Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

IDEAL-IQ combined with intravoxel incoherent motion diffusion-weighted imaging for quantitative diagnosis of osteoporosis.

BACKGROUND: Osteoporosis (OP) is a common chronic metabolic bone disease characterized by decreased bone mineral content and microstructural damage, leading to increased fracture risk. Traditional methods for measuring bone density have limitations in accurately distinguishing vertebral bodies and are influenced by vertebral degeneration and surrounding tissues. Therefore, novel methods are needed to quantitatively assess changes in bone density and improve the accurate diagnosis of OP. METHODS: This study aimed to explore the applicative value of the iterative decomposition of water and fat with echo asymmetry and least-squares estimation-iron (IDEAL-IQ) sequence combined with intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the diagnosis of osteoporosis. Data from 135 patients undergoing dual-energy X-ray absorptiometry (DXA), IDEAL-IQ, and IVIM-DWI were prospectively collected and analyzed. Various parameters obtained from IVIM-DWI and IDEAL-IQ sequences were compared, and their diagnostic efficacy was evaluated. RESULTS: Statistically significant differences were observed among the three groups for FF, R2*, f, D, DDC values, and BMD values. FF and f values exhibited negative correlations with BMD values, with r=-0.313 and - 0.274, respectively, while R2*, D, and DDC values showed positive correlations with BMD values, with r = 0.327, 0.532, and 0.390, respectively. Among these parameters, D demonstrated the highest diagnostic efficacy for osteoporosis (AUC = 0.826), followed by FF (AUC = 0.713). D* exhibited the lowest diagnostic performance for distinguishing the osteoporosis group from the other two groups. Only D showed a significant difference between genders. The AUCs for IDEAL-IQ, IVIM-DWI, and their combination were 0.74, 0.89, and 0.90, respectively. CONCLUSIONS: IDEAL-IQ combined with IVIM-DWI provides valuable information for the diagnosis of osteoporosis and offers evidence for clinical decisions. The superior diagnostic performance of IVIM-DWI, particularly the D value, suggests its potential as a more sensitive and accurate method for diagnosing osteoporosis compared to IDEAL-IQ. These findings underscore the importance of integrating advanced imaging techniques into clinical practice for improved osteoporosis management and highlight the need for further research to explore the full clinical implications of these imaging modalities.

Radiofrequency echographic multi spectrometry (REMS) in the diagnosis and management of osteoporosis: state of the art.

Radiofrequency Echographic Multi Spectrometry (REMS) is a radiation-free, portable technology, which can be used for the assessment and monitoring of osteoporosis at the lumbar spine and femoral neck and may facilitate wider access to axial BMD measurement compared with standard dual-energy x-ray absorptiometry (DXA).There is a growing literature demonstrating a strong correlation between DXA and REMS measures of BMD and further work supporting 5-year prediction of fracture using the REMS Fragility Score, which provides a measure of bone quality (in addition to the quantitative measure of BMD).The non-ionising radiation emitted by REMS allows it to be used in previously underserved populations including pregnant women and children and may facilitate more frequent measurement of BMD.The portability of the device means that it can be deployed to measure BMD for frail patients at the bedside (avoiding the complications in transfer and positioning which can occur with DXA), in primary care, the emergency department, low-resource settings and even at home.The current evidence base supports the technology as a useful tool in the management of osteoporosis as an alternative to DXA.

Relationship between muscle and subcutaneous adipose tissue size and density and proximal femur bone in elderly women with hip fracture.

BACKGROUND: Both osteoporosis and sarcopenia are associated with aging, increasing the likelihood of falls in older adults and consequently raising the risk of hip fractures (HF). AIMS: To explore the relationship between the size and density of muscle and subcutaneous adipose tissue (SAT) and the bone mineral density (BMD) of the proximal femur in elderly women with HF. METHODS: Quantitative computed tomography (QCT) was conducted on the hips of 661 female participants who experienced low-energy acute HFs to measure both areal BMD (aBMD) and volume BMD (vBMD). Measurements were taken for the cross-sectional area (CSA) and density of the muscle around the hip and adjacent SAT. Multivariable linear regression models were applied to assess the relationship between these parameters. RESULTS: Most increases in the density of the gluteus medius and minimus muscle (G.Med/MinM) were correlated with higher BMD in the femoral neck fracture (FNF) group with osteoporosis. In the FNF group, gluteus maximus muscle (G.MaxM) density was negatively associated with the BMD parameters of the proximal femur in individuals with osteoporosis, while they were positively associated with nonosteoporosis. In the intertrochanteric fracture (ITF) group without osteoporosis, both FN aBMD and FN vBMD showed significant correlations with G.Med/MinM density. DISCUSSION: In women with HFs, bone and muscle are closely related. CONCLUSIONS: In older women with HFs, density but not CSA of the G.Med/MinM were associated with BMD parameters of the proximal femur. Osteoporosis may influence the relationship between G.MaxM density and proximal femur BMD in elderly women with FNF.

Dual Energy X-ray Absorptiometry (DXA) in the Management of Osteoporosis.

Null.

A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.

Purpose: The main objective of this study is to assess the possibility of using radiomics, deep learning, and transfer learning methods for the analysis of chest CT scans. An additional aim is to combine these techniques with bone turnover markers to identify and screen for osteoporosis in patients. Method: A total of 488 patients who had undergone chest CT and bone turnover marker testing, and had known bone mineral density, were included in this study. ITK-SNAP software was used to delineate regions of interest, while radiomics features were extracted using Python. Multiple 2D and 3D deep learning models were trained to identify these regions of interest. The effectiveness of these techniques in screening for osteoporosis in patients was compared. Result: Clinical models based on gender, age, and ß-cross achieved an accuracy of 0.698 and an AUC of 0.665. Radiomics models, which utilized 14 selected radiomics features, achieved a maximum accuracy of 0.750 and an AUC of 0.739. The test group yielded promising results: the 2D Deep Learning model achieved an accuracy of 0.812 and an AUC of 0.855, while the 3D Deep Learning model performed even better with an accuracy of 0.854 and an AUC of 0.906. Similarly, the 2D Transfer Learning model achieved an accuracy of 0.854 and an AUC of 0.880, whereas the 3D Transfer Learning model exhibited an accuracy of 0.740 and an AUC of 0.737. Overall, the application of 3D deep learning and 2D transfer learning techniques on chest CT scans showed excellent screening performance in the context of osteoporosis. Conclusion: Bone turnover markers may not be necessary for osteoporosis screening, as 3D deep learning and 2D transfer learning techniques utilizing chest CT scans proved to be equally effective alternatives.

SKELETAL HEALTH ASSESSMENT IN BRAZILIAN MEN WITH CELIAC DISEASE AT DIAGNOSIS: HOW IMPORTANT IS IT?

BACKGROUND: Low bone mass density (BMD) is an extraintestinal finding in celiac disease (CD). This may result in bone fractures leading to loss in quality of life. OBJECTIVE: To assess BMD in male CD patients at diagnosis according to the patient's age. METHODS: Descriptive retrospective carried out during the period between 2013 and 2023 in a single office that studied dual-energy X-ray absorptiometry (DXA) results in 28 male patients with a recent diagnosis of CD, divided into three groups: group 1 (age up to 18 years); group 2 (from 19 to 49 years of age) and group 3 (over 50 years of age). Were studied demographic and anthropometric parameters, time delay between symptoms onset and CD diagnosis and fracture occurrence. RESULTS: Celiac patients studied had median age 36.0 years (IQR=16.5-50.7). Among them, 39.3% had osteopenia and 14.3% had osteoporosis. Only 36% of the sample had normal DXA values (group 1 with 37.5%; group 2 with 46% and group 3 with 14.2%). No pathological fracture was observed in this sample. CD diagnosis delay observed had median 1.0 year (IQR=1.0-4.7). When the number of individuals with normal and abnormal DXA results were compared, there was no difference in body mass index, time of diagnosis delay or Marsh classification (P=0.18). CONCLUSION: Male patients at the time of CD diagnosis showed a high prevalence of low BMD, which was particularly evident in individuals over 50 years of age.

Evaluation of temporomandibular joint morphology and morphometry in male osteoporotic patients using advanced imaging and biochemical markers: A cross-sectional study.

Osteoporosis is a condition with reduced bone mass and disrupted architecture. Osteoporosis affects the Temporomandibular disorders (TMD) by changing bone density and quality. This study aims to determine the nature and extent of temporomandibular joint (TMJ) involvement in osteoporotic patients by correlating TMJ morphological changes detected by CBCT with systemic bone health indicated by BMD T-scores from DEXA and analyzing BTMs in serum and saliva. This study was a cross-sectional study conducted from May 2021 to December 2022. It involved 50 participants divided into two groups (N=25). One group was healthy male, while the other group had osteoporosis male. Saliva and blood samples were collected, and diagnostic imaging was conducted. The prevalence of various bone changes in the condyle was examined using CBCT. Erosion was found to be the most common, followed by Flattening, Osteophyte, and Subchondral cysts. The study group had significantly higher rates of smooth condyle, erosive lesions, and osteophytes compared to the control group. Pseudocyst decreased on the right side but increased on the left side. Pain on the right side increased more in the study group, and the T score for osteoporosis was higher in the study group. Joint spaces, condyle diameter, and glenoid cavity measurements differed significantly between sick and healthy people, as shown by CBCT (P≤0.001). Only the ALP parameter in the serum showed a significant increase in the study group compared to the control group. Saliva analysis revealed higher levels of calcium, osteocalcin, and ALP in the case group compared to the control group. The results of this study showed that CBCT as a specialized technique in imaging by providing detailed images can be used to evaluate osteoporosis and be used as an accurate diagnostic tool.

Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial.

Background Diagnosing osteoporosis is challenging due to its often asymptomatic presentation, which highlights the importance of providing screening for high-risk populations. Purpose To evaluate the effectiveness of dual-energy x-ray absorptiometry (DXA) screening in high-risk patients with osteoporosis identified by an artificial intelligence (AI) model using chest radiographs. Materials and Methods This randomized controlled trial conducted at an academic medical center included participants 40 years of age or older who had undergone chest radiography between January and December 2022 without a history of DXA examination. High-risk participants identified with the AI-enabled chest radiographs were randomly allocated to either a screening group, which was offered fully reimbursed DXA examinations between January and June 2023, or a control group, which received usual care, defined as DXA examination by a physician or patient on their own initiative without AI intervention. A logistic regression was used to test the difference in the primary outcome, new-onset osteoporosis, between the screening and control groups. Results Of the 40 658 enrolled participants, 4912 (12.1%) were identified by the AI model as high risk, with 2456 assigned to the screening group (mean age, 71.8 years ± 11.5 [SD]; 1909 female) and 2456 assigned to the control group (mean age, 72.1 years ± 11.8; 1872 female). A total of 315 of 2456 (12.8%) participants in the screening group underwent fully reimbursed DXA, and 237 of 315 (75.2%) were identified with new-onset osteoporosis. After including DXA results by means of usual care in both screening and control groups, the screening group exhibited higher rates of osteoporosis detection (272 of 2456 [11.1%] vs 27 of 2456 [1.1%]; odds ratio [OR], 11.2 [95% CI: 7.5, 16.7]; P < .001) compared with the control group. The ORs of osteoporosis diagnosis were increased in screening group participants who did not meet formalized criteria for DXA compared with those who did (OR, 23.2 [95% CI: 10.2, 53.1] vs OR, 8.0 [95% CI: 5.0, 12.6]; interactive P = .03). Conclusion Providing DXA screening to a high-risk group identified with AI-enabled chest radiographs can effectively diagnose more patients with osteoporosis. Clinical trial registration no. NCT05721157 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Smith and Rothenberg in this issue.

Towards the diagnosis of osteoporosis - contributions from coincidental diagnostic imaging findings in chiropractors' practice.

BACKGROUND: Osteoporosis is significantly associated with fractures and burdens the health of especially older people. Osteoporotic fractures cause pain, disability, and increased mortality. Early diagnosis of osteoporosis allows earlier initiation of treatment, thereby reducing the risk of osteoporotic fractures. Chiropractors encounter potential osteoporotic patients daily, and perform radiological evaluation of these and other patients, including evaluation of X-rays done for other purposes than osteoporosis. Therefore, chiropractors may identify vertebral fractures, vertebral deformity or osteopenia not otherwise suspected or recorded. METHODS: This study examines procedures available to the chiropractor to describe conventional X-rays with the focus of osteoporosis related findings. We review the indications for radiological examination in chiropractic practice, and in the realm of osteoporosis we describe radiological methods available for examination of conventional radiographs, and the necessity of inter-disciplinary communication. RESULTS: National guidelines are available regarding referral for X-rays in chiropractic practice. Standardized protocols ensure image acquisition of the highest quality in the chiropractors' radiological department. Conventional X-ray examination is not indicated on clinical suspicion of osteoporosis alone, as bone mineral density testing is the diagnostic test. Radiological assessment of all available X-rays of patients above the age of 50 years should include evaluation of the bone quality, and hip and vertebral fracture assessment. The Singh index, Genant Semi-Quantitative tool (GSQ), and Algorithm-Based Qualitative method (ABQ) should be used consistently during interpretation. Referral for additional imaging and evaluation should be prompt and systematic when needed. CONCLUSIONS: This article presents an overview of evidence-based radiological procedures for the purpose of promoting early diagnosis of osteoporosis. We present recommendations to the clinicians where we propose an opportunistic evaluation of X-rays, done for any reason, which include systematic evaluation of bone quality, presence of hip and vertebral fractures, and vertebral deformation of all patients above the age of 50 years. Detailed referral to healthcare professionals for further diagnostic evaluation is performed when needed. Consistent, high-quality radiological procedures in chiropractic practices could feasibly contribute to the timely diagnosis of osteoporosis, ultimately minimizing the impact of osteoporosis-related complications on patients' health.

Relationship between paraspinal muscle properties and bone mineral density based on QCT in patients with lumbar disc herniation.

OBJECTIVE: Increasing research suggests that paraspinal muscle fat infiltration may be a potential biological marker for the assessment of osteoporosis. Our aim was to investigate the relationship between lumbar paraspinal muscle properties on MRI and volumetric bone mineral density (vBMD) based on QCT in patients with lumbar disc herniation (LDH). METHODS: A total of 383 patients (aged 24-76 years, 193 females) with clinically and radiologically diagnosed LDH were enrolled in this retrospective study. The muscle cross-sectional area (CSA) and the proton density fat fraction (PDFF) were measured for the multifidus (MF), erector spinae (ES) and psoas major (PS) at the central level of L3/4, L4/5 and L5/S1 on lumbar MRI. QCT was used to measure the vBMD of two vertebral bodies at L1 and L2 levels. Patients were divided into three groups based on their vBMD values: normal bone density group (> 120 mg/cm3), osteopenia group (80 to 120 mg/cm3) and osteoporosis group (< 80 mg/cm3). The differences in paraspinal muscle properties among three vBMD groups were tested by one-way ANOVA with post hoc analysis. The relationships between paraspinal muscle properties and vBMD were analyzed using Pearson correlation coefficients. Furthermore, the association between vBMD and paraspinal muscle properties was further evaluated using multiple linear regression analysis, with age and sex also included as predictors. RESULTS: Among the 383 LDH patients, 191 had normal bone density, 129 had osteopenia and 63 had osteoporosis. In LDH patients, compared to normal and osteopenia group, paraspinal muscle PDFF was significantly greater in osteoporosis group, while paraspinal muscle CSA was lower (p < 0.001). After adjusting for age and sex, it was found that MF PDFF and PS CSA were found to be independent factors influencing vBMD (p < 0.05). CONCLUSION: In patients with LDH, paraspinal muscle properties measured by IDEAL-IQ sequence and lumbar MR scan were found to be related to vBMD. There was a correlation between the degree of paraspinal muscle PDFF and decreasing vBMD, as well as a decrease paraspinal muscle CSA with decreasing vBMD. These findings suggest that clinical management should consider offering tailored treatment options for patients with LDH based on these associations.

Relationship Between Prepatellar Fat Thickness and Bone Mineral Density.

OBJECTIVE: To evaluate the relationship between bone mineral density (BMD) by measuring the prepatellar fat thickness with knee radiography and to gain a measurement method that has not been done before in the literature. STUDY DESIGN: Cross-sectional descriptive study. Place and Duration of the Study: Department of Physical Medicine and Rehabilitation, Training and Research Hospital, Sanliurfa, Turkiye, between January and June 2020. METHODOLOGY: Patients' age, body mass index (BMI) data, prepatellar fat thickness (mm), L1-L4 total, bone mineral density femoral neck, femur trochanter major, and femur total T scores were recorded. The relationships between these three groups (normal, osteopenia, osteoporosis) and between prepatellar fat tissue measurement were evaluated. One-way analysis of variance (ANOVA) and Post Hoc Tukey tests were used in the analysis. RESULTS:  A statistically significant difference was found in terms of trochanter major T score measurements (X2 = 20.435; p <0.001) and BMI (X2 = 66.535; p <0.001) measurements of prepatellar fat thickness measurement. A statistically significant difference was found between the three groups in terms of prepatellar fat thickness measurement, L1-4 T-score, femoral neck, and femur total values (p <0.001). CONCLUSION:  Prepatellar fat thickness in postmenopausal Turkish women was positively correlated with BMD; BMD increases as the prepatellar fat thickness increases. This explains that perapatellar fat thickness creates a mechanical load on the bones and causes an increase in BMD. KEY WORDS: Osteoporosis, Fat thickness, Bone mineral density.

The Suitable Population for Opportunistic Low Bone Mineral Density Screening Using Computed Tomography.

Objective: To explore the suitable population of CT value for predicting low bone mineral density (low-BMD). Methods: A total of 1268 patients who underwent chest CT examination and DXA within one-month period retrospectively analyzed. The CT attenuation values of trabecular bone were measured in mid-sagittal plane from thoracic vertebra 7 (T7). Receiver operating characteristic (ROC) curves were used to evaluate the ability to diagnose low-BMD. Results: The AUC for diagnosing low BMD was larger in women than in men (0.894 vs 0.744, p < 0.05). The AUC increased gradually with the increase of age but decreased gradually with the increase in height and weight (p < 0.05). In females, when specificity was adjusted to approximately 90%, a threshold of 140.25 HU has a sensitivity of 69.3%, which is higher than the sensitivity of 36.5% in males for distinguishing low-BMD from normal. At the age of 70 or more, when specificity was adjusted to approximately 90%, a threshold of 126.31 HU has a sensitivity of 76.1%, which was higher than that of other age groups. Conclusion: For patients who had completed chest CTs, the CT values were more effective in predicting low-BMD in female, elderly, lower height, and lower weight patients.

Opportunistic prediction of osteoporosis in patients with degenerative lumbar diseases: a simplified T12 vertebral bone quality approach.

BACKGROUND: Osteoporosis is one of the risk factors for screw loosening after lumbar fusion. However, the probability of preoperative osteoporosis screening in patients with lumbar degenerative disease is low. Therefore, the aim of this study was to investigate whether a simplified vertebral bone quality (VBQ) score based on T12 T1-MRI could opportunistically predict osteoporosis in patients with degenerative lumbar spine diseases. METHODS: We retrospectively analyzed cases treated for lumbar degenerative diseases at a single institution between August 2021 and June 2022. The patients were divided into three groups by the lowest T-score: osteoporosis group, osteopenia group, and normal bone mineral density (BMD) group. The signal intensity based on the T12 vertebral body divided by the signal intensity of the cerebrospinal fluid was calculated to obtain the simplified VBQ score, as well as the CT-based T12HU value and the traditional L1-4VBQ score. Various statistical analyses were used to compare VBQ, HU and DEXA, and the optimal T12VBQ threshold for predicting osteoporosis was obtained by plotting the receiver operating curve (ROC) analysis. RESULTS: Total of 166 patients were included in this study. There was a statistically significant difference in T12VBQ scores between the three groups (p < 0.001). Pearson correlation showed that there was a moderate correlation between T12VBQ and T-score (r=-0.406, p < 0.001). The AUC value of T12VBQ, which distinguishes between normal and low BMD, was 0.756, and the optimal diagnostic threshold was 2.94. The AUC value of T12VBQ, which distinguishes osteoporosis from non-osteoporosis, was 0.634, and the optimal diagnostic threshold was 3.18. CONCLUSION: T12VBQ can be used as an effective opportunistic screening method for osteoporosis in patients with lumbar degenerative diseases. It can be used as a supplement to the evaluation of DEXA and preoperative evaluation. TRIAL REGISTRATION: retrospectively registered number:1502-009-644; retrospectively registered number date:27 oct 2022.

The association of waist circumference with bone mineral density and risk of osteoporosis in US adult: National health and nutrition examination survey.

PURPOSE: Obesity and osteoporosis (OP) are receiving increasing attention. Waist circumference (WC) is an effective indicator for assessing central obesity. Currently, there is controversy regarding the relationship between WC and bone mineral density (BMD), as well as OP. Therefore, our study aims to utilize data from the National Health and Nutrition Examination Survey (NHANES) to evaluate the relationship between WC and BMD, as well as OP, in US adults. METHODS: This cross-sectional study included subjects aged ≥18 years from the NHANES 1999-2018. Multivariate linear regression models were performed to investigate the association between WC and BMD. Multivariate logistic regression models were employed to assess the relationship between WC and OP. Restricted cubic spline curves were used to assess potential nonlinear association between WC and BMD, OP. Subgroup analysis and sensitivity analysis were performed to assess the robustness of the results. RESULTS: Finally, 11,165 participants (non-OP, n = 10,465; OP, n = 700) were included in the final analysis. The results showed that WC was positively associated with total femur (TF), femoral neck (FN), and lumbar spine (LS) BMD, and might be a protective factor for OP, independent of traditional confounding factors. For each 1 cm increased in WC, TF BMD, FN BMD and LS BMD increased by 0.004 g/cm2, 0.003 g/cm2 and 0.003 g/cm2, respectively, and the risk of OP decreased by 3.1 %. Furthermore, there was a non-linear relationship between WC and BMD, OP. The association remained robust in sensitivity and subgroup analyses. CONCLUSION: In US adults, there is a positive association between WC and BMD, and WC may be a protective factor for the risk of OP. The association between WC and BMD as well as OP exhibits a non-linear relationship.

Guidelines for fracture risk assessment and management of osteoporosis in postmenopausal women and men above the age of 50 in Qatar.

We present comprehensive guidelines for osteoporosis management in Qatar. Formulated by the Qatar Osteoporosis Association, the guidelines recommend the age-dependent Qatar fracture risk assessment tool for screening, emphasizing risk-based treatment strategies and discouraging routine dual-energy X-ray scans. They offer a vital resource for physicians managing osteoporosis and fragility fractures nationwide. PURPOSE: Osteoporosis and related fragility fractures are a growing public health issue with an impact on individuals and the healthcare system. We aimed to present guidelines providing unified guidance to all healthcare professionals in Qatar regarding the management of osteoporosis. METHODS: The Qatar Osteoporosis Association formulated guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men above the age of 50. A panel of six local rheumatologists who are experts in the field of osteoporosis met together and conducted an extensive review of published articles and local and international guidelines to formulate guidance for the screening and management of postmenopausal women and men older than 50 years in Qatar. RESULTS: The guidelines emphasize the use of the age-dependent hybrid model of the Qatar fracture risk assessment tool for screening osteoporosis and risk categorization. The guidelines include screening, risk stratification, investigations, treatment, and monitoring of patients with osteoporosis. The use of a dual-energy X-ray absorptiometry scan without any risk factors is discouraged. Treatment options are recommended based on risk stratification. CONCLUSION: Guidance is provided to all physicians across the country who are involved in the care of patients with osteoporosis and fragility fractures.

Radiological manifestations and clinical findings of patients with oncologic and osteoporotic medication-related osteonecrosis of the jaw.

Medication-related osteonecrosis of the jaw (MRONJ) poses a challenging form of osteomyelitis in patients undergoing antiresorptive therapies in contrast to conventional osteomyelitis. This study aimed to compare the clinical and radiological features of MRONJ between patients receiving low-dose medications for osteoporosis and those receiving high-dose medications for oncologic purposes. The clinical, panoramic radiographic, and computed tomography data of 159 patients with MRONJ (osteoporotic group, n = 120; oncologic group, n = 39) who developed the condition after using antiresorptive medications for the management of osteoporosis or bone malignancy were analyzed. The osteoporotic group was older (75.8 vs. 60.4 years, p < 0.01) and had a longer duration of medication usage than the oncologic group (58.1 vs. 28.0 months, p < 0.01). Pus discharge and swelling were more common in the osteoporotic group (p < 0.05), whereas bone exposure was more frequent in the oncologic group (p < 0.01). The mandibular cortical index (MCI) in panoramic radiographs was higher in the osteoporotic group (p < 0.01). The mean sequestra size was larger in the oncologic group than in the osteoporotic group (15.3 vs. 10.6 mm, p < 0.05). The cured rate was significantly higher in the osteoporotic group (66.3% vs. 33.3%, p < 0.01). Oncologic MRONJ exhibited distinct clinical findings including rapid disease onset, fewer purulent signs, and lower cure rates than osteoporotic MRONJ. Radiological features such as sequestrum size on CT scan, and MCI values on panoramic radiographs, may aid in differentiating MRONJ in osteoporotic and oncologic patients.

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.

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.