohorts. The TVCB automatic segmentation model was trained using VB-Net. The accuracy of the segmentation was evaluated using the Dice coefficient. Predictive models for assessing bone mineral density (BMD) were constructed utilizing radiomics analysis based on automatic segmentation (ASeg model) and manual segmentation (MSeg model), respectively. The BMD predictive model based on ASeg and MSeg included the identification of normal and abnormal BMD (first-level model), and osteopenia and osteoporosis (second-level model). The diagnostic performance of the radiomics models were evaluated using the area under the curve (AUC), sensitivity and specificity.

RESULTS

The Dice coefficients of the TVCB segmentation model in the internal and external testing cohorts were found to be 0.988 ± 0.014 and 0.939 ± 0.034, respectively. In the first-level model, the AUC of the ASeg model exhibited comparable performance to that of the MSeg model for both the internal (0.985 vs. 0.946, P = 0.080) and external (0.965 vs. 0.955, P = 0.724) testing cohorts. Similarly, in the second-level model, the AUC of the ASeg model was found to be comparable to that of the MSeg model for both the internal (0.933 vs. 0.920, P = 0.794) and external (0.907 vs. 0.892, P = 0.805) testing cohorts.

CONCLUSION

A fully automated pipeline for TVCB segmentation and BMD assessment with radiomics analysis can be used for opportunistic BMD screening in chest LDCT.

Transcriptome Sequencing Identifies Abnormal lncRNAs and mRNAs and Reveals Potentially Hub Immune-Related mRNA in Osteoporosis with Vertebral Fracture

Background

Recent studies have put forward the viewpoint of "bone immunology", which holds that the immune system and immune factors play an important regulatory role in the occurrence and development of osteoporosis. This study was intended to identify genetic characteristics of differentially expressed immune-related mRNA and lncRNA in patients combined with osteoporosis and vertebral fracture.

Methods

The peripheral blood samples were obtained from 3 groups of subjects: healthy control (HC), osteoporosis patients without vertebral fracture (OWF), and osteoporosis patients combined with vertebral fracture (OVF). The data were integrated to obtain differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs). Subsequently, the protein-protein interaction (PPI) networks were constructed. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses were performed. Cytoscape-cytoHubba plug-in was used to identify key DEmRNAs. Furthermore, lncRNA-miRNA-mRNA, mRNA-lncRNA co-expression and transcription factors (TFs) networks were constructed. In addition, real-time PCR verification was performed.

Results

Totally of 3378 lncRNA-mRNA pairs were obtained, and the lncRNA co-expressed mRNA was mainly enriched in immune-related pathways, especially in GO-biological process (GO-BP) analysis. A total of 8 hub immune-related DEmRNAs were obtained, including IL18R1, IL18RAP, SLC11A1, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1. The TFs network showed that 8 hub immune-related DEmRNAs had interacting TFs. The co-expression network showed that 7 hub immune-related DEmRNAs (IL18R1, IL18RAP, SLC11A1, CSF2RA, IL-1R2, PGLYRP1, and IL1R1) had lncRNA-mRNA co-expression relationship. In addition, the lncRNA-miRNA-mRNA network includes 32 miRNAs, 7 hub immune-related mRNAs (IL18R1, IL18RAP, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1), and 11 lncRNAs.

Conclusion

Our study provides a novel and in-depth identification of co-expressed mRNAs and lncRNAs in patients combined with osteoporosis and vertebral fracture at a molecular level. This may provide new candidate biomarkers for the diagnosis of patients with high-risk fractures in the future.

Zoledronate reduces loading-induced microdamage in cortical ulna of ovariectomized rats

As a daily physiological mechanism in bone, microdamage accumulation dissipates energy and helps to prevent fractures. However, excessive damage accumulation might bring adverse effects to bone mechanical properties, which is especially problematic among the osteoporotic and osteopenic patients treated by bisphosphonates. Some pre-clinical studies in the literature applied forelimb loading models to produce well-controlled microdamage in cortical bone. Ovariectomized animals were also extensively studied to assimilate human conditions of estrogen-related bone loss. In the present study, we combined both experimental models to investigate microdamage accumulation in the context of osteopenia and zoledronate treatment. Three-month-old normal and ovariectomized rats treated by saline or zoledronate underwent controlled compressive loading on their right forelimb to create in vivo microdamage, which was then quantified by barium sulfate contrast-enhanced micro-CT imaging. Weekly in vivo micro-CT scans were taken to evaluate bone (re)modeling and to capture microstructural changes over time. After sacrifice, three-point-bending tests were performed to assess bone mechanical properties. Results show that the zoledronate treatment can reduce cortical microdamage accumulation in ovariectomized rats, which might be explained by the enhancement of several bone structural properties such as ultimate force, yield force, cortical bone area and volume. The rats showed increased bone formation volume and surface after the generation of microdamage, especially for the normal and the ovariectomized groups. Woven bone formation was also observed in loaded ulnae, which was most significant in ovariectomized rats. Although all the rats showed strong correlations between periosteal bone formation and microdamage accumulation, the correlation levels were lower for the zoledronate-treated groups, potentially because of their lower levels of microdamage. The present study provides insights to further investigations of pharmaceutical treatments for osteoporosis and osteopenia. The same experimental concept can be applied in future studies on microdamage and drug testing.

Comparison of the prevalence of osteoporosis in people with spinal cord injury according to bone mineral density reference values for the diagnosis of osteoporosis: a retrospective, cross-sectional study

BACKGROUND

Spinal cord injury (SCI) is a complex cause of rapid low bone mass that easily predisposes the affected individuals to osteoporosis-induced fractures. Several studies have investigated osteoporosis pathophysiology in SCI; however, those associated with its diagnosis in SCI are limited. Additionally, errors in osteoporosis diagnosis and its prevalence vary based on the bone mineral density (BMD) reference values (BMDRV), and no studies have reported BMDRV application for osteoporosis diagnosis in individuals with SCI. Therefore, this study aimed to compare the prevalence of osteoporosis among Korean adults aged ≥ 50 years with SCI according to BMDRV for diagnosing osteoporosis.

METHODS

Overall, 855 patients with SCI who underwent BMD tests of the lumbar spine, femoral neck, and total hip at the National Rehabilitation Center (NRC) in Korea between 2010 and 2020 were included in this retrospective cross-sectional study. Osteoporosis was diagnosed in patients with SCI by comparing the differences in prevalence, diagnostic consistency, and risk factors according to the region-based BMDRV of the dual-energy x-ray absorptiometry (DXA) manufacturer and international BMDRV based on the Third National Health and Nutrition Examination Survey (NHANES III) data of females aged 20-29 years.

RESULTS

The prevalence of osteoporosis according to the T-score provided by a single reference population of the NHANES III (TNHA) (PONHA) (males: 26.69%; females: 69.35%) was significantly higher in females and males than that according to the T-scores provided by the DXA manufacturer (TDXA) (PODXA) (males: 15.32%; females: 43.15%). The lumbar spine and femoral neck were major osteoporosis diagnosis sites for the PODXA and PONHA, respectively. Risk factors for osteoporosis differed based on the probability of osteoporosis (also known as the OZ ratio) according to the BMD criteria; however, the risk factors were similar according to old age, female sex, low body mass index (BMI), and long SCI period. No significant relationship was noted between the different SCI-related clinical factors (p > 0.05).

CONCLUSIONS

The osteoporosis diagnostic site and prevalence in SCI differed according to the regional-based TDXA and international standards of the TNHA. Therefore, further studies on BMDRV are warranted to establish accurate diagnostic criteria for osteoporosis prevention in patients with SCI.