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

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.

Assessing Thoracic Vertebral Bone Mineral Density (T8-T10) for Osteoporosis Diagnosis During CT Lung Cancer Screening in Older Adults

Introduction

Osteoporosis diagnosis often utilizes quantitative computed tomography (QCT). This study explored the validity of applying lumbar bone mineral density (LBMD) standards to thoracic vertebrae (T8-T10) for osteoporosis detection during CT lung cancer screenings. This study investigated the utility of thoracic BMD (BMD-T8-T10) for detecting osteoporosis in older persons during CT lung cancer screening.

Methods

We studied 701 participants who underwent QCT scans for both LBMD and BMD-T8-T10. Osteoporosis was diagnosed using ACR criteria based on LBMD. We determined BMD-T8-T10 thresholds via a receiver operating characteristic (ROC) curve and translated BMD-T8+T9+T10 to LBMD (TTBMD) using linear regression. Kappa test was used to evaluate the accuracy of BMD-T8-T10 thresholds and TTBMD in diagnosing osteoporosis.

Results

Raw BMD-T8-T10 poorly identified osteoporosis (kappa = 0.51). ROC curve analysis identified BMD-T8-T10 thresholds for osteopenia (138 mg/cm3) and osteoporosis (97 mg/cm3) with areas under the curve of 0.97 and 0.99, respectively. We normalized BMD-T8-T10 to TTBMD based on the formula: TTBMD = 0.9 × BMD-T8-T10 - 2.56. These thresholds (kappa = 0.74) and TTBMD performed well in detecting osteoporosis/osteopenia (kappa = 0.74).

Conclusion

Both calculating BMD-T8-T10 threshold (138.0 mg/cm3 for osteopenia and 97 mg/cm3 for osteoporosis) and normalizing BMD-T8-T10 to LBMD demonstrated good performance in identifying osteoporosis in older adults during CT lung cancer screening.

Bone mineral density in lower thoracic vertebra for osteoporosis diagnosis in older adults during CT lung cancer screening

BACKGROUND

Quantitative computed tomography (QCT)-based lumbar bone mineral density (LBMD) has been used to diagnose osteoporosis. This study explored the value of lower thoracic BMD (TBMD) in diagnosing osteoporosis in older adults during CT lung cancer screening.

METHODS

This study included 751 subjects who underwent QCT scans with both LBMD and TBMD. 141 of them was selected for a validation. Osteoporosis was diagnosed based on LBMD using the ACR criteria (gold standard). TBMD thresholds were obtained using receiver operating characteristic curve. TBMD was also translated into LBMD (TTBMD) and osteoporosis was defined based on TTBMD using ACR criteria. The performance of TBMD and TTBMD in identifying osteoporosis was determined by Kappa test. The associations between TBMD- and TTBMD-based osteoporosis and fracture were tested in 227 subjects with followed up status of spine fracture.

RESULTS

The performance of TBMD in identifying osteoporosis was low (kappa = 0.66) if using the ACR criteria. Two thresholds of TBMD for identifying osteopenia (128 mg/cm3) and osteoporosis (91 mg/cm3) were obtained with areas under the curve of 0.97 and 0.99, respectively. The performance of the identification of osteoporosis/osteopenia using the two thresholds or TTBMD both had good agreement with the gold standard (kappa = 0.78, 0.86). Similar results were observed in validation population. Osteoporosis identified using the thresholds (adjusted hazard ratio (HR) = 18.72, 95% confidence interval (CI): 5.13-68.36) or TTBMD (adjusted HR = 10.28, 95% CI: 4.22-25.08) were also associated with fractures.

CONCLUSION

Calculating the threshold of TBMD or normalizing TBMD to LBMD are both useful in identifying osteoporosis in older adults during CT lung cancer screening.

Quantitative CT Evaluation of Bone Mineral Density in the Thoracic Spine on 18F-Fluorocholine PET/CT Imaging in Patients With Primary Hyperparathyroidism

INTRODUCTION

Measurement of bone mineral density (BMD) with quantitative CT (QCT) carries several advantages over other densitometric techniques, including superior assessment of the spine. As most QCT studies evaluated the lumbar spine, measurements of the thoracic spine are limited. We performed QCT analysis of the thoracic spine in a cohort of patients with primary hyperparathyroidism.

MATERIALS AND METHODS

This study was a retrospective QCT analysis of the thoracic spine on 18F-fluorocholine PET/CT scans in patients with primary hyperparathyroidism patients between March 2018 and December 2022. Correlations between QCT-derived BMD or Hounsfield units (HU) and demographic data, laboratory parameters, results from histopathological examination after parathyroidectomy and results of DXA imaging were analyzed, when available.

RESULTS

In 189 patients, mean QCT-derived BMD at the thoracic spine was 85.6 mg/cm3. Results from recent DXA were available in 122 patients. Mean thoracic QCT-derived BMD and HU were significantly correlated with DXA-derived BMD in lumbar spine, total hip and femoral neck and with the lowest T-score at DXA imaging. Only weak correlations were found with BMI or 18F-fluorocholine uptake, while no significant correlations were found with adenoma weight, PTH or calcium levels.

CONCLUSION

Our study confirms correlation between QCT-derived BMD in the thoracic spine with age and DXA-derived BMD measurements within a population of patients with primary hyperparathyroidism. Establishment of reference BMD values for individual thoracic vertebrae, may allow direct osteoporosis classification on thoracic CT imaging.

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.

Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography

OBJECTIVE

This study developed a diagnostic tool combining machine learning (ML) segmentation and radiomic texture analysis (RTA) for bone density screening using chest low-dose computed tomography (LDCT).

METHODS

A total of 197 patients who underwent LDCT followed by dual-energy X-ray absorptiometry were analyzed. First, an autosegmentation model was trained using LDCT to delineate the thoracic vertebral body (VB). Second, a two-level classifier was developed using radiomic features extracted from VBs for the hierarchical pairwise classification of each patient's bone status. All the patients were initially classified as either normal or abnormal, and all patients with abnormal bone density were then subdivided into an osteopenia group and an osteoporosis group. The performance of the classifier was evaluated through fivefold cross-validation.

RESULTS

The model for automated VB segmentation achieved a Sorenson-Dice coefficient of 0.87 ± 0.01. Furthermore, the area under the receiver operating characteristic curve scores for the two-level classifier were 0.96 ± 0.01 for detecting abnormal bone density (accuracy = 0.91 ± 0.02; sensitivity = 0.93 ± 0.03; specificity = 0.89 ± 0.03) and 0.98 ± 0.01 for distinguishing osteoporosis (accuracy = 0.94 ± 0.02; sensitivity = 0.95 ± 0.03; specificity = 0.93 ± 0.03). The testing prediction accuracy levels for the first- and second-level classifiers were 0.92 ± 0.04 and 0.94 ± 0.05, respectively. The overall testing prediction accuracy of our method was 0.90 ± 0.05.

CONCLUSION

The combination of ML segmentation and RTA for automated bone density prediction based on LDCT scans is a feasible approach that could be valuable for osteoporosis screening during lung cancer screening.

KEY POINTS

• This study developed an automatic diagnostic tool combining machine learning-based segmentation and radiomic texture analysis for bone density screening using chest low-dose computed tomography. • The developed method enables opportunistic screening without quantitative computed tomography or a dedicated phantom. • The developed method could be integrated into the current clinical workflow and used as an adjunct for opportunistic screening or for patients who are ineligible for screening with dual-energy X-ray absorptiometry.

Computed Tomography of the Chest as a Screening Tool for Low Bone Mineral Density

INTRODUCTION

Computed tomography (CT) Hounsfield units (HU) recently emerged as a promising screening tool for low bone mineral density (BMD). We hypothesized that CT HU measurements of the thoracic spine would significantly and positively correlate with dual X-ray absorptiometry (DXA) BMD scans of the femoral neck.

MATERIALS AND METHODS

The study included patients with DXA scans and thoracic CT scans at the Walter Reed National Military Medical Center. One author, blinded to the DXA scans, measured HU from the cancellous bone in T4 vertebrae. Another author statistically compared femoral neck DXA T-scores to the CT HU measurements.

RESULTS

The study included 145 patients with CT scans and femoral neck DXAs. The osteoporotic and osteopenic groups had a significant difference in HU measurements compared to the normal group within the study (P < .0001 and .002, respectively). A low BMD screening value of 231 HU provided a sensitivity of 90.1% and negative predictive value of 85.7%.

CONCLUSION

Thoracic vertebrae HU measurements correlate with a low BMD of the femoral neck as determined by DXA T-scores. A high sensitivity and negative predictive value was achieved with a screening value of 231 HU. Utilization of chest or thoracic spine CT imaging as a screening method provides a quick and available screening tool for assessing low BMD in patients with these scans.Level of Evidence: III (Diagnostic).

Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: phantom-based validation and parameter influence evaluation

Asynchronous calibration could allow opportunistic screening based on routine CT for early osteoporosis detection. In this phantom study, a bone mineral density (BMD) calibration phantom and multi-energy CT (MECT) phantom were imaged on eight different CT scanners with multiple tube voltages (80-150 kV_p) and image reconstruction settings (e.g. soft/hard kernel). Reference values for asynchronous BMD estimation were calculated from the BMD-phantom and validated with six calcium composite inserts of the MECT-phantom with known ground truth. Relative errors/changes in estimated BMD were calculated and investigated for influence of tube voltage, CT scanner and reconstruction setting. Reference values for 282 acquisitions were determined, resulting in an average relative error between calculated BMD and ground truth of - 9.2% ± 14.0% with a strong correlation (R² = 0.99; p < 0.0001). Tube voltage and CT scanner had a significant effect on calculated BMD (p < 0.0001), with relative differences in BMD of 3.8% ± 28.2% when adapting reference values for tube voltage, - 5.6% ± 9.2% for CT scanner and 0.2% ± 0.2% for reconstruction setting, respectively. Differences in BMD were small when using reference values from a different CT scanner of the same model (0.0% ± 1.4%). Asynchronous phantom-based calibration is feasible for opportunistic BMD assessment based on CT images with reference values adapted for tube voltage and CT scanner model.

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.

Osteoporosis screening using computed tomography for men with prostate cancer: results of a prospective study

We performed a prospective study using both FRAX and computed tomography to screen for osteoporosis in men undergoing radiation for prostate cancer. We found that implementing routine computed tomography (CT)-based screening was feasible in the setting of a prospective study, but the yield of osteoporosis identification was low in this population.

PURPOSE

Men with prostate cancer (PCa) are at increased risk of hip fracture for multiple reasons. Estimation of hip fracture risk with the FRAX tool is currently recommended, but FRAX alone may not identify a portion of men with osteoporosis. We hypothesized that adding bone mineral density (BMD) screening using CT to FRAX is feasible and would identify more men with osteoporosis.

METHODS

Men with PCa scheduled to undergo CT simulation for radiation treatment were enrolled in a single-arm prospective study. The mean attenuation of the mid-L5 vertebral body trabecular bone (L5_CT) was calculated on a single slice using the radiation simulation CT scan. The 10-year risk of hip fracture was calculated using the FRAX tool. Dual energy X-ray absorptiometry (DXA) was performed for men whose L5_CT measurement was less than 130 Hounsfield units (HU).

RESULTS

A total of 98 eligible men were enrolled and underwent FRAX and CT screening. The median 10-year risk of hip fracture was 1.1% and exceeded 3% in 16 cases; the median L5_CT was 162.28 HU (range 55.6-526.1 HU). DXA scan was completed in 15 men who had L5_CT < 130 HU but 10-year calculated hip fracture risk < 3%, 1 of whom was found to have osteoporosis (T-score ≤ -2.5).

CONCLUSIONS

Implementing CT-based BMD screening was feasible in the setting of a prospective study for men receiving radiation for PCa, but fewer cases than anticipated of osteoporosis were identified.

X-ray-based quantitative osteoporosis imaging at the spine

Osteoporosis is a metabolic bone disease with a high prevalence that affects the population worldwide, particularly the elderly. It is often due to fractures associated with bone fragility that the diagnosis of osteoporosis becomes clinically evident. However, early diagnosis would be necessary to initiate therapy and to prevent occurrence of further fractures, thus reducing morbidity and mortality. X-ray-based imaging plays a key role for fracture risk assessment and monitoring of osteoporosis. Whereas over decades dual-energy X-ray absorptiometry (DXA) has been the main method used and still reflects the reference standard, another modality reemerges with quantitative computed tomography (QCT) because of its three-dimensional advantages and the opportunistic exploitation of routine CT scans. Against this background, this article intends to review and evaluate recent advances in the field of X-ray-based quantitative imaging of osteoporosis at the spine. First, standard DXA with the recent addition of trabecular bone score (TBS) is presented. Secondly, standard QCT, dual-energy BMD quantification, and opportunistic BMD screening in non-dedicated CT exams are discussed. Lastly, finite element analysis and microstructural parameter analysis are reviewed.

Association between osteoporotic femoral neck fractures and DXA-derived 3D measurements at lumbar spine: a case-control study

A case-control study assessing the association of DXA-derived 3D measurements at lumbar spine with osteoporotic hip fractures was performed. Stronger association was found between transcervical hip fractures and integral (AUC = 0.726), and cortical (AUC = 0.696) measurements at the lumbar spine compared with measurements at the trabecular bone (AUC = 0.617); although femur areal bone mineral density (aBMD) remains the referent measurement for hip fracture risk evaluation (AUC = 0.838).

PURPOSE

The aim of the present study was to evaluate the association between DXA-derived 3D measurements at lumbar spine and osteoporotic hip fractures.

METHODS

We analyzed a case-control database composed by 61 women with transcervical hip fractures and 61 age-matched women without any type of fracture. DXA scans at lumbar spine were acquired, and areal bone mineral density (aBMD) was measured. Integral, trabecular and cortical volumetric BMD (vBMD), cortical thickness, and cortical surface BMD (sBMD) at different regions of interest were assessed using a DXA-based 3D modeling software. Descriptive statistics, tests of difference, odds ratio (OR), and area under the receiver operating curve (AUC) were used to compare hip fracture and control groups.

RESULTS

Integral vBMD, cortical vBMD, cortical sBMD, and cortical thickness were the DXA-derived 3D measurements at lumbar spine that showed the stronger association with transcervical hip fractures, with AUCs in the range of 0.685-0.726, against 0.670 for aBMD. The highest AUC (0.726) and OR (2.610) at the lumbar spine were found for integral vBMD at the posterior vertebral elements. Significantly, lower AUC (0.617) and OR (1.607) were found for trabecular vBMD at the vertebral body. Overall, total femur aBMD remains the DXA-derived measurement showing the highest AUC (0.838) and OR (6.240).

CONCLUSION

This study showed the association of DXA-derived measurements at lumbar spine with transcervical hip fractures. A strong association between vBMD at the posterior vertebral elements and transcervical hip fractures was observed, probably because of global deterioration of the cortical bone. Further studies should be carried out to investigate on the relative risk of transcervical fracture in patients with long-term cortical structural deterioration.