Clinical Use of Quantitative Computed Tomography and Peripheral Quantitative Computed Tomography in the Management of Osteoporosis in Adults: The 2007 ISCD Official Positions

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older East Asian women should be lower than the value for Caucasians

For Caucasian women, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) cutpoint value for classifying osteoporosis is 80 mg/ml. At the age of approximate 78 years, US Caucasian women QCT LS BMD population mean is 80 mg/ml, while that of Chinese women and Japanese women is around 50 mg/ml. Correlation analyses show, for Chinese women and Japanese women, QCT LS BMD of 45 mg/ml corresponds to the dual-energy X-ray absorptiometry cutpoint value for classifying osteoporosis. For Chinese and Japanese women, if QCT LS BMD 80 mg/ml is used as the threshold to classify osteoporosis, then the specificity of classifying subjects with vertebral fragility fracture into the osteoporotic group is low, whereas threshold of 45 mg/ml approximately achieve a similar separation for women with and without vertebral fragility fracture as the reports for Caucasian women. Moreover, by using 80mg/ml as the cutpoint value, LS QCT leads to excessively high prevalence of osteoporosis for Chinese women, with the discordance between hip dual-energy X-ray absorptiometry and LS QCT measures far exceeding expectation. Considering the different bone properties and the much lower prevalence of fragility fractures in the East Asian women compared with Caucasians, we argue that the QCT cutpoint value for classifying osteoporosis among older East Asian women will be close to and no more than 50 mg/ml LS BMD. We suggest that it is also imperative the QCT osteoporosis classification criterion for East Asian male LS, and male and female hips be re-examined.

Skeletal muscle estimation: A review of techniques and their applications

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non-invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual-energy X-ray absorptiometry, and Brightness-mode ultrasound, and non-imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole-body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut-off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses.

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study

BACKGROUND

The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT).

OBJECTIVE

To construct a novel predicting model based on bone turn-over markers and CT to identify patients who were more inclined to suffer spine refracture.

METHODS

CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U-net model was adopted to automatically segment ROI. Three-dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121-3D model to model the cropped region and simultaneously build a T-NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models.

RESULTS

The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer-Lemeshow goodness-of-fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p-value < 0.05) compared to using clinical features independently or using only 3D_RoiOnly.

CONCLUSION

T_P1NT was an independent risk factor of refracture. Our 3D-FULL model showed better performance in predicting high-risk population of spine refracture than other models and junior doctors do. This model can be applicable to real-world translation due to its automatic segmentation and detection.

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older Chinese men can be the same as that of older Chinese women, both much lower than the value for Caucasians

For older Caucasian women and men, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) threshold for classifying osteoporosis is 80 mg/ml. It was recently proposed that, for older East Asian women, the QCT LS BMD value equivalent to the Caucasian women's threshold of 80 mg/mL is about 45∼50 mg/ml. For a data of 328 cases of Chinese men (age: 73.6 ± 4.4 years) who had QCT LS BMD and DXA LS BMD at the same time and with the DXA BMD value of ≤ 0.613 g/cm2 to classify osteoporosis, the corresponding QCT LS BMD threshold is 53 mg/ml. Osteoporotic-like vertebral fracture sum score (OLVFss) ≤ -2.5 has been proposed to diagnose osteoporosis. For 316 cases of Chinese men (age:73.7±4.5 years), OLVFss ≤ -2.5 defines an osteoporosis prevalence of 4.4%; to achieve this osteoporosis prevalence, the corresponding QCT LS BMD value is < 47.5 mg/ml. In the China Action on Spine and Hip Status study, a Genant grades 2/3 radiographic 'osteoporotic vertebral fracture' prevalence was 2.84% for Chinese men (total n = 1267, age: 62.77 ± 9.20 years); to achieve this osteoporosis prevalence, the corresponding BMD value was < 42.5 mg/ml. In a study of 357 Beijing older men, according to the clinical fragility fracture prevalence and femoral neck DXA T-score, the QCT LS BMD value to classify osteoporosis was between 39.45 mg/ml and 51.38 mg/ml. For older Chinese men (≥ 50 years), we recommend the cutpoint for the QCT LS BMD definition of osteoporosis to be 45∼50 mg/ml which is the same as the value for Chinese women.

Accuracy of volumetric bone mineral density measurement in weight bearing, cone beam computed tomography

BACKGROUND

Weight bearing computed tomography (WBCT) utilizes cone beam CT technology to provide assessments of lower limb joint structures while they are functionally loaded. Grey-scale values indicative of X-ray attenuation that are output from cone beam CT are challenging to calibrate, and their use for bone mineral density (BMD) measurement remains debatable. To determine whether WBCT can be reliably used for cortical and trabecular BMD assessment, we sought to establish the accuracy of BMD measurements at the knee using modern WBCT by comparing them to measurements from conventional CT.

METHODS

A hydroxyapatite phantom with three inserts of varying densities was used to systematically quantify signal uniformity and BMD accuracy across the acquisition volume. We evaluated BMD in vivo (n = 5, female) using synchronous and asynchronous calibration techniques in WBCT and CT. To account for variation in attenuation along the height (z-axis) of acquisition volumes, we tested a height-dependent calibration approach for both WBCT and CT images.

RESULTS

Phantom BMD measurement error in WBCT was as high as 15.3% and consistently larger than CT (up to 5.6%). Phantom BMD measures made under synchronous conditions in WBCT improved measurement accuracy by up to 3% but introduced more variability in measured BMD. We found strong correlations (R = 0.96) as well as wide limits of agreement (-324 mgHA/cm3 to 183 mgHA/cm3) from Bland-Altman analysis between WBCT and CT measures in vivo that were not improved by height-dependent calibration.

CONCLUSION

Whilst BMD accuracy from WBCT was found to be dependent on apparent density, accuracy was independent of the calibration technique (synchronous or asynchronous) and the location of the measurement site within the field of view. Overall, we found strong correlations between BMD measures from WBCT and CT and in vivo measures to be more accurate in trabecular bone regions. Importantly, WBCT can be used to distinguish between anatomically relevant differences in BMD, however future work is necessary to determine the repeatability and sensitivity of BMD measures in WBCT.

Changes in thoracic radio density after living donor liver transplantation

BACKGROUND

The outcomes after liver transplantation have greatly improved, which has resulted in greater focus on improving non-hepatic outcomes of liver transplantation. The present study aimed to evaluate thoracic spine radio density in children and adolescents after liver transplantation.

METHODS

A total of 116 patients who underwent living donor liver transplantation were retrospectively analyzed. The radio density at the eleventh thoracic vertebra was measured using computed tomography scan performed preoperatively then annually for 5 years postoperatively and subsequently every 2 or 3 years.

RESULTS

The mean thoracic radio density of male recipients of male grafts had the lowest values during the study. The radio density of patients receiving a graft from a female donor was higher than in recipients with grafts from males. Total mean radio density decreased for first 5 years postoperatively and then increased. Changes in radio density were equally distributed in both steroid withdrawal and no steroid withdrawal groups for 5 years, after which patients with steroid withdrawal had a greater increase. Changes in radio density were equally distributed in both the steroid withdrawal and no steroid withdrawal groups up to age 20, after which patients in the steroid withdrawal group had a greater increase.

CONCLUSIONS

Gender differences may affect the outcome of radio density changes after transplantation. Given the moderate association between thoracic radio density and bone mineral density in skeletally mature adults and further studies are needed to validate this relationship between thoracic radio density and bone mineral density changes in pediatric liver transplantation.

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.

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.

Predicting Osteoporosis and Osteopenia by Fusing Deep Transfer Learning Features and Classical Radiomics Features Based on Single-Source Dual-energy CT Imaging

RATIONALE AND OBJECTIVES

To develop and validate a predictive model for osteoporosis and osteopenia prediction by fusing deep transfer learning (DTL) features and classical radiomics features based on single-source dual-energy computed tomography (CT) virtual monochromatic imaging.

METHODS

A total of 606 lumbar vertebrae with dual-energy CT imaging and quantitative CT (QCT) evaluation were included in the retrospective study and randomly divided into the training (n = 424) and validation (n = 182) cohorts. Radiomics features and DTL features were extracted from 70-keV monochromatic CT images, followed by feature selection and model construction, radiomics and DTL features models were established. Then, we integrated the selected two types of features into a features fusion model. We developed a two-level classifier for the hierarchical pairwise classification of each vertebra. All the vertebrae were first classified into osteoporosis and non-osteoporosis groups, then non-osteoporosis group was classified into osteopenia and normal groups. QCT was used as reference. The predictive performance and clinical usefulness of three models were evaluated and compared.

RESULTS

The area under the curve (AUC) of the features fusion, radiomics and DTL models for the classification between osteoporosis and non-osteoporosis were 0.981, 0.999, 0.997 in the training cohort and 0.979, 0.943, 0.848 in the validation cohort. Furthermore, the AUCs of the previously mentioned models for the differentiation between osteopenia and normal were 0.994, 0.971, 0.996 in the training cohort and 0.990, 0.968, 0.908 in the validation cohort. The overall accuracy of the previously mentioned models for two-level classifications was 0.979, 0.955, 0.908 in the training cohort and 0.918, 0.885, 0.841 in the validation cohort. Decision curve analysis showed that all models had high clinical value.

CONCLUSION

The feature fusion model can be used for osteoporosis and osteopenia prediction with improved predictive ability over a radiomics model or a DTL model alone.

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults

BACKGROUND

Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosis and sarcopenia by identifying metabolic clusters simultaneously. We also investigated the prognostic value of metabolic phenotyping by CT model for long-term mortality.

METHODS

The derivation set (n = 516; 75% train set, 25% internal test set) was constructed using age- and sex-stratified random sampling from two community-based cohorts. Data from participants in the individual health assessment programme (n = 380) were used as the external test set 1. Semi-automatic quantification of body compositions at multiple levels of abdominal CT scans was performed to train a multi-layer perceptron (MLP)-based multi-label classification model. External test set 2 to test the prognostic value of the model output for mortality was built using data from individuals who underwent abdominal CT in a tertiary-level institution (n = 10 141).

RESULTS

The mean ages of the derivation and external sets were 62.8 and 59.7 years, respectively, without difference in sex distribution (women 50%) or body mass index (BMI; 23.9 kg/m2). Skeletal muscle density (SMD) and bone density (BD) showed a more linear decrement across age than skeletal muscle area. Alternatively, an increase in visceral fat area (VFA) was observed in both men and women. Hierarchical clustering based on multi-level CT body composition parameters revealed three distinctive phenotype clusters: normal, MS and osteosarcopenia clusters. The L3 CT-parameter-based model, with or without clinical variables (age, sex and BMI), outperformed clinical model predictions of all outcomes (area under the receiver operating characteristic curve: MS, 0.76 vs. 0.55; osteoporosis, 0.90 vs. 0.79; sarcopenia, 0.85 vs. 0.81 in external test set 1; P < 0.05 for all). VFA contributed the most to the MS predictions, whereas SMD, BD and subcutaneous fat area were features of high importance for detecting osteoporosis and sarcopenia. In external test set 2 (mean age 63.5 years, women 79%; median follow-up 4.9 years), a total of 907 individuals (8.9%) died during follow-up. Among model-predicted metabolic phenotypes, sarcopenia alone (adjusted hazard ratio [aHR] 1.55), MS + sarcopenia (aHR 1.65), osteoporosis + sarcopenia (aHR 1.83) and all three combined (aHR 1.87) remained robust predictors of mortality after adjustment for age, sex and comorbidities.

CONCLUSIONS

A CT body composition-based MLP model detected MS, osteoporosis and sarcopenia simultaneously in community-dwelling and hospitalized adults. Metabolic phenotypes predicted by the CT MLP model were associated with long-term mortality, independent of covariates.

Reliability, costs, and radiation dose of dual-energy X-ray absorptiometry in diagnosis of radiologic sarcopenia in surgically menopausal women

OBJECTIVE

The aim of this study was to evaluate and compare reliability, costs, and radiation dose of dual-energy X-ray absorptiometry (DXA) to MRI and CT in measuring muscle mass for the diagnosis of sarcopenia.

METHODS

Thirty-four consecutive DXA scans performed in surgically menopausal women from November 2019 until March 2020 were analyzed by two observers. Observers analyzed muscle mass of the lower limbs in every scan twice. Reliability was assessed by calculating inter- and intra-observer variability. Reliability from CT and MRI as well as radiation dose from CT and DXA were collected from literature. Costs for each type of scan were calculated according to the guidelines for economic evaluation of the Dutch National Health Care Institute.

RESULTS

The 34 participants had a median age of 58 years (IQR 53-65) and a median body mass index of 24.6 (IQR 21.7-29.7). Inter-observer variability had an intraclass correlation coefficient (ICC) of 0.997 (95% CI 0.994-0.998) with a relative variability of 0.037 ± 0.022%. Regarding intra-observer variability, observer 1 had an ICC of 0.998 (95% CI 0.996-0.999) with a relative variability of 0.019 ± 0.016% and observer 2 had an ICC of 0.997 (95% CI 0.993-0.998) with a relative variability of 0.016 ± 0.011%. DXA costs were €62, CT €77, and MRI €195. The estimated radiation dose of CT was 2.5-3.0 mSv, for DXA this was 2-4 µSv.

CONCLUSIONS

DXA has lower costs and a lower radiation dose, with low inter- and intra-observer variability, compared to CT and MRI for assessing lower limb muscle mass.

TRIAL REGISTRATION

Netherlands Trial Register; NL8068.

CRITICAL RELEVANCE STATEMENT

DXA is a good alternative for CT and MRI in assessing lower limb muscle mass, with lower costs and lower radiation dose, while inter-observer and intra-observer variability are low.

KEY POINTS

• Screening for sarcopenia should be optimized as the population ages. • DXA outperformed CT and MRI in the measured metrics. • DXA validity should be further evaluated as an alternative to CT and MRI for sarcopenia evaluation.

To Evaluate the Value of Vertebral Body Cortical Thickness in Predicting Osteoporosis by Opportunistic CT

BACKGROUND

In vertebrae, the amount of cortical bone has been estimated at 30-60%, but 45-75% of axial load on a vertebral body is borne by cortical bone (1).

RATIONALE AND OBJECTIVES

The purpose of this study is to investigate the accuracy, sensitivity, specificity, positive predictive value and negative predictive value of vertebral body cortical thickness in predicting osteoporosis (OP) by analyzing the relationship between vertebral body cortical thickness and bone mineral density (BMD) in different age and gender groups. The optimal diagnostic cut-off value of vertebral body cortical thickness in predicting OP was analyzed.

MATERIALS AND METHODS

The data of 150 patients (50-89 years old) who underwent chest or abdominal Quantitative computed tomography (QCT) scan (obtained in one scan) in our hospital from July 2021 to July 2022 were retrospectively analyzed. The average volume bone mineral density (vBMD) of L1-L2 vertebral bodies was obtained and grouped according to BMD, age, and gender. According to BMD, the patients were divided into three groups: osteoporosis, osteopenia and normal. According to age, the patients were divided into three groups: 50-59 years, 60-69 years and ≥70 years. The axial images of T11, T12 and L1 were reconstructed with 1.25 mm slice thickness by AW4.7 workstation provided by General Electric Co (GE) Company. The images were imported into the computed tomography (CT) Spine Bone Quantification System software for spine analysis, and the vertebral body cortical thickness values were obtained. CT Spine Bone Quantification System is a software for quantitative analysis and separation of cortical bone and cancellous bone.

RESULTS

A total of 150 patients were enrolled in this study, including 49 patients in the osteoporosis group, 51 patients in the osteopenia group, and 50 patients in the normal group. The cortical thickness values of T11, T12 and L1 were positively correlated with BMD, and the correlation coefficient was 0.750 at T11. According to the receiver operating characteristic (ROC) curve analysis of T11, T12, L1 cortical thickness value and BMD, OP was diagnosed when T11 < 2.75 mm, T12 < 3.06 mm, and L1 < 2.67 mm. The sensitivity was 83.67%, 87.76%, 75.51%, respectively. The specificity was 79.21%, 71.29% and 90.10%, respectively, and the difference was statistically significant.

CONCLUSION

Vertebral body cortical thickness is correlated with BMD and age. According to the cut-off value of different vertebral bodies, OP can be predicted when T11 < 2.75 mm or T12 < 3.06 mm or L1 < 2.67 mm.

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

PURPOSE

To investigate the difference in vertebral morphology and bone mineral density (BMD) between grade 1 VFs and non-fractured participants in the Chinese population to shed light on the clinical significance of grade 1 VFs from various perspectives.

METHODS

This retrospective cohort study included patients who received a chest low-dose computed tomography (LDCT) scan for health examination and visited the First Affiliated Hospital of Zhengzhou University, Henan, China, from October 2019 to August 2022. Data were analyzed from March 2023 to July 2023. The main outcome of this study was the difference in morphological parameters and BMD between grade 1 VFs and non-fractured participants. The prevalence of grade 1 VFs in China populations was calculated. The difference in BMD of three fracture types in the Grade 1 group was also evaluated.

RESULTS

A total of 3652 participants (1799 males, 54.85 ± 9.02 years, range, 40-92 years; 1853 females, 56.00 ± 9.08 years, range, 40-93 years) were included. The prevalence of grade 2 and 3 increase with age. The prevalence of grade 1 VFs gradually increases ≤ 50y to 60-69y group, but there is a decrease in the ≥ 70 years male group (6.6%) and a rise in the female group (25.5%). There was no significant statistical difference observed in vertebral shape indices (VSI) and BMD between the Grade 1 group and the no-fractured group aged < 50 years old except the wedge index in male. The biconcavity index did not differ between the non-fractured group and the Grade 1 group in men aged 50-59 years, whereas a significant statistical difference was observed in women. Additionally, the results of BMD were consistent with these findings. For the 40-59 years age group, there were significant differences between the compression deformity group and the other groups.

CONCLUSIONS

The grade 1 group had higher VSI and lower BMD than the non-fractured group, suggesting an association between the Grade 1 group and osteoporosis in individuals aged over 50 for women and over 60 for men. Different fracture types have significant variations in BMD among middle-aged people. The prevalence of grade 1 VFs exhibits an age-related increase in both genders, with opposite trends observed between older males and females. We suggested VSI can aid physicians in the diagnosis of grade 1 VFs.

Magnetic resonance imaging based finite element modelling of the proximal femur: a short-term in vivo precision study

Proximal femoral fractures are a serious life-threatening injury with high morbidity and mortality. Magnetic resonance (MR) imaging has potential to non-invasively assess proximal femoral bone strength in vivo through usage of finite element (FE) modelling (a technique referred to as MR-FE). To precisely assess bone strength, knowledge of measurement error associated with different MR-FE outcomes is needed. The objective of this study was to characterize the short-term in vivo precision errors of MR-FE outcomes (e.g., stress, strain, failure loads) of the proximal femur for fall and stance loading configurations using 13 participants (5 males and 8 females; median age: 27 years, range: 21-68), each scanned 3 times. MR-FE models were generated, and mean von Mises stress and strain as well as principal stress and strain were calculated for 3 regions of interest. Similarly, we calculated the failure loads to cause 5% of contiguous elements to fail according to the von Mises yield, Brittle Coulomb-Mohr, normal principal, and Hoffman stress and strain criteria. Precision (root-mean squared coefficient of variation) of the MR-FE outcomes ranged from 3.3% to 11.8% for stress and strain-based mechanical outcomes, and 5.8% to 9.0% for failure loads. These results provide evidence that MR-FE outcomes are a promising non-invasive technique for monitoring femoral strength in vivo.

A Study on Intelligent Optical Bone Densitometry

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

The practicality of using bone impact microindentation in a population-based study of women: A Geelong-Osteoporosis Study

Impact microindentation (IMI) is a minimally invasive technique that allows the assessment of bone material strength index (BMSi) in vivo, by measuring the depth of a micron-sized, spherical tip into cortical bone that is then indexed to the depth of the tip into a reference material. In this study, we aimed to assess the practicality of its application in 99 women aged 42-84 yr from the Geelong Osteoporosis Study. Impact microindentation was performed in the mid-shaft of the right tibia using the OsteoProbe. Immediately following measurement, each participant was requested to rate on a Visual Analogue Scale [0-10] the level of discomfort anticipated and experienced, any initial reluctance towards the measurement and whether they were willing to repeat the measurement. Of 99 potential participants who attended this assessment phase, 55 underwent IMI measurement. Reasons for non-measurement in 44 women were existing skin conditions (n = 8, 18.2 %) and excessive soft tissue around mid-tibial region (n = 32, 72.2 %). An additional four (9.1 %) participants did not provide any reasons for declining. For 55 participants who had underwent IMI, the expectation for pain when briefed about the procedure was low (2.28 ± 2.39), as was pain experienced during the measurement (0.72 ± 1.58). Participants were not reluctant to undergo the measurement (0.83 ± 1.67), and all indicated a willingness to repeat the measurement. Results of this study showed that the IMI technique is well tolerated and accepted by women participating in the Geelong Osteoporosis Study, suggesting that the technique shows promise in a research or clinical setting.

Quantitative 31P magnetic resonance imaging on pathologic rat bones by ZTE at 7T

BACKGROUND

Osteoporosis is characterized by low bone mineral density (BMD), which predisposes individuals to frequent fragility fractures. Quantitative BMD measurements can potentially help distinguish bone pathologies and allow clinicians to provide disease-relieving therapies. Our group has developed non-invasive and non-ionizing magnetic resonance imaging (MRI) techniques to measure bone mineral density quantitatively. Dual-energy X-ray Absorptiometry (DXA) is a clinically approved non-invasive modality to diagnose osteoporosis but has associated disadvantages and limitations.

PURPOSE

Evaluate the clinical feasibility of phosphorus (31P) MRI as a non-invasive and non-ionizing medical diagnostic tool to compute bone mineral density to help differentiate between different metabolic bone diseases.

MATERIALS AND METHODS

Fifteen ex-vivo rat bones in three groups [control, ovariectomized (osteoporosis), and vitamin-D deficient (osteomalacia - hypo-mineralized) were scanned to compute BMD. A double-tuned (1H/31P) transmit-receive single RF coil was custom-designed and in-house-built with a better filling factor and strong radiofrequency (B1) field to acquire solid-state 31P MR images from rat femurs with an optimum signal-to-noise ratio (SNR). Micro-computed tomography (μCT) and gold-standard gravimetric analyses were performed to compare and validate MRI-derived bone mineral densities.

RESULTS

Three-dimensional 31P MR images of rat bones were obtained with a zero-echo-time (ZTE) sequence with 468 μm spatial resolution and 12-17 SNR on a Bruker 7 T Biospec having multinuclear capability. BMD was measured quantitatively on cortical and trabecular bones with a known standard reference. A strong positive correlation (R = 0.99) and a slope close to 1 in phantom measurements indicate that the densities measured by 31P ZTE MRI are close to the physical densities in computing quantitative BMD. The 31P NMR properties (resonance linewidth of 4 kHz and T1 of 67 s) of ex-vivo rat bones were measured, and 31P ZTE imaging parameters were optimized. The BMD results obtained from MRI are in good agreement with μCT and gravimetry results.

CONCLUSION

Quantitative measurements of BMD on ex-vivo rat femurs were successfully conducted on a 7 T preclinical scanner. This study suggests that quantitative measurements of BMD are feasible on humans in clinical MRI with suitable hardware, RF coils, and pulse sequences with optimized parameters within an acceptable scan time since human femurs are approximately ten times larger than rat femurs. As MRI provides quantitative in-vivo data, various systemic musculoskeletal conditions can be diagnosed potentially in humans.

Potential endpoints for assessment of bone health in persons with neurofibromatosis type 1

Neurofibromatosis type 1 is a genetic syndrome characterized by a wide variety of tumor and non-tumor manifestations. Bone-related issues, such as scoliosis, tibial dysplasia, and low bone mineral density, are a significant source of morbidity for this population with limited treatment options. Some of the challenges to developing such treatments include the lack of consensus regarding the optimal methods to assess bone health in neurofibromatosis type 1 and limited data regarding the natural history of these manifestations. In this review, the Functional Committee of the Response Evaluation in Neurofibromatosis and Schwannomatosis International Collaboration: (1) presents the available techniques for measuring overall bone health and metabolism in persons with neurofibromatosis type 1, (2) reviews data for use of each of these measures in the neurofibromatosis type 1 population, and (3) describes the strengths and limitations for each method as they might be used in clinical trials targeting neurofibromatosis type 1 bone manifestations. The Response Evaluation in Neurofibromatosis and Schwannomatosis International Collaboration supports the development of a prospective, longitudinal natural history study focusing on the bone-related manifestations and relevant biomarkers of neurofibromatosis type 1. In addition, we suggest that the neurofibromatosis type 1 research community consider adding the less burdensome measurements of bone health as exploratory endpoints in ongoing or planned clinical trials for other neurofibromatosis type 1 manifestations to expand knowledge in the field.

Renal safety of zoledronic acid in patients with osteoporosis: a retrospective study

INTRODUCTION

This study aimed to investigate the renal safety of Zoledronic Acid (ZOL) in patients with osteoporosis (OP).

METHODS

A total of 1379 patients (baseline estimated glomerular filtration rate, eGFR ≥ 60 mL/min/1.73 m2) with primary OP who received ZOL from January 2008 to October 2020 at our hospital were retrospectively analyzed. Baseline and the changes in renal function within 1 year following infusions were collected, the incidence of renal impairment (eGFR < 60 mL/min/1.73 m2 or a > 25% reduction in the eGFR from baseline) was noted and the risk factors were analyzed. Furthermore, the changes in renal function between a 3-year consecutive infusion and a single infusion of ZOL were compared.

RESULTS

Renal impairment occurred in 8.05% of patients, who with a significantly higher age, Charlson Comorbidity Index (CCI), smoking history, combination of hypertension or diabetes mellitus and worse renal function indicators (all P < 0.05). Binary logistic regression analysis showed that higher CCI (≥5) or smoking history or the baseline eGFR <90 mL/min/1.73 m2 were the risk factors for renal impairment (all P < 0.05). Patients of 3-year continuous infusion group had a significantly greater drop in the eGFR levels than the single infusion group after 1 year of infusion(s) (P < 0.05).

CONCLUSION

Attention should be given to possible potential renal impairment following ZOL infusion in clinical practice for the management of OP, particularly in patients with higher CCI (≥5) or smoking history or the baseline eGFR <90 mL/min/1.73 m2. Continuous infusion of ZOL exerts a significant impact on renal function when compared to single infusion and intensive monitoring of renal function is necessary.

Use of noninvasive imaging to identify causes of skeletal fragility in adults with diabetes: a review

Diabetes, a disease marked by consistent high blood glucose levels, is associated with various complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease. Notably, skeletal fragility has emerged as a significant complication in both type 1 (T1D) and type 2 (T2D) diabetic patients. This review examines noninvasive imaging studies that evaluate skeletal outcomes in adults with T1D and T2D, emphasizing distinct skeletal phenotypes linked with each condition and pinpointing gaps in understanding bone health in diabetes. Although traditional DXA-BMD does not fully capture the increased fracture risk in diabetes, recent techniques such as quantitative computed tomography, peripheral quantitative computed tomography, high-resolution quantitative computed tomography, and MRI provide insights into 3D bone density, microstructure, and strength. Notably, existing studies present heterogeneous results possibly due to variations in design, outcome measures, and potential misclassification between T1D and T2D. Thus, the true nature of diabetic skeletal fragility is yet to be fully understood. As T1D and T2D are diverse conditions with heterogeneous subtypes, future research should delve deeper into skeletal fragility by diabetic phenotypes and focus on longitudinal studies in larger, diverse cohorts to elucidate the complex influence of T1D and T2D on bone health and fracture outcomes.

Mouse models of accelerated aging in musculoskeletal research for assessing frailty, sarcopenia, and osteoporosis - A review

Musculoskeletal aging encompasses the decline in bone and muscle function, leading to conditions such as frailty, osteoporosis, and sarcopenia. Unraveling the underlying molecular mechanisms and developing effective treatments are crucial for improving the quality of life for those affected. In this context, accelerated aging models offer valuable insights into these conditions by displaying the hallmarks of human aging. Herein, this review focuses on relevant mouse models of musculoskeletal aging with particular emphasis on frailty, osteoporosis, and sarcopenia. Among the discussed models, PolgA mice in particular exhibit hallmarks of musculoskeletal aging, presenting early-onset frailty, as well as reduced bone and muscle mass that closely resemble human musculoskeletal aging. Ultimately, findings from these models hold promise for advancing interventions targeted at age-related musculoskeletal disorders, effectively addressing the challenges posed by musculoskeletal aging and associated conditions in humans.

Bone Mineral Density Derived from Cardiac CT Scans: Using Contrast Enhanced Scans for Opportunistic Screening

PURPOSE

Osteoporosis is under-diagnosed and often co-exists with other diseases. Very low bone mineral density (BMD) indicates risk of osteoporosis and opportunistic screening for low BMD in CT-scans has been suggested. In a non-contrast enhanced thoracic CT scan, the scan-field-of-view includes vertebrae enabling BMD estimation. However, many CT scans are obtained by administration of contrast material. If the impact of contrast enhancement on BMD measurements could be quantified, considerably more patients are eligible for screening.

METHODS

This study investigated the impact of intravenous contrast on thoracic BMD measurements in cardiac CT scans pre- and post-contrast, including different contrast trigger levels of 130 and 180 Hounsfield units (HU). BMD was measured using quantitative CT with asynchronous calibration.

RESULTS

In 195 participants undergoing cardiac CT (mean age 57±9 years, 37 % females) contrast increased mean thoracic BMD from 116±33 mg/cm3 (non-enhanced CT) to 130±38 mg/cm3 (contrast-enhanced CT) (p<0.001). Using clinical cut-off values for very low (<80 mg/cm3) and low BMD (<120 mg/cm3) showed that 24 % (47/195 participants) were misclassified when BMD was measured on contrast-enhanced CT-scans. Of the misclassified patients, 6 % (12/195 participants) were categorized as having low BMD despite having very low BMD on the non-enhanced images. Contrast-CT using a higher contrast trigger level showed a significant increase in BMD compared to the lower trigger level (119±32 vs. 135±40 mg/cm3, p<0.01).

CONCLUSION

For patients undergoing cardiac CT, using contrast-enhanced images to assess BMD entails substantial overestimation. Contrast protocol trigger levels also affect BMD measurements. Adjusting for these factors is needed before contrast-enhanced images can be used clinically.

MINI ABSTRACT

Osteoporosis is under-diagnosed. Contrast-enhanced CT made to examine other diseases might be utilized simultaneously for bone mineral density (BMD) screening. These scans, however, likely entails overestimation of BMD due to the effect of contrast. Adjusting for this effect is needed before contrast-enhanced images can be implemented clinically for BMD screening.

A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening

This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested the models on data from different hospitals and equipment. Results showed high accuracy and strong correlation with QCT results, showing promise for expanding osteoporosis screening and reducing unnecessary radiation and costs.

PURPOSE

To explore the feasibility of using deep learning to establish a model for osteoporosis classification and bone density value prediction based on opportunistic CT scans and to verify its generalization and diagnostic ability using an independent test set.

METHODS

A total of 1219 cases of opportunistic CT scans were included in this study, with QCT results as the reference standard. The training set: test set: independent test set ratio was 703: 176: 340, and the independent test set data of 340 cases were from 3 different hospitals and 4 different CT scanners. The VB-Net structure automatic segmentation model was used to segment the trabecular bone, and DenseNet was used to establish a three-classification model and bone density value prediction regression model. The performance parameters of the models were calculated and evaluated.

RESULTS

The ROC curves showed that the mean AUCs of the three-category classification model for categorizing cases into "normal," "osteopenia," and "osteoporosis" for the training set, test set, and independent test set were 0.999, 0.970, and 0.933, respectively. The F1 score, accuracy, precision, recall, precision, and specificity of the test set were 0.903, 0.909, 0.899, 0.908, and 0.956, respectively, and those of the independent test set were 0.798, 0.815, 0.792, 0.81, and 0.899, respectively. The MAEs of the bone density prediction regression model in the training set, test set, and independent test set were 3.15, 6.303, and 10.257, respectively, and the RMSEs were 4.127, 8.561, and 13.507, respectively. The R-squared values were 0.991, 0.962, and 0.878, respectively. The Pearson correlation coefficients were 0.996, 0.981, and 0.94, respectively, and the p values were all < 0.001. The predicted values and bone density values were highly positively correlated, and there was a significant linear relationship.

CONCLUSION

Using deep learning neural networks to process opportunistic CT scan images of the body can accurately predict bone density values and perform bone density three-classification diagnosis, which can reduce the radiation risk, economic consumption, and time consumption brought by specialized bone density measurement, expand the scope of osteoporosis screening, and have broad application prospects.

Traumatic rib fracture patterns associated with bone mineral density statuses derived from CT images

Background

The impact of decreased bone mineral density (BMD) on traumatic rib fractures remains unknown. We combined computed tomography (CT) and artificial intelligence (AI) to measure BMD and explore its impact on traumatic rib fractures and their patterns.

Methods

The retrospective cohort comprised patients who visited our hospital from 2017-2018; the prospective cohort (control group) was consecutively recruited from the same hospital from February-June 2023. All patients had blunt chest trauma and underwent CT. Volumetric BMD of L1 vertebra was measured by using an AI software. Analyses were done by using BMD categorized as osteoporosis (<80 mg/cm3), osteopenia (80-120 mg/cm3), or normal (>120 mg/cm3). Pearson's χ2, Fisher's exact, or Kruskal-Wallis tests and Bonferroni correction were used for comparisons. Negative binomial, and logistic regression analyses were used to assess the associations and impacts of BMD status. Sensitivity analyses were also performed.

Findings

The retrospective cohort included 2,076 eligible patients, of whom 954 (46%) had normal BMD, 806 (38.8%) had osteopenia, and 316 (15.2%) had osteoporosis. After sex- and age-adjustment, osteoporosis was significantly associated with higher rib fracture rates, and a higher likelihood of fractures in ribs 4-7. Furthermore, both the osteopenia and osteoporosis groups demonstrated a significantly higher number of fractured ribs and fracture sites on ribs, with a higher likelihood of fractures in ribs 1-3, as well as flail chest. The prospective cohort included 205 eligible patients, of whom 92 (44.9%) had normal BMD, 74 (36.1%) had osteopenia, and 39 (19.0%) had osteoporosis. The findings observed within this cohort were in concurrence with those in the retrospective cohort.

Interpretation

Traumatic rib fractures are associated with decreased BMD. CT-AI can help to identify individuals who have decreased BMD and a greater rib fracture rate, along with their fracture patterns.

Quantifying Bone Strength Deficits in Young Adults Born Extremely Preterm or Extremely Low Birth Weight

The long-term bone health of young adults born extremely preterm (EP; <28 weeks' gestation) or extremely low birth weight (ELBW; <1000 g birth weight) in the post-surfactant era (since the early 1990s) is unclear. This study investigated their bone structure and estimated bone strength using peripheral quantitative computed tomography (pQCT)-based finite element modeling (pQCT-FEM). Results using this technique have been associated with bone fragility in several clinical settings. Participants comprised 161 EP/ELBW survivors (46.0% male) and 122 contemporaneous term-born (44.3% male), normal birth weight controls born in Victoria, Australia, during 1991-1992. At age 25 years, participants underwent pQCT at 4% and 66% of tibia and radius length, which was analyzed using pQCT-FEM. Groups were compared using linear regression and adjusted for height and weight. An interaction term between group and sex was added to assess group differences between sexes. Parameters measured included compressive stiffness (kcomp ), torsional stiffness (ktorsion ), and bending stiffness (kbend ). EP/ELBW survivors were shorter than the controls, but their weights were similar. Several unadjusted tibial pQCT-FEM parameters were lower in the EP/ELBW group. Height- and weight-adjusted ktorsion at 66% tibia remained lower in EP/ELBW (mean difference [95% confidence interval] -180 [-352, -8] Nm/deg). The evidence for group differences in ktorsion and kbend at 66% tibia was stronger among males than females (pinteractions  <0.05). There was little evidence for group differences in adjusted radial models. Lower height- and weight-adjusted pQCT-FEM measures in EP/ELBW compared with controls suggest a clinically relevant increase in predicted long-term fracture risk in EP/ELBW survivors, particularly males. Future pQCT-FEM studies should utilize the tibial pQCT images because of the greater variability in the radius possibly related to lower measurement precision. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography

Osteoporosis is a prevalent bone disease that causes fractures in fragile bones, leading to a decline in daily living activities. Dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) are highly accurate for diagnosing osteoporosis; however, these modalities require special equipment and scan protocols. To frequently monitor bone health, low-cost, low-dose, and ubiquitously available diagnostic methods are highly anticipated. In this study, we aim to perform bone mineral density (BMD) estimation from a plain X-ray image for opportunistic screening, which is potentially useful for early diagnosis. Existing methods have used multi-stage approaches consisting of extraction of the region of interest and simple regression to estimate BMD, which require a large amount of training data. Therefore, we propose an efficient method that learns decomposition into projections of bone-segmented QCT for BMD estimation under limited datasets. The proposed method achieved high accuracy in BMD estimation, where Pearson correlation coefficients of 0.880 and 0.920 were observed for DXA-measured BMD and QCT-measured BMD estimation tasks, respectively, and the root mean square of the coefficient of variation values were 3.27 to 3.79% for four measurements with different poses. Furthermore, we conducted extensive validation experiments, including multi-pose, uncalibrated-CT, and compression experiments toward actual application in routine clinical practice.

A meta-analysis of the value of MRI-based VBQ scores for evaluating osteoporosis

Objective

Osteoporosis is the most common skeletal disease in humans. Early onset of osteoporosis is usually asymptomatic, so early diagnosis is critical. The purpose of this study was to analyze the value of MRI-based VBQ scores for evaluating osteoporosis.

Methods

We searched PubMed, Embase, the Cochrane Library databases, Web of Science, and some Chinese electronic databases for published articles and the ClinicalTrials.gov site for completed but unpublished studies on evaluating the value of MRI-based VBQ scores for evaluating osteoporosis. We calculated the summarized sensitivity, specificity, the ROC curve (AUC) values and their 95% confidence intervals (CIs) using MetaDiSc 1.4 software and STATA.

Results

Our study included 8 studies involving 999 patients of which 660 patients were diagnosed with osteopenia/osteoporosis, and 339 patients were identified as having normal BMD. The pooled sensitivity was 0.809 (95% CI, 0.777-0.838, I 2  = 78.8%), the pooled specificity was 0.640 (95% CI, 0.587-0.691, I 2  = 85.9%), and the pooled AUC was 0.8375.

Conclusion

MRI-based VBQ scores provided high sensitivity and moderate specificity in detecting osteoporosis. Opportunistic use of VBQ scores could be considered, e.g. before lumbar spine surgery.

Prospero registration number

CRD42022377024.

Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography

Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis. By summarizing the relevant studies, we aimed to assess the effectiveness, constraints, and potential impact of AI-based osteoporosis classification (severity) via CT. A systematic search of electronic databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 39 articles were retrieved from the databases, and the key findings were compiled and summarized, including the regions analyzed, the type of CT imaging, and their efficacy in predicting BMD compared with conventional DXA studies. Important considerations and limitations are also discussed. The overall reported accuracy, sensitivity, and specificity of AI in classifying osteoporosis using CT images ranged from 61.8% to 99.4%, 41.0% to 100.0%, and 31.0% to 100.0% respectively, with areas under the curve (AUCs) ranging from 0.582 to 0.994. While additional research is necessary to validate the clinical efficacy and reproducibility of these AI tools before incorporating them into routine clinical practice, these studies demonstrate the promising potential of using CT to opportunistically predict and classify osteoporosis without the need for DEXA.

A genome-wide genomic score added to standard recommended stratification tools does not improve the identification of patients with very low bone mineral density

The role of integrating genomic scores (GSs) needs to be assessed. Adding a GS to recommended stratification tools does not improve the prediction of very low bone mineral density. However, we noticed that the GS performed equally or above individual risk factors in discrimination.

PURPOSE

We aimed to investigate whether adding a genomic score (GS) to recommended stratification tools improves the discrimination of participants with very low bone mineral density (BMD).

METHODS

BMD was measured in three thoracic vertebrae using CT. All participants provided information on standard osteoporosis risk factors. GSs and FRAX scores were calculated. Participants were grouped according to mean BMD into very low (<80 mg/cm3), low (80-120 mg/cm3), and normal (>120 mg/cm3) and according to the Bone Health and Osteoporosis Foundation recommendations for BMD testing into an "indication for BMD testing" and "no indication for BMD testing" group. Different models were assessed using the area under the receiver operating characteristics curves (AUC) and reclassification analyses.

RESULTS

In the total cohort (n=1421), the AUC for the GS was 0.57 (95% CI 0.52-0.61) corresponding to AUCs for osteoporosis risk factors. In participants without indication for BMD testing, the AUC was 0.60 (95% CI 0.52-0.69) above or equal to AUCs for osteoporosis risk factors. Adding the GS to a clinical risk factor (CRF) model resulted in AUCs not statistically significant from the CRF model. Using probability cutoff values of 6, 12, and 24%, we found no improved reclassification or risk discrimination using the CRF-GS model compared to the CRF model.

CONCLUSION

Our results suggest adding a GS to a CRF model does not improve prediction. However, we noticed that the GS performed equally or above individual risk factors in discrimination. Clinical risk factors combined showed superior discrimination to individual risk factors and the GS, underlining the value of combined CRFs in routine clinics as a stratification tool.

The correlation between osteoporotic vertebrae fracture risk and bone mineral density measured by quantitative computed tomography and dual energy X-ray absorptiometry: a systematic review and meta-analysis

This paper presents a comparison of quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA) in osteoporosis with vertebral fracture and osteoporosis without fracture. It has been proved that the volumetric bone mineral density (vBMD) measured by QCT exhibits a stronger correlation with fracture risk than areal bone mineral density (aBMD) measured by DXA.

PURPOSE

This study aims to systematically evaluate the ability of QCT and DXA to distinguish between osteoporosis with vertebral fracture and osteoporosis without fracture according to vBMD and aBMD.

METHODS

We conducted a primary literature search of the online databases up to 3 July, 2022, in both English and Chinese publications, combining synonyms for "QCT", "DXA" and "osteoporosis". The Newcastle-Ottawa scale (NOS) was employed to evaluate the quality of the selected articles. vBMD obtained through QCT and aBMD obtained through DXA were extracted, and were analyzed by Review Manager 5.4 and RStudio.

RESULTS

Six studies with 610 individuals aged 45 to 90, of which 179 had vertebral fractures, were included in the final analysis. The weighted mean difference (WMD) between osteoporosis with vertebral fracture and osteoporosis without fracture for vBMD was - 27.08 (95% CI  - 31.24 to  - 22.92), while for aBMD was - 0.05 (95% CI - 0.08 to - 0.03).

CONCLUSIONS

Both vBMD detected by QCT and aBMD detected by DXA could discriminate fracture status in the spine, and vBMD performed a stronger correlation with fracture risk.

TRIAL REGISTRATION

PROSPERO 2022 CRD42022349185.

Opportunistic Screening With CT: Comparison of Phantomless BMD Calibration Methods

Opportunistic screening is a new promising technique to identify individuals at high risk for osteoporotic fracture using computed tomography (CT) scans originally acquired for an clinical purpose unrelated to osteoporosis. In these CT scans, a calibration phantom traditionally required to convert measured CT values to bone mineral density (BMD) is missing. As an alternative, phantomless calibration has been developed. This study aimed to review the principles of four existing phantomless calibration methods and to compare their performance against the gold standard of simultaneous calibration (ΔBMD). All methods were applied to a dataset of 350 females scanned with a highly standardized CT protocol (DS1) and to a second dataset of 114 patients (38 female) from clinical routine covering a large range of CT acquisition and reconstruction parameters (DS2). Three of the phantomless calibration methods must be precalibrated with a reference dataset containing a calibration phantom. Sixty scans from DS1 and 57 from DS2 were randomly selected for this precalibration. For each phantomless calibration method first the best combination of internal reference materials (IMs) was selected. These were either air and blood or subcutaneous adipose tissue, blood, and cortical bone. In addition, for phantomless calibration a fifth method based on average calibration parameters derived from the reference dataset was applied. For DS1, ΔBMD results (mean ± standard deviation) for the phantomless calibration methods requiring a precalibration ranged from 0.1 ± 2.7 mg/cm3 to 2.4 ± 3.5 mg/cm3 with similar means but significantly higher standard deviations for DS2. Performance of the phantomless calibration method, which does not require a precalibration was worse (ΔBMD DS1: 12.6 ± 13.2 mg/cm3 , DS2: 0.5 ± 8.8 mg/cm3 ). In conclusion, phantomless BMD calibration performs well if precalibrated with a reference dataset. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Feasibility analysis of low-dose CT with asynchronous quantitative computed tomography to assess vBMD

BACKGROUND

To explore the feasibility of low-dose computed tomography (LDCT) with asynchronous quantitative computed tomography (asynchronous QCT) for assessing the volumetric bone mineral density (vBMD).

METHODS

416 women patients, categorized into 4 groups, were included and underwent chest CT examinations combined with asynchronous QCT, and CT scanning dose protocols (LDCT or CDCT) were self-determined by the participants. Radiation dose estimations were retrieved from patient protocols, including volume CT dose index (CTDIvol) and dose-length-product (DLP), and then calculated effective dose (ED). Delimiting ED by 1.0 mSv, chest CT examinations were categorized into 2 groups, LDCT group and CDCT group. vBMD of T12-L2 was obtained by transferring the LDCT and CDCT images to the QCT workstation, without extra radiation.

RESULTS

There was no difference of vBMD among 4 age groups in LDCT group (P = 0.965), and no difference in CDCT group (P = 0.988). In LDCT group and CDCT group, vBMD was not correlated to mAs, CTDIvol and DLP (P > 0.05), respectively. Between LDCT group and CDCT group, there was no difference of vBMD (P ≥ 0.480), while differences of mAs, CTDIvol and DLP.

CONCLUSION

There was no difference of vBMD between LDCT group and CDCT group and vBMD was not correlated to mAs. While screening for diseases such as lung cancer and mediastinal lesions, LDCT combined with asynchronous QCT can be also used to assess vBMD simultaneously with no extra imaging equipment, patient visit time, radiation dose and no additional economic cost.

Screening for osteoporosis based on IQon spectral CT virtual low monoenergetic images: Comparison with conventional 120 kVp images

Objectives

To explore the differences between low kiloelectron volt (keV) virtual monoenergetic images (VMIs) using IQon spectral CT and conventional CT (120 kVp) in the diagnosis of osteoporosis.

Methods

This retrospective study included 317 patients who underwent IQon spectral CT and dual-energy X-ray absorptiometry (DXA) examination. Commercial deep learning-based software was used for the fully automated extraction of the CT values of the first to fourth lumbar vertebrae (L1-L4) from two different low-keV levels (including 40/70 keV) VMIs and conventional 120 kVp images. The DXA examination results served as the standard of reference (normal [T-score ≥ -1], osteopenia [-2.5 < T-score < -1], and osteoporosis [T-score < -2.5]). Osteoporosis diagnosis models were constructed using machine learning classifiers (logistic regression, support vector machine, random forest, XGBoost, and multilayer perceptron) based on the average CT values of L1-L4. The area under the receiver operating characteristic curve (AUC) and DeLong test were performed to compare differences in the performance of the osteoporosis diagnosis model between virtual low-keV VMIs and standard 120 kVp images.

Results

Random forest-based prediction model obtained good overall performance among all classifiers, and macro/micro average AUC values of 0.820/840, 0.834/853, and 0.831/852 were obtained based on 40/70 keV and 120 kVp images, respectively. The model presented no significant difference between low-keV VMIs and standard 120 kVp images for the diagnosis of osteoporosis (p > 0.05).

Conclusions

The performance of the osteoporosis diagnosis model using IQon spectral CT simulating the low tube voltage scanning condition (less than 120 kVp) was also satisfactory. Bone density screening evaluation can be performed with a combination of low-dose lung scanning CT, greatly reducing the radiation dose without affecting the diagnosis.

MRI-based vertebral bone quality score for predicting cage subsidence by assessing bone mineral density following transforaminal lumbar interbody fusion: a retrospective analysis

PURPOSE

This is the first study to evaluate the predictive value of the vertebral bone quality (VBQ) score on cage subsidence after transforaminal lumbar interbody fusion (TLIF) in a Chinese population using the spinal quantitative computed tomography (QCT) as the clinical standard. Meanwhile, the accuracy of the MRI-based VBQ score in bone mineral density (BMD) measurement was verified.

METHODS

We performed a retrospective study of patients who underwent single-level TLIF from 2015 to 2020 with at least 1 year of follow-up. Cage subsidence was measured using postoperative radiographic images based on cage protrusion through the endplates more than 2 mm. The VBQ score was measured on T1-weighted MRI. The results were subjected to statistical analysis.

RESULTS

A total of 283 patients (61.1% of female) were included in the study. The subsidence rate was with 14.1% (n = 40), and the average cage subsidence was 2.3 mm. There was a significant difference in age, sex, VBQ score and spinal QCT between the subsidence group and the no-subsidence group. The multivariable analysis demonstrated that only an increased VBQ score (OR = 2.690, 95% CI 1.312-5.515, p = 0.007) and decreased L1/2 QCT-vBMD (OR = 0.955, 95% CI 0.933-0.977, p < 0.001) were associated with an increased rate of cage subsidence. The VBQ score was found to be moderately correlated with the spinal QCT (r = -0.426, p < 0.001). The VBQ score was shown to significantly predict cage subsidence, with an accuracy of 82.5%.

CONCLUSION

Our findings indicate that the MRI-based VBQ score is a significant predictor of cage subsidence and could be used to assess BMD.

Dual-Energy CT-based Opportunistic Volumetric Bone Mineral Density Assessment of the Distal Radius

Background In patients with distal radius fractures (DRFs), low bone mineral density (BMD) is associated with bone substitute use during surgery and bone nonunion, but BMD information is not regularly available. Purpose To evaluate the feasibility of dual-energy CT (DECT)-based BMD assessment from routine examinations in the distal radius and the relationship between the obtained BMD values, the occurrence of DRFs, bone nonunion, and use of surgical bone substitute. Materials and Methods Scans in patients who underwent routine dual-source DECT in the distal radius between January 2016 and December 2021 were retrospectively acquired. Phantomless BMD assessment was performed using the delineated trabecular bone of a nonfractured segment of the distal radius and both DECT image series. CT images and health records were examined to determine fracture severity, surgical management, and the occurrence of bone nonunion. Associations of BMD with the occurrence of DRFs, bone nonunion, and bone substitute use at surgical treatment were examined with generalized additive models and receiver operating characteristic analysis. Results This study included 263 patients (median age, 52 years; IQR, 36-64 years; 132 female patients), of whom 192 were diagnosed with fractures. Mean volumetric BMD was lower in patients who sustained a DRF (93.9 mg/cm3 vs 135.4 mg/cm3; P < .001), required bone substitutes (79.6 mg/cm3 vs 95.5 mg/cm3; P < .001), and developed bone nonunion (71.1 mg/cm3 vs 96.5 mg/cm3; P < .001). Receiver operating characteristic curve analysis identified these patients with an area under the curve of 0.71-0.91 (P < .001). Lower BMD increased the risk to sustain DRFs, develop bone nonunion, and receive bone substitutes at surgery (P < .001). Conclusion DECT-based BMD assessment at routine examinations is feasible and could help predict surgical bone substitute use and the occurrence of bone nonunion in patients with DRFs. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Carrino in this issue.

Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans

Objectives

To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models.

Methods

This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC).

Results

420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7).

Conclusions

VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data.

Positions of The International Society for Clinical Densitometry and Their Etiology: A Scoping Review

The International Society for Clinical Densitometry convenes a Position Development Conference (PDC) every 2 to 3 years to make recommendations for guidelines and standards in the field of musculoskeletal measurement and assessment. The recommendations pertain to clinically relevant issues regarding the acquisition, quality control, interpretation, and reporting of measures of various aspects of musculoskeletal health. These PDCs have been meeting since 2002 and have generated 214 Adult, 26 FRAX, 41 pediatric, and 9 general nomenclature consideration positions, for a total of 290 positions. All positions are justified by detailed documents that present the background and rationale for each position. However, the linkage to these publications is not maintained by the ISCD or any other publication such that physicians cannot easily understand the etiology of the positions. Further, the wording of many positions has changed over the years after being reviewed by subsequent PDCs. This scoping review captures the references, changes, and timeline associated with each position through the 2019 PDC. It is meant to serve as a guide to clinicians and researchers for intelligent use and application of the positions.

Managing Early Onset Osteoporosis: The Impact of Premature Ovarian Insufficiency on Bone Health

Premature ovarian insufficiency is a reproductive endocrine disorder characterized by the cessation of ovarian function before the age of 40 years. Although the etiopathology of POI remains largely unknown, certain causative factors have been identified. Individuals affected by POI are at an increased risk of experiencing bone mineral density (BMD) loss. Hormonal replacement therapy (HRT) is recommended for patients with POI to mitigate the risk of decreased BMD, starting from the time of diagnosis until reaching the average age of natural menopause. Various studies have compared the dose-effect relationship of estradiol supplementation, as well as different HRT formulations on BMD. The impact of oral contraception on reduced BMD or the potential benefits of adding testosterone to estrogen replacement therapy are still subjects of ongoing discussion. This review provides an overview of the latest advancements in the diagnosis, evaluation, and treatment of POI as it relates to BMD loss.

Feasibility Study of 3D FACT and IVIM Sequences in the Evaluation of Female Osteoporosis

BACKGROUND

The aim of this study is to search for the predictive value of 3D fat analysis and calculation technique (FACT) and intravoxel incoherent motion (IVIM) parameters in identifying osteoporosis in women.

METHODS

We enrolled 48 female subjects who underwent 3.0 T MRI, including 3D FACT and IVIM sequences. Bone mineral density (BMD) values and Fracture Risk Assessment (FRAX) scores were obtained. Proton density fat fraction (PDFF) in the bone marrow and the real diffusion (D) value of intervertebral discs were measured on 3D FACT and IVIM images, respectively. Accuracy and bias were assessed by linear regression analysis and Bland-Altman plots. Intraclass correlation coefficients were used to assess the measurements' reproducibility. Spearman's rank correlation was applied to explore the correlation. MRI-based parameters were tested for significant differences among the three groups using ANOVA analyses. A receiver operating characteristic (ROC) analysis was performed.

RESULTS

The PDFF of the vertebral body showed a negative correlation with BMD (R = -0.393, p = 0.005) and a positive correlation with the FRAX score (R = 0.706, p < 0.001). The D value of intervertebral discs showed a positive correlation with BMD (R = 0.321, p = 0.024) and a negative correlation with the FRAX score (R = -0.334, p = 0.019). The area under the curve values from the ROC analysis showed that the 3D FACT and IVIM sequences could accurately differentiate between normal and osteoporosis (AUC = 0.88 using the PDFF; AUC = 0.77 using the D value). The PDFF value demonstrated a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 78.6%, 89.5%, 84.6%, and 85.0%, respectively, in its ability to predict osteoporosis. The D value had a sensitivity, specificity, PPV, and NPV of 63.16%, 92.9%, 65.0%, and 77.8%, respectively, for predicting osteoporosis.

CONCLUSIONS

The 3D FACT- and IVIM-measured PDFF and D values are promising biomarkers in the assessment of bone quality and fracture risk.

Craniocaudal toggling increases the risk of screw loosening in osteoporotic vertebrae

BACKGROUND AND OBJECTIVE

Screw loosening remains a prominent problem for osteoporotic patients undergoing pedicle screw fixation surgeries but its underlying mechanisms are not fully understood. This study sought to examine the interactive effect of craniocaudal or axial cyclic loading (toggling) and osteoporosis on screw fixation.

METHODS

QCT-based finite element models of normal (n = 7; vBMD = 156 ± 13 mg/cm³) and osteoporotic vertebrae (n = 7; vBMD = 72 ± 6 mg/cm³) were inserted with pedicle screws and loaded with or without craniocaudal toggling. Among them, a representative normal vertebra (age: 55; BMD: 140 mg/cm³) and an osteoporotic vertebra (age: 64; BMD: 79 mg/cm³) were also loaded with or without axial toggling. The individual and interactive effects of craniocaudal toggling and osteoporosis on screw fixation strength (the force when the pull-up displacement of the screw head reached 1 mm) and bone tissue failure (characterized by equivalent plastic strain) were examined by repeated measure ANOVA.

RESULTS

A significant interactive effect between craniocaudal toggling and osteoporosis on screw fixation strength was detected (p = 0.008). Specifically, craniocaudal toggling led to a marked decrease in the fixation strength (68%, p < 0.05) and stiffness (83%, p < 0.05) only in the osteoporotic vertebrae but had no effect on screw fixation strength and stiffness of the normal vertebrae (p > 0.05). Likewise, most of the bone tissues around the screw in the osteoporotic vertebrae yielded following craniocaudal toggling whereas this result was not seen in the normal vertebrae. The axial toggling had no significant effect on bone tissue failure as well as pedicle screw fixation in normal or osteoporotic vertebrae.

CONCLUSIONS

Craniocaudal toggling substantially reduces the screw fixation strength of the osteoporotic vertebrae by progressively increasing tissue failure around the screw, and therefore may contribute to the higher rates of screw loosening in osteoporotic compared to normal patients, whereas axial toggling is not a risk factor for pedicle screw loosening in normal or osteoporotic patients.

Biomechanical MRI detects reduced bone strength in subjects with vertebral fractures

Vertebral fracture is one of the most serious consequences of osteoporosis. Estimation of vertebral strength from magnetic resonance imaging (MRI) scans may provide a new approach for the prediction of vertebral fractures. To that end, we sought to establish a biomechanical MRI (BMRI) method to compute vertebral strength and test its ability to distinguish fracture from non-fracture subjects. This case-control study included 30 subjects without vertebral fractures and 15 subjects with vertebral fractures. All subjects underwent MRI with a mDIXON-Quant sequence and quantitative computed tomography (QCT), from which proton fat fraction-based bone marrow adipose tissue (BMAT) content and volumetric bone mineral density (vBMD) were measured, respectively. Nonlinear finite element analysis was applied to MRI and QCT scans of L2 vertebrae to compute vertebral strength (BMRI- and BCT-strength). The differences in BMAT content, vBMD, BMRI-strength and BCT-strength between the two groups were examined by t-tests. Receiver operating characteristic (ROC) analysis was performed to assess the ability of each measured parameter to distinguish fracture from non-fracture subjects. Results showed that the fracture group had 23 % lower BMRI-strength (P < .001) and 19 % higher BMAT content (P < .001) than the non-fracture group, whereas no significant difference in vBMD was detected between the two groups. A poor correlation was found between vBMD and BMRI-strength (R² = 0.33). Compared to vBMD and BMAT content, BMRI- and BCT-strength had the larger area under the curve (0.82 and 0.84, respectively) and provided better sensitivity and specificity in separating fracture from non-fracture subjects. In conclusion, BMRI is capable of detecting reduced bone strength in patients with vertebral fracture, and may serve as a new approach for risk assessment of vertebral fracture.

MRI-based vertebral bone quality score compared to quantitative computed tomography bone mineral density in patients undergoing cervical spinal surgery

PURPOSE

The vertebral bone quality (VBQ) score based on magnetic resonance imaging (MRI) was introduced as a bone quality marker in the lumbar spine. Prior studies showed that it could be utilized as a predictor of osteoporotic fracture or complications after instrumented spine surgery. The objective of this study was to evaluate the correlation between VBQ scores and bone mineral density (BMD) measured by quantitative computer tomography (QCT) in the cervical spine.

METHODS

Preoperative cervical CT and sagittal T1-weighted MRIs from patients undergoing ACDF were retrospectively reviewed and included. The VBQ score in each cervical level was calculated by dividing the signal intensity of the vertebral body by the signal intensity of the cerebrospinal fluid on midsagittal T1-weighted MRI images and correlated with QCT measurements of the C2-T1 vertebral bodies. A total of 102 patients (37.3% female) were included.

RESULTS

VBQ values of C2-T1 vertebrae strongly correlated with each other. C2 showed the highest VBQ value [Median (range) 2.33 (1.33, 4.23)] and T1 showed the lowest VBQ value [Median (range) 1.64 (0.81, 3.88)]. There was significant weak to moderate negative correlations between and VBQ Scores for all levels [C2: p < 0.001; C3: p < 0.001; C4: p < 0.001; C5: p < 0.004; C6: p < 0.001; C7: p < 0.025; T1: p < 0.001].

CONCLUSION

Our results indicate that cervical VBQ scores may be insufficient in the estimation of BMDs, which might limit their clinical application. Additional studies are recommended to determine the utility of VBQ and QCT BMD to evaluate their potential use as bone status markers.

Bone collagen quality in lumbar fusion patients: the association between volumetric bone mineral density and advanced glycation endproducts

PURPOSE

The sole determination of volumetric bone mineral density (vBMD) is insufficient to evaluate overall bone integrity. The accumulation of advanced glycation endproducts (AGEs) stiffens and embrittles collagen fibers. Despite the important role of AGEs in bone aging, the relationship between AGEs and vBMD is poorly understood. We hypothesized that an accumulation of AGEs, a marker of impaired bone quality, is related to decreased vBMD.

METHODS

Prospectively collected data of 127 patients undergoing lumbar fusion were analyzed. Quantitative computed tomography (QCT) measurements were performed at the lumbar spine. Intraoperative bone biopsies were obtained and analyzed with confocal fluorescence microscopy for fluorescent AGEs, both trabecular and cortical. Spearman's correlation coefficients were calculated to examine relationships between vBMD and fAGEs, stratified by sex. Multivariable linear regression analysis with adjustments for age, sex, body mass index (BMI), race, diabetes mellitus and HbA1c was used to investigate associations between vBMD and fAGEs.

RESULTS

One-hundred and twenty-seven patients (51.2% female, 61.2 years, BMI of 28.7 kg/m2) with 107 bone biopsies were included in the final analysis, excluding patients on anti-osteoporotic drug therapy. In the univariate analysis, cortical fAGEs increased with decreasing vBMD at (r = -0.301; p = 0.030), but only in men. In the multivariable analysis, trabecular fAGEs increased with decreasing vBMD after adjusting for age, sex, BMI, race, diabetes mellitus and HbA1c (β = 0.99;95%CI=(0.994,1.000); p = 0.04).

CONCLUSION

QCT-derived vBMD measurements were found to be inversely associated with trabecular fAGEs. Our results enhance the understanding of bone integrity by suggesting that spine surgery patients with decreased bone quantity may also have poorer bone quality.

Regional variations in the intra- and intervertebral trabecular microarchitecture of the osteoporotic axial skeleton

Trabecular structures in vertebral bodies are unequally distributed in the cervical, thoracic and lumbar spine, and also within individual vertebrae. Knowledge of the microstructure of these entities could influence our comprehension and treatment of osteoporotic fractures, and even surgical procedures. Appropriate investigations may clarify the pathomechanisms of various osteoporotic fractures (fish, wedge-shaped, and flat vertebrae). We obtained three cancellous bone cylinders from the centers and margins of cervical vertebra 3 to lumbar vertebra 5, and investigated these in regard of bone volume fraction, trabecular thickness, separation, trabecular number, trabecular bone pattern factor, connectivity density, and degree of anisotropy. Using a Jamshidi needle^®, we obtained samples from three quadrants (QI: right-sided edge, QII: central, QIII: left-sided edge) of 242 prepared vertebrae, and investigated these on a micro-CT device. In all, 726 bone samples were taken from eleven body donors. Bone volume fraction, trabecular thickness, and the degree of anisotropy were significantly lower in QII than in QI and QIII. Trabecular pattern factor, however, was significantly higher in QII than in QI and QIII. The results helped to explain fish vertebrae. Wedge fractures and flat vertebrae are most likely caused by the complex destruction of trabecular and cortical structures. The higher bone volume fraction in the cervical spine compared to the thoracic and lumbar spine accounts for the small number of fractures in the cervical spine. The marked trabecular pattern factor in the center of thoracic and lumbar vertebrae could be a reason for the surgeon to use different screw designs for individual vertebrae.

Quantitative CT screening improved lumbar BMD evaluation in older patients compared to dual-energy X-ray absorptiometry

BACKGROUND

Robust evidence on whether diagnostic discordance exists between lumbar osteoporosis detected by quantitative computed tomography (QCT) vs. dual-energy X-ray absorptiometry (DXA) is still lacking. In this study involving a relatively large prospective cohort of older men (aged > 60 years) and postmenopausal women, we assessed lumbar QCT-derived volumetric bone mineral density (vBMD) and DXA-derived area BMD and evaluated their predictive performance for prevalent vertebral fracture (VF).

METHODS

A total of 501 patients who underwent spinal surgery from September 2020 to September 2022 were enrolled. The criteria recommended by the American College of Radiology and the World Health Organization were used for lumbar osteoporosis diagnosis. The osteoporosis detection rates between QCT and DXA were compared. QCT-vBMD was plotted against the DXA T score, and the line of best fit was calculated based on linear regression. Multivariate logistic regression was used to analyze the associations between risk factors and VF. Receiver operating characteristic curve analysis was performed, and the corresponding area under the curve (AUC) was calculated.

RESULTS

QCT screening showed that 60.7% of patients had osteoporosis, whereas DXA screening showed that 50.7% of patients had osteoporosis. Diagnoses were concordant for 325 (64.9%) patients. In all, 205 patients suffered a VF of at least one anatomic level. Of these, 84.4% (173/205) were diagnosed with osteoporosis by QCT, while only 73.2% (150/205) were diagnosed by DXA. Multivariate logistic regression showed that osteoporosis detected by QCT exhibited a stronger relationship with VF than that detected by DXA (unadjusted OR, 6.81 vs. 5.04; adjusted OR, 3.44 vs. 2.66). For discrimination between patients with and without VF, QCT-vBMD (AUC = 0.802) showed better performance than DXA T score (AUC = 0.76).

CONCLUSION

In older patients undergoing spinal surgery, QCT-vBMD is more helpful than DXA in terms of osteoporosis detection rate and prediction of patients with prevalent VFs.

Assessment of bone density using the 1.5 T or 3.0 T MRI-based vertebral bone quality score in older patients undergoing spine surgery: Does field strength matter?

BACKGROUND CONTEXT

Recently published studies have revealed a correlation between MRI-based vertebral bone quality (VBQ) score and bone mineral density (BMD) measured using dual X-ray absorptiometry (DXA) or quantitative computed tomography (QCT). However, no studies have determined if differences in field strength (1.5 vs. 3.0 T) could affect the comparability of the VBQ score among different individuals.

PURPOSE

To compare the VBQ score obtained from 1.5 T and 3.0 T MRI (VBQ_1.5T versus VBQ_3.0T) in patients undergoing spine surgery and assess the predictive performance of VBQ for osteoporosis and osteoporotic vertebral fracture (VCF).

DESIGN

A nested case‒control study based on an ongoing prospective cohort study of patients undergoing spine surgery.

PATIENT SAMPLE

All older patients (men aged > 60 years and postmenopausal women) with available DXA, QCT and MR images within one month were included.

OUTCOME MEASURES

VBQ score, DXA T-score, and QCT derived vBMD.

METHODS

The osteoporotic classifications recommended by the World Health Organization and American College of Radiology were used to categorize the DXA T-score and QCT-derived BMD, respectively. For each patient, the VBQ score was calculated using T1-weighted MR images. Correlation analysis between VBQ and DXA/QCT was performed. Receiver operating characteristic (ROC) curve analysis, including determination of the area under the curve (AUC), was performed to assess the predictive performance of VBQ for osteoporosis.

RESULTS

A total of 452 patients (98 men aged > 60 years and 354 postmenopausal women) were included in the analysis. Across different BMD categories, the correlation coefficients between the VBQ score and BMD ranged from -0.211 to -0.511, and the VBQ_1.5T score and QCT BMD demonstrated the strongest correlation. The VBQ score was a significant classifier of osteoporosis detected by either DXA or QCT, with VBQ_1.5T showing the highest discriminative power for QCT-osteoporosis (AUC = 0.744, 95% CI = 0.685-0.803). In ROC analysis, the VBQ_1.5T threshold values ranged from 3.705 to 3.835 with a sensitivity between 48% and 55.6% and a specificity between 70.8% and 74.8%, while the VBQ_3.0T threshold values ranged from 2.59 to 2.605 with a sensitivity between 57.6% and 67.1% and a specificity between 67.8% and 69.7%.

CONCLUSIONS

VBQ_1.5T exhibited better discriminability between patients with and without osteoporosis than VBQ_3.0T. Considering the nonnegligible difference in osteoporosis diagnosis threshold values between the VBQ_1.5T and VBQ_3.0T scores, it is essential to clearly distinguish the magnetic field strength when assessing the VBQ score.

Reference Intervals for Bone Impact Microindentation in Healthy Adults: A Multi-Centre International Study

Impact microindentation (IMI) is a novel technique for assessing bone material strength index (BMSi) in vivo, by measuring the depth of a micron-sized, spherical tip into cortical bone that is then indexed to the depth of the tip into a reference material. The aim of this study was to define the reference intervals for men and women by evaluating healthy adults from the United States of America, Europe and Australia. Participants included community-based volunteers and participants drawn from clinical and population-based studies. BMSi was measured on the tibial diaphysis using an OsteoProbe in 479 healthy adults (197 male and 282 female, ages 25 to 98 years) across seven research centres, between 2011 and 2018. Associations between BMSi, age, sex and areal bone mineral density (BMD) were examined following an a posteriori method. Unitless BMSi values ranged from 48 to 101. The mean (± standard deviation) BMSi for men was 84.4 ± 6.9 and for women, 79.0 ± 9.1. Healthy reference intervals for BMSi were identified as 71.0 to 97.9 for men and 59.8 to 95.2 for women. This study provides healthy reference data that can be used to calculate T- and Z-scores for BMSi and assist in determining the utility of BMSi in fracture prediction. These data will be useful for positioning individuals within the population and for identifying those with BMSi at the extremes of the population.

Opportunistic measures of bone mineral density at multiple skeletal sites during whole-body CT in polytrauma patients

Whole-body CT in polytrauma patients revealed bone mineral density variations throughout the skeleton. Bone density was the highest in cranial bones and the lowest in proximal extremities and pelvis. Skeletal age-related changes were generally more pronounced than sex-related changes. Cranial bones did not follow the same aging pattern compared to other bones.

INTRODUCTION

Whole-body CT (WBCT) in polytrauma patients enables the detection of numerous incidental findings, such as estimates of bone mineral density (BMD) at multiple skeletal sites. This could help in better understanding of age- and sex-related changes in BMD through skeleton.

METHODS

Data were retrospectively retrieved from the WBCTs requested during a 2-year period. BMD, expressed in CT Hounsfield units (HU), was measured at frontal and occipital bone, four vertebrae (C4, Th7, L4, and S2), iliac bone, and proximal humerus and femur. Measurements were done on native and postcontrast scans. The population sample was age-, sex-, and visceral fat volume adjusted for analysis.

RESULTS

A total of 296 patients were included, with a median age of 51 years. BMD varied from the highest HU in cranial bones (629 HU) to the lowest HU in the pelvic bones (114 HU), P < 0.001. Sex differences were independent predictors of BMD in cranial bones and proximal humerus. The age-related decline in BMD was significant in all other bones, but the association with age differed among the measurement's sites. Visceral fat showed the strongest correlation with the lumbar spine and iliac wing, although multivariate analysis revealed it was not an independent predictor of bone density, such as age and sex.

CONCLUSIONS

BMD varies through skeleton, being the highest in the proximal axial skeleton. Age-related changes in BMD are significant and more pronounced than sex-related changes in almost all bones. Cranial bones do not follow the same pattern compared to other bones.