Opportunistic Bone Density Measurement on Abdomen and Pelvis Computed Tomography to Predict Fracture Risk in Women Aged 50 to 64 Years Without Osteoporosis Risk Factors

Using advanced imaging to measure bone density, compression fracture risk, and risk for construct failure after spine surgery

Low bone mineral density (BMD) can predispose to vertebral body compression fractures and postoperative instrumentation failure. DEXA is considered the gold standard for measurement of BMD, however it is not obtained for all spine surgery patients preoperatively. There is a growing body of evidence suggesting that more routinely acquired spine imaging studies such as computed tomography (CT) and magnetic resonance imaging (MRI) can be opportunistically used to measure BMD. Here we review available studies that assess the validity of opportunistic screening with CT-derived Hounsfield Units (HU) and MRI-derived vertebral vone quality (VBQ) to measure BMD of the spine as well the utility of these measures in predicting postoperative outcomes. Additionally, we provide screening thresholds based on HU and VBQ for prediction of osteopenia/ osteoporosis and postoperative outcomes such as cage subsidence, screw loosening, proximal junctional kyphosis, and implant failure.

Coronal plane in opportunistic screening of osteoporosis using computed tomography: comparison with axial and sagittal planes

OBJECTIVE

To compare the coronal plane with axial and sagittal planes in opportunistic screening of osteoporosis using computed tomography (CT).

MATERIALS AND METHODS

A total of 100 patients aged ≥ 50 years who underwent both lumbar spine CT and dual-energy X-ray absorptiometry within 3 months were included. Osteoporosis was diagnosed based on dual-energy X-ray absorptiometry results. The CT number was measured at the center of the vertebral body in coronal, axial, and sagittal planes. To compare the coronal plane with axial and sagittal planes in diagnosing osteoporosis, the areas under the receiver operating characteristic curve (AUC) were compared and intraclass correlation coefficient (ICC) was calculated. The optimal cutoff values were calculated using Youden's index.

RESULTS

The AUC of the coronal plane (0.80; 95% confidence interval [CI], 0.71-0.89) was not significantly different from that of the axial plane (0.78; 95% CI, 0.68-0.87; P = 0.39) and that of the sagittal plane (0.78; 95% CI, 0.69-0.87; P = 0.68). Excellent concordance rates were observed between coronal and axial planes with ICC of 0.95 (95% CI, 0.92-0.96) and between coronal and sagittal planes with ICC of 0.93 (95% CI, 0.85-0.96). The optimal cutoff values for the coronal, axial, and sagittal planes were 110, 112, and 112 HU, respectively.

CONCLUSION

The coronal plane does not significantly differ from axial and sagittal planes in opportunistic screening of osteoporosis. Thus, the coronal plane as well as axial and sagittal planes can be used interchangeably in measuring bone mineral density using CT.

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

Opportunistic Screening Techniques for Analysis of CT Scans

PURPOSE OF REVIEW

Opportunistic screening is a combination of techniques to identify subjects of high risk for osteoporotic fracture using routine clinical CT scans prescribed for diagnoses unrelated to osteoporosis. The two main components are automated detection of vertebral fractures and measurement of bone mineral density (BMD) in CT scans, in which a phantom for calibration of CT to BMD values is not used. This review describes the particular challenges of opportunistic screening and provides an overview and comparison of current techniques used for opportunistic screening. The review further outlines the performance of opportunistic screening.

RECENT FINDINGS

A wide range of technologies for the automatic detection of vertebral fractures have been developed and successfully validated. Most of them are based on artificial intelligence algorithms. The automated differentiation of osteoporotic from traumatic fractures and vertebral deformities unrelated to osteoporosis, the grading of vertebral fracture severity, and the detection of mild vertebral fractures is still problematic. The accuracy of automated fracture detection compared to classical radiological semi-quantitative Genant scoring is about 80%. Accuracy errors of alternative BMD calibration methods compared to simultaneous phantom-based calibration used in standard quantitative CT (QCT) range from below 5% to about 10%. The impact of contrast agents, frequently administered in clinical CT on the determination of BMD and on fracture risk determination is still controversial. Opportunistic screening, the identification of vertebral fracture and the measurement of BMD using clinical routine CT scans, is feasible but corresponding techniques still need to be integrated into the clinical workflow and further validated with respect to the prediction of fracture risk.

Vertebral trabecular bone texture analysis in opportunistic MRI and CT scan can distinguish patients with and without osteoporotic vertebral fracture: A preliminary study

PURPOSE

To investigate the potential of texture parameters from opportunistic MRI and CT for the detection of patients with vertebral fragility fracture, to design a decision tree and to compute a Random Forest analysis for the prediction of fracture risk.

METHODS

One hundred and eighty vertebrae of sixty patients with at least one (30) or without (30) a fragility fracture were retrospectively assessed. Patients had a DXA, an MRI and a CT scan from the three first lumbar vertebrae. Vertebrae texture analysis was performed in routine abdominal or lumbar CT and lumbar MRI using 1st and 2nd order texture parameters. Hounsfield Unit Bone density (HU BD) was also measured on CT-scan images.

RESULTS

Twelve texture parameters, Z-score and HU BD were significantly different between the two groups whereas T score and BMD were not. The inter observer reproducibility was good to excellent. Decision tree showed that age and HU BD were the most relevant factors to predict the fracture risk with a 93 % sensitivity and 56 % specificity. AUC was 0.91 in MRI and 0.92 in CT-scan using the Random Forest analysis. The corresponding sensitivity and specificity were 72 % and 93 % in MRI and 83 and 89 % in CT.

CONCLUSIONS

This study is the first to compare texture indices computed from opportunistic CT and MR images. Age and HU-BD together with selected texture parameters could be used to assess risk fracture. Machine learning algorithm can detect fracture risk in opportunistic CT and MR imaging and might be of high interest for the diagnosis of osteoporosis.

Machine learning for the prediction of osteopenia/osteoporosis using the CT attenuation of multiple osseous sites from chest CT

PURPOSE

To use machine learning and the CT attenuation of all bones visible on chest CT scans to predict osteopenia/osteoporosis.

METHOD

We retrospectively evaluated 364 patients with CT scans of the chest, and Dual-energy X-ray absorptiometry (DXA) scans within 6 months of each other. Studies were performed between 01/01/2015 and 08/01/2021. Volumetric segmentation of the ribs, thoracic vertebrae, sternum, and clavicle was performed using 3D Slicer to obtain the mean CT attenuation of each bone. The study sample was randomly split into training/validation (80 %, n = 291 patients) and test (20 %, n = 73 patients) datasets. Univariate analyses were used to identify the optimal CT attenuation thresholds to diagnose osteopenia/osteoporosis. We used penalized multivariable logistic regression models including Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net, and Ridge regression, and Support Vector Machines (SVM) with radial basis functions (RBF) to predict osteopenia/osteoporosis and compared these results to the CT attenuation threshold at T12.

RESULTS

There were positive correlations between the CT attenuation between all bones (r > 0.6, P < 0.001 for all). There were positive correlations between CT attenuation of the bones and the L1-L4 BMD T-score, total hip T-score, and femoral neck T-scores (r > 0.4, P < 0.001 for all). A CT attenuation threshold of 170.2 Hounsfield units (HU) at T12 had an AUC of 0.702, while a threshold of 192.1 HU at T4 had an AUC of 0.757. The SVM with RBF had the highest AUC (AUC = 0.864) and was better than the LASSO (P = 0.011), Elastic Net (P = 0.011), Ridge regression (P = 0.011) but was not better than using the CT attenuation at T12 (P = 0.060).

CONCLUSIONS

The CT attenuation of the ribs, thoracic vertebra, sternum, and clavicle can be used individually and collectively to predict BMD and to predict osteopenia/osteoporosis.

Bone density and strength from thoracic and lumbar CT scans both predict incident vertebral fractures independently of fracture location

In a population-based study, we found that computed tomography (CT)-based bone density and strength measures from the thoracic spine predicted new vertebral fracture as well as measures from the lumbar spine, suggesting that CT scans at either the thorax or abdominal regions are useful to assess vertebral fracture risk.

INTRODUCTION

Prior studies have shown that computed tomography (CT)-based lumbar bone density and strength measurements predict incident vertebral fracture. This study investigated whether CT-based bone density and strength measurements from the thoracic spine predict incident vertebral fracture and compared the performance of thoracic and lumbar bone measurements to predict incident vertebral fracture.

METHODS

This case-control study of community-based men and women (age 74.6 ± 6.6) included 135 cases with incident vertebral fracture at any level and 266 age- and sex-matched controls. We used baseline CT scans to measure integral and trabecular volumetric bone mineral density (vBMD) and vertebral strength (via finite element analysis, FEA) at the T8 and L2 levels. Association between these measurements and vertebral fracture was determined by using conditional logistic regression. Sensitivity and specificity for predicting incident vertebral fracture were determined for lumbar spine and thoracic bone measurements.

RESULTS

Bone measurements from T8 and L2 predicted incident vertebral fracture equally well, regardless of fracture location. Specifically, for predicting vertebral fracture at any level, the odds ratio (per 1-SD decrease) for the vBMD and strength measurements at L2 and T8 ranged from 2.0 to 2.7 (p < 0.0001) and 1.8 to 2.8 (p < 0.0001), respectively. Results were similar when predicting fracture only in the thoracic versus the thoracolumbar spine. Lumbar and thoracic spine bone measurements had similar sensitivity and specificity for predicting incident vertebral fracture.

CONCLUSION

These findings indicated that like those from the lumbar spine, CT-based bone density and strength measurements from the thoracic spine may be useful for identifying individuals at high risk for vertebral fracture.

Opportunistic Computed Tomography and Spine Surgery: A Narrative Review

STUDY DESIGN

Narrative review.

OBJECTIVE

This article seeks to provide a narrative review regarding the ability of opportunistic information available from computed tomography (CT) scans to guide decisions in spine surgery related to patient bone quality.

METHODS

A review of the literature (limited to human and English language) was performed via PubMed and Google Scholar using the search terms; "osteoporosis" AND "opportunistic" AND "computed tomography" AND "spine surgery." The titles and then abstracts of all identified citations were reviewed for inclusion by 2 of the authors (MS, BAF). Relevant articles were then studied in full text.

RESULTS

A review of the literature found 25 articles that were selected for inclusion in this narrative review. These articles were broadly divided into 4 subcategories: (1) opportunistic CT (oCT) and osteoporosis detection, (2) oCT data and the quality of screw fixation, (3) utilization of Hounsfield units to assess clinical and/or radiographic outcomes following spine fusion, and (4) virtual stress testing in spine surgery.

CONCLUSION

The literature on oCT, as well as associated virtual stress-testing techniques, demonstrate the potential to enhance spine surgery outcomes by preoperatively identifying at-risk patients in need of bone health optimization and informing best techniques for performing spinal fusion surgery on patients with diminished bone quality. While our narrative summary of the limited literature to date suggests a promising future for oCT data, significant additional research and/or radiographic workflow standardization is needed to validate these methods for clinical use.

Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA

Objectives

To compare opportunistic quantitative CT (QCT) with dual energy X-ray absorptiometry (DXA) in their ability to predict incident vertebral fractures.

Methods

We included 84 patients aged 50 years and older, who had routine CT including the lumbar spine and DXA within a 12-month period (baseline) as well as follow-up imaging after at least 12 months or who sustained an incident vertebral fracture documented earlier. Patients with bone disorders aside from osteoporosis were excluded. Fracture status and trabecular bone mineral density (BMD) were retrospectively evaluated in baseline CT and fracture status was reassessed at follow-up. BMD_QCT was assessed by opportunistic QCT with asynchronous calibration of multiple MDCT scanners.

Results

Sixteen patients had incident vertebral fractures showing lower mean BMD_QCT than patients without fracture (p = 0.001). For the risk of incident vertebral fractures, the hazard ratio increased per SD in BMD_QCT (4.07; 95% CI, 1.98–8.38), as well as after adjusting for age, sex, and prevalent fractures (2.54; 95% CI, 1.09–5.90). For DXA, a statistically significant increase in relative hazard per SD decrease in T-score was only observed after age and sex adjustment (1.57; 95% CI, 1.04–2.38). The predictability of incident vertebral fractures was good by BMD_QCT (AUC = 0.76; 95% CI, 0.64–0.89) and non-significant by T-scores. Asynchronously calibrated CT scanners showed good long-term stability (linear drift ranging from − 0.55 to − 2.29 HU per year).

Conclusions

Opportunistic screening of mainly neurosurgical and oncologic patients in CT performed for indications other than densitometry allows for better risk assessment of imminent vertebral fractures than dedicated DXA.

Key Points

• Opportunistic QCT predicts osteoporotic vertebral fractures better than DXA reference standard in mainly neurosurgical and oncologic patients.

• More than every second patient (56%) with an incident vertebral fracture was misdiagnosed not having osteoporosis according to DXA.

• Standard ACR QCT-cutoff values for osteoporosis (< 80 mg/cm³) and osteopenia (≤ 120 mg/cm³) can also be applied scanner independently in calibrated opportunistic QCT.

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.