Vertebral Bone Mineral Density Measured by Quantitative Computed Tomography With and Without a Calibration Phantom: A Comparison Between 2 Different Software Solutions

Risk of fragility fracture is aggravated during bone regeneration processes in osteoporotic sheep

INTRODUCTION

Bone regeneration processes are associated with a systemic skeletal change in bone quality, increasing the risk of fragility fractures. This condition may be aggravated in osteoporotic patients due to their limited osteogenic capacity. This work evaluates the impairment of the bone quality in osteoporotic sheep during a bone regeneration process. It provides a deeper understanding about the complex multiscale dynamics of bone mineral density, microstructure and chemical composition across different bone tissues, locations and time points.

MATERIALS AND METHODS

Osteoporosis was induced in fifteen Merino sheep. A critical-size defect was then created in the sheep's right hind metatarsus and subsequently regenerated using distraction osteogenesis. The animals were randomly sacrificed during bone regeneration, either on days 40 or 100 after surgery. Computed tomography, micro-computed tomography and chemical composition analyses were conducted on different bone tissues (cortical, trabecular and woven) at several skeletal locations (the operated metatarsus, the contralateral one and the iliac crest) to assess the individual bone quality changes relative to the non-osteoporotic time point.

RESULTS

After osteoporosis induction, the trabecular tissue experienced a 6.4% reduction in the bone mineral density, while no significant changes were reported in cortical tissue quality. During bone regeneration, the operated bone increased significantly the woven ossification whilst the cortical mineral density decreased by 18.7%. Simultaneously, an early deterioration in the microstructure and chemical composition of the trabecular bone was observed in the iliac crest, persisting over time in non-operated trabecular regions.

CONCLUSIONS

Osteoporosis causes uneven degradation to trabecular tissue quality across different bone locations. Furthermore, the bone regeneration process via bone transport in osteoporotic subjects leads to a systemic skeletal disorder that further impairs the bone quality, surpassing the damage caused by osteoporosis alone. This impairment appears to be intensified by the pre-existing osteoporotic condition.

Computed tomography provides a "one-stop-shop" targeted analysis for coronary artery calcification and osteoporosis: a review

The global trend towards longer lifespans has led to an aging population and a rise in the prevalence of diseases that predominantly affect elderly people. Coronary artery calcification (CAC) and osteoporosis (OP) are common in elderly populations. CT scans provide a reliable method to assess and monitor the progression of these diseases. In this review, the relationship between OP and CAC in terms of pathophysiological mechanism, comorbidity risk factors and clinical manifestations is reviewed, with a focus on the advancements in CT imaging, clinical applications and the possibility for "one-stop-shop" for examination.

Developing Cut-off Values for Low and Very Low Bone Mineral Density at the Thoracic Spine Using Quantitative Computed Tomography

Osteoporosis is under-diagnosed while detectable by measuring bone mineral density (BMD) using quantitative computer tomography (QCT). Opportunistic screening for low BMD has previously been suggested using lumbar QCT. However, thoracic QCT also possesses this potential to develop upper and lower cut-off values for low thoracic BMD, corresponding to the current cut-offs for lumbar BMD. In participants referred with chest pain, lumbar and thoracic BMD were measured using non-contrast lumbar- and cardiac CT scans. Lumbar BMD cut-off values for very low (< 80 mg/cm3), low (80-120 mg/cm3), and normal BMD (> 120 mg/cm3) were used to assess the corresponding thoracic values. A linear regression enabled identification of new diagnostic thoracic BMD cut-off values. The 177 participants (mean age 61 [range 31-74] years, 51% women) had a lumbar BMD of 121.6 mg/cm3 (95% CI 115.9-127.3) and a thoracic BMD of 137.0 mg/cm3 (95% CI: 131.5-142.5), p < 0.001. Categorization of lumbar BMD revealed 14%, 35%, and 45% in each BMD category. When applied for the thoracic BMD measurements, 25% of participants were reclassified into a lower group. Linear regression predicted a relationship of Thoracic BMD = 0.85 * Lumbar BMD + 33.5, yielding adjusted thoracic cut-off values of < 102 and > 136 mg/cm3. Significant differences in BMD between lumbar and thoracic regions were found, but a linear relationship enabled the development of thoracic upper and lower cut-off values for low BMD in the thoracic spine. As Thoracic CT scans are frequent, these findings will strengthen the utilization of CT images for opportunistic detection of osteoporosis.

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.

Vertebral Fracture Risk Thresholds from Phantom-Less Quantitative Computed Tomography-Based Finite Element Modeling Correlate to Phantom-Based Outcomes

INTRODUCTION

Osteoporosis indicates weakened bones and heightened fracture susceptibility due to diminished bone quality. Dual-energy x-ray absorptiometry is unable to assess bone strength. Volumetric bone mineral density (vBMD) from quantitative computed tomography (QCT) has been used to establish guidelines as equivalent measurements for osteoporosis. QCT-based finite element analysis (FEA) has been implemented using calibration phantoms to establish bone strength thresholds based on the established vBMD. The primary aim was to validate vertebral failure load thresholds using a phantom-less approach with previously established thresholds, advancing a phantom-free approach for fracture risk prediction.

METHODOLOGY

A controlled cohort of 108 subjects (68 females) was used to validate sex-specific vertebral fracture load thresholds for normal, osteopenic, and osteoporotic subjects, obtained using a QCT/FEA-based phantom-less calibration approach and two material equations.

RESULTS

There were strong prediction correlations between the phantom-less and phantom-based methods (R2: 0.95 and 0.97 for males, and R2: 0.96 and 0.98 for females) based on the two equations. Bland Altman plots and paired t-tests showed no significant differences between methods. Predictions for bone strengths and thresholds using the phantom-less method matched those obtained using the phantom calibration and those previously established, with ≤4500 N (fragile) and ≥6000 N (normal) bone strength in females, and ≤6500 N (fragile) and ≥8500 N (normal) bone strength in males.

CONCLUSION

Phantom-less QCT-based FEA can allow for prospective and retrospective studies evaluating incidental vertebral fracture risk along the spine and their association with spine curvature and/or fracture etiology. The findings of this study further supported the application of phantom-less QCT-based FEA modeling to predict vertebral strength, aiding in identifying individuals prone to fractures. This reinforces the rationale for adopting this method as a comprehensive approach in predicting and managing fracture risk.

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning

OBJECTIVE

To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD) measurement and opportunistic low BMD (osteopenia and osteoporosis) screening using chest low-dose CT (LDCT) scans.

METHODS

A total of 1175 individuals were enrolled in this study, who underwent both chest LDCT and BMD examinations with quantitative computed tomography (QCT), by two different CT scanners (Siemens and GE). Two convolutional neural network (CNN) models were employed for vertebral body segmentation and labeling, respectively. A histogram technique was applied for vertebral BMD calculation using paraspinal muscle and surrounding fat as references. 195 cases (by Siemens scanner) as fitting cohort were used to build the calibration function. 698 cases as validation cohort I (VCI, by Siemens scanner) and 282 cases as validation cohort II (VCII, by GE scanner) were performed to evaluate the performance of the proposed method, with QCT as the standard for analysis.

RESULTS

The average BMDs from the proposed method were strongly correlated with QCT (in VCI: r = 0.896, in VCII: r = 0.956, p < 0.001). Bland-Altman analysis showed a small mean difference of 1.1 mg/cm3, and large interindividual differences as seen by wide 95% limits of agreement (-29.9 to +32.0 mg/cm3) in VCI. The proposed method measured BMDs were higher than QCT measured BMDs in VCII (mean difference = 15.3 mg/cm3, p < 0.001). Osteoporosis and low BMD were diagnosed by proposed method with AUCs of 0.876 and 0.903 in VCI, 0.731 and 0.794 in VCII, respectively. The AUCs of the proposed method were increased to over 0.920 in both VCI and VCII after adjusting the cut-off.

CONCLUSION

Without manual selection of the region of interest of body tissues, the proposed method based on deep learning and phantomless internal calibration has the potential for preliminary screening of patients with low BMD using chest LDCT scans. However, the agreement between the proposed method and QCT is insufficient to allow them to be used interchangeably in BMD measurement.

ADVANCES IN KNOWLEDGE

This study proposed an automated vertebral BMD measurement method based on deep learning and phantomless internal calibration with paraspinal muscle and fat as reference.

Performance of iCare quantitative computed tomography in bone mineral density assessment of the hip and vertebral bodies in European spine phantom

BACKGROUND

Osteoporosis is a systemic bone disease which can increase the risk of osteoporotic fractures. Dual-energy X-ray absorptiometry (DXA) is considered as the clinical standard for diagnosing osteoporosis by detecting the bone mineral density (BMD) in patients, but it has flaws in distinguishing between calcification and other degenerative diseases, thus leading to inaccurate BMD levels in subjects. Mindways quantitative computed tomography (Mindways QCT) is a classical QCT system. Similar to DXA, Mindways QCT can directly present the density of trabecular bone, vascular or tissue calcification; therefore, it is more accurate and sensitive than DXA and has been widely applied in clinic to evaluate osteoporosis. iCare QCT osteodensitometry was a new phantom-based QCT system, recently developed by iCare Inc. (China). It has been gradually applied in clinic by its superiority of taking 3-dimensional BMD of bone and converting BMD values to T value automatically. This study aimed at evaluating the osteoporosis detection rate of iCare QCT, compared with synchronous Mindways QCT (USA).

METHODS

In this study, 131 patients who underwent hip phantom-based CT scan were included. Bone mineral density (BMD) of the unified region of interests (ROI) defined at the European spine phantom (ESP, German QRM) including L1 (low), L2 (medium), and L3 (high) vertebral bodies was detected for QCT quality control and horizontal calibration. Every ESP scan were taken for 10 times, and the mean BMD values measured by iCare QCT and Mindways QCT were compared. Hip CT scan was conducted with ESP as calibration individually. T-scores gained from iCare QCT and Mindways QCT were analyzed with Pearson correlation test. The detection rates of osteoporosis were compared between iCare QCT and Mindways QCT. The unified region of interests (ROI) was delineated in the QCT software.

RESULTS

The results showed that there was no significant difference between iCare QCT and Mindways QCT in the evaluation of L1, L2, and L3 vertebrae bodies in ESP. A strong correlation between iCare QCT and Mindways QCT in the assessment of hip T-score was found. It was illustrated that iCare QCT had a higher detection rate of osteoporosis with the assessment of hip T-score than Mindways QCT did. In patients < 50 years subgroup, the detection rate of osteoporosis with iCare QCT and Mindways QCT was equal. In patients ≥ 50 years subgroup, the detection rate of osteoporosis with iCare QCT (35/92, 38.0%) was higher than that with Mindways QCT. In female subgroup, the detection rate of osteoporosis with iCare QCT was significantly higher than Mindways QCT. In male subgroup, the detection rate of osteoporosis with iCare QCT was also markedly higher than Mindways QCT. The detection rate of osteoporosis by iCare QCT was higher than Mindways QCT with hip bone assessment. Of course, the results of the present study remain to be further verified by multicenter studies in the future.

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.

Distribution of bone voids in the thoracolumbar spine in Chinese adults with and without osteoporosis: A cross-sectional multi-center study based on 464 vertebrae

Bone void is a novel intuitive morphological indicator to assess bone quality but its use in vertebrae has not been described. This cross-sectional and multi-center study aimed to investigate the distribution of bone voids in the thoracolumbar spine in Chinese adults based on quantitative computed tomography (QCT). A bone void was defined as a trabecular net region with extremely low bone mineral density (BMD) (<40 mg/cm³), detected by an algorithm based on phantom-less technology. A total of 464 vertebrae from 152 patients (51.8 ± 13.4 years old) were included. The vertebral trabecular bone was divided into eight sections based on the middle sagittal, coronal, and horizontal planes. Bone void of the whole vertebra and each section were compared between healthy, osteopenia, and osteoporosis groups and between spine levels. Receiver operator characteristic (ROC) curves were plotted and optimum cutoff points of void volume between the groups were obtained. The total void volumes of the whole vertebra were 124.3 ± 221.5 mm³, 1256.7 ± 928.7 mm^3, and 5624.6 ± 3217.7 mm³ in healthy, osteopenia, and osteoporosis groups, respectively. The detection rate of vertebrae with bone voids was higher and the normalized void volume was larger in the lumbar than in thoracic vertebrae. L3 presented the largest void (2165.0 ± 3396.0 mm³), while T12 had the smallest void (448.9 ± 699.4 mm³). The bone void was mainly located in the superior-posterior-right section (40.8 %). Additionally, bone void correlated positively with age and increased rapidly after 55 years. The most significant void volume increase was found in the inferior-anterior-right section whereas the least increase was found in the inferior-posterior-left section with aging. The cutoff points were 345.1 mm³ between healthy and osteopenia groups (sensitivity = 0.923, specificity = 0.932) and 1693.4 mm³ between osteopenia and osteoporosis groups (sensitivity = 1.000, specificity = 0.897). In conclusion, this study demonstrated the bone void distribution in vertebrae using clinical QCT data. The findings provide a new perspective for the description of bone quality and showed that bone void could guide clinical practice such as osteoporosis screening.

Sources of error in bone mineral density estimates from quantitative CT

Bone mineral density (BMD) estimates from quantitative computed tomography (QCT) have proven useful for opportunistic screening of osteoporosis, treatment monitoring, and bone strength measurement. These estimates are subject to bias and variance from a variety of sources related to the imaging equipment, methods applied in the estimation procedure, and the patients themselves. In this article, we review the literature to describe the sources and sizes of error in spine and hip BMD estimates from single-energy QCT that can result from factors related to the scanner, imaging techniques, imaging subject, calibration phantom, and calibration approach. We also describe the baseline variance that can be expected based on repeatability and reproducibility studies. Though reproducible BMD estimates may be achievable with QCT, a thorough understanding of the potential sources of error and their size relative to the diagnostic task is essential to their appropriate and meaningful interpretation.

Opportunistic CT screening predicts individuals at risk of major osteoporotic fracture

Millions of CT scans are performed annually and could be also used to opportunistically assess musculoskeletal health; however, it is unknown how well this secondary assessment relates to osteoporotic fracture. This study demonstrates that opportunistic CT screening is a promising tool to predict individuals with previous osteoporotic fracture.

INTRODUCTION

Opportunistic computed tomography (oCT) screening for osteoporosis and fracture risk determination complements current dual X-ray absorptiometry (DXA) diagnosis. This study determined major osteoporotic fracture prediction by oCT at the spine and hip from abdominal CT scans.

METHODS

Initial 1158 clinical abdominal CT scans were identified from administrative databases and were the basis to generate a cohort of 490 men and women with suitable abdominal CT scans. Participant CT scans met the following criteria: over 50 years of age, the scan had no image artifacts, and the field-of-view included the L4 vertebra and proximal femur. A total of 123 participants were identified as having previously suffered a fracture within 5 years of CT scan date. Fracture cause was identified from clinical data and used to create a low-energy fracture sub-cohort. At each skeletal site, bone mineral density (BMD) and finite element (FE)-estimated bone strength were determined. Logistic regression predicted fracture and receiver-operator characteristic curves analyzed prediction capabilities.

RESULTS

In participants with a fracture, low-energy fractures occurred in 88% of women and 79% of men. Fracture prediction by combining both BMD and FE-estimated bone strength was not statistically different than using either BMD or FE-estimated bone strength alone. Predicting low-energy fractures in women determined the greatest AUC of 0.710 by using both BMD and FE-estimated bone strength.

CONCLUSIONS

oCT screening using abdominal CT scans is effective at predicting individuals with previous fracture at major osteoporotic sites and offers a promising screening tool for skeletal health assessment.

Automated segmentation of an intensity calibration phantom in clinical CT images using a convolutional neural network

PURPOSE

In quantitative computed tomography (CT), manual selection of the intensity calibration phantom's region of interest is necessary for calculating density (mg/cm³) from the radiodensity values (Hounsfield units: HU). However, as this manual process requires effort and time, the purposes of this study were to develop a system that applies a convolutional neural network (CNN) to automatically segment intensity calibration phantom regions in CT images and to test the system in a large cohort to evaluate its robustness.

METHODS

This cross-sectional, retrospective study included 1040 cases (520 each from two institutions) in which an intensity calibration phantom (B-MAS200, Kyoto Kagaku, Kyoto, Japan) was used. A training dataset was created by manually segmenting the phantom regions for 40 cases (20 cases for each institution). The CNN model's segmentation accuracy was assessed with the Dice coefficient, and the average symmetric surface distance was assessed through fourfold cross-validation. Further, absolute difference of HU was compared between manually and automatically segmented regions. The system was tested on the remaining 1000 cases. For each institution, linear regression was applied to calculate the correlation coefficients between HU and phantom density.

RESULTS

The source code and the model used for phantom segmentation can be accessed at https://github.com/keisuke-uemura/CT-Intensity-Calibration-Phantom-Segmentation . The median Dice coefficient was 0.977, and the median average symmetric surface distance was 0.116 mm. The median absolute difference of the segmented regions between manual and automated segmentation was 0.114 HU. For the test cases, the median correlation coefficients were 0.9998 and 0.999 for the two institutions, with a minimum value of 0.9863.

CONCLUSION

The proposed CNN model successfully segmented the calibration phantom regions in CT images with excellent accuracy.

Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses

Osteoporosis affects an increasing number of people every year and patient specific finite element analysis of the femur has been proposed to identify patients that could benefit from preventative treatment. The aim of this study was to demonstrate, verify, and validate an objective process for selecting tissues for use as the basis of phantomless calibration to enable patient specific finite element analysis derived hip fracture risk prediction. Retrospective reanalysis of patient computed tomography (CT) scans has the potential to yield insights into more accurate prediction of osteoporotic fracture. Bone mineral density (BMD) specific calibration scans are not typically captured during routine clinical practice. Tissue-based BMD calibration can therefore empower the retrospective study of patient CT scans captured during routine clinical practice. Together the method for selecting tissues as the basis for phantomless calibration coupled with the post-processing steps for deriving a calibration equation using the selected tissues provide an estimation of quantitative equivalent density results derived using calibration phantoms. Patient tissues from a retrospective cohort of 211 patients were evaluated. The best phantomless calibration resulted in a femoral strength (FS) [N] bias of 0.069 ± 0.07% over FS derived from inline calibration and a BMD [kg/cm³] bias of 0.038 ± 0.037% over BMD derived from inline calibration. The phantomless calibration slope for the best method presented was within the range of patient specific calibration curves available for comparison and demonstrated a small bias of 0.028 ± 0.054 HU/(mg/cm³), assuming the Mindways Model 3 BMD inline calibration phantom as the gold standard. The presented method of estimating a calibration equation from tissues showed promise for CT-based femoral fracture analyses of retrospective cohorts without readily available calibration data.

Sex Differences in the Association Between Bone Mineral Density and Coronary Artery Disease in Patients Referred for Cardiac Computed Tomography

Atherosclerosis and osteoporosis are both common and preventable diseases. Evidence supports a link between coronary artery disease (CAD) and low bone mineral density (BMD). This study aimed to assess the association between thoracic spine BMD and CAD in men and women with symptoms suggestive of CAD. This cross-sectional study included 1487 (mean age 57 years (range 40-80), 47% men) patients referred for cardiac computed tomography (CT). Agatston coronary artery calcium score (CACS), CAD severity (no, mild, moderate, and severe), vessel involvement (no, 1-, 2-, and 3/left main disease), and invasive measurements were evaluated. BMD of three thoracic vertebrae was measured using quantitative CT. We used the American college of radiology cut-off values for lumbar spine BMD to categorize patients into very low (<80 mg/cm³), low (80-120 mg/cm³), or normal BMD (>120 mg/cm³). BMD as a continuous variable was included in the linear regression analyses to assess associations between CACS (CACS=0, CACS 1- 399, and CACS ≥ 400) and BMD, and CAD severity and BMD. Significant lower BMD was present with increasing CACS and stenosis degree unadjusted. Multivariate linear regression analyses in women revealed a significant correlation between BMD and CACS groups (β = -4.06, p<0.05), but no correlation between BMD and CAD severity (β = -1.59, p = 0.14). No association was found between BMD and CACS (β = -1.50, p = 0.36) and CAD severity (β = 0.07, p = 0.94) in men. BMD is significantly correlated to CACS after adjusting for confounders in women, but not in men, suggesting a possible sex difference in pathophysiology.

Thoracic Bone Mineral Density Derived from Cardiac CT Is Associated with Greater Fracture Rate

Background Osteoporosis is a prevalent, under-diagnosed, and treatable disease associated with increased fracture risk. Bone mineral density (BMD) derived from cardiac CT may be used to determine fracture rate. Purpose To assess the association between fracture rate and thoracic BMD derived from cardiac CT. Materials and Methods This prospective cohort study included consecutive participants referred for cardiac CT for evaluation of ischemic heart disease between September 2014 and March 2016. End of follow-up was June 30, 2018. In all participants, volumetric BMD of three thoracic vertebrae was measured by using quantitative CT software. The primary and secondary outcomes were any incident fracture and any incident osteoporosis-related fracture registered in the National Patient Registry, respectively. Hazard ratios were assessed by using BMD categorized as very low (<80 mg/cm³), low (80-120 mg/cm³), or normal (>120 mg/cm³). The study is registered at ClinicalTrials.gov (identifier: NCT02264717). Results In total, 1487 participants (mean age, 57 years ± 9; age range, 40-80 years; 52.5% women) were included, of whom 179 (12.0%) had very low BMD. During follow-up (median follow-up, 3.1 years; interquartile range, 2.7-3.4 years; range, 0.2-3.8 years), 80 of 1487 (5.3%) participants were diagnosed with an incident fracture and in 31 of 80 participants, the fracture was osteoporosis related. In unadjusted Cox regressions analyses, very low BMD was association with a greater rate of any fracture (hazard ratio, 2.6; 95% confidence interval [CI]: 1.4, 4.7; P = .002) and any osteoporosis-related fracture (hazard ratio, 8.1; 95% CI: 2.4, 26.7; P = .001) compared with normal BMD. After adjusting for age and sex, very low BMD remained associated with any fracture (hazard ratio, 2.1; 95% CI: 1.1, 4.2) and any osteoporosis-related fracture (hazard ratio, 4.0; 95% CI: 1.1, 14.6). Conclusion Routine cardiac CT can be used to help measure thoracic bone mineral density (BMD) to identify individuals who have low BMD and a greater fracture rate. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Bredella in this issue.

Feasibility of Opportunistic Screening for Low Thoracic Bone Mineral Density in Patients Referred for Routine Cardiac CT

Despite being a frequent and treatable disease, osteoporosis remains under-diagnosed worldwide. Our study aim was to characterize the bone mineral density (BMD) status in a group of patients with symptoms suggestive of coronary artery disease (CAD) with low/intermediate risk profile undergoing routine cardiac computed tomography (CT) to rule out CAD. This cross-sectional study used prospectively acquired data from a large consecutively included cohort. Participants were referred for cardiac CT based on symptoms of CAD. Quantitative CT (QCT) dedicated software was used to obtain BMD measurements in 3 vertebrae starting from the level of the left main coronary artery. We used the American College of Radiology cut-off values for lumbar spine QCT to categorize patients into very low (<80 mg/cm3), low (80-120 mg/cm3), or normal BMD (>120 mg/cm3). Analyses included 1487 patients. Mean age was 57 years (range 40-80), and 52% were women. The number of patients with very low BMD was 105 women (14%, 105/773) and 74 men (10%, 74/714). The majority of patients with very low BMD was not previously diagnosed with osteoporosis (87%) and received no anti-osteoporotic treatment (90%). Opportunistic screening in patients referred for cardiac CT revealed a substantial number of patients with very low BMD. The majority of these patients was not previously diagnosed with osteoporosis and received no anti-osteoporotic treatment. Identification of these patients could facilitate initiation of anti-osteoporotic treatment and reduce the occurrence of osteoporosis-related complications.

Opportunistic Screening for Osteoporosis Using Computed Tomography: State of the Art and Argument for Paradigm Shift

PURPOSE OF REVIEW

Osteoporosis is disproportionately common in rheumatology patients. For the past three decades, the diagnosis of osteoporosis has benefited from well-established practice guidelines that emphasized the use of dual x-ray absorptiometry (DXA). Despite these guidelines and the wide availability of DXA, approximately two thirds of eligible patients do not undergo testing. One strategy to improve osteoporosis testing is to employ computed tomography (CT) examinations obtained as part of routine patient care to "opportunistically" screen for osteoporosis, without additional cost or radiation exposure to patients. This review examines the role of opportunistic CT in the evaluation of osteoporosis.

RECENT FINDINGS

Recent evidence suggests that opportunistic measurement of bone attenuation (radiodensity) using CT has sensitivity comparable to DXA. More importantly, such an approach has been shown to predict osteoporotic fractures. The paradigm shift of using CTs obtained for other reasons to opportunistically screen for osteoporosis promises to substantially improve patient care.