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Automated Opportunistic Osteoporosis Screening in Routine Computed Tomography of the Spine: Comparison With Dedicated Quantitative CT
Authors:Nico Sollmann  Maximilian T. Löffler  Malek El Husseini  Anjany Sekuboyina  Michael Dieckmeyer  Sebastian Rühling  Claus Zimmer  Bjoern Menze  Gabby B. Joseph  Thomas Baum  Jan S. Kirschke
Affiliation:1. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany;2. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany

Contribution: Data curation, ​Investigation, Methodology, Resources, Software, Writing - review & editing;3. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Conceptualization, ​Investigation, Methodology, Resources, Software, Writing - review & editing;4. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: ​Investigation, Methodology, Resources, Software, Writing - review & editing;5. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Conceptualization, ​Investigation, Methodology, Validation, Writing - review & editing;6. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Data curation, ​Investigation, Methodology, Validation, Visualization, Writing - review & editing;7. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Funding acquisition, ​Investigation, Project administration, Resources, Supervision, Writing - review & editing;8. Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany

Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland

Contribution: Conceptualization, Funding acquisition, ​Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing - review & editing;9. Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA

Contribution: Data curation, Formal analysis, Software, Validation, Writing - review & editing;10. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Conceptualization, Data curation, Formal analysis, Funding acquisition, ​Investigation, Project administration, Resources, Writing - review & editing;11. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

Contribution: Conceptualization, Data curation, Formal analysis, Funding acquisition, ​Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing - review & editing

Abstract:Opportunistic osteoporosis screening in nondedicated routine computed tomography (CT) is of increasing importance. The purpose of this study was to compare lumbar volumetric bone mineral density (vBMD) assessed by a convolutional neural network (CNN)-based framework in routine CT to vBMD from dedicated quantitative CT (QCT), and to evaluate the ability of vBMD and surrogate measurements of Hounsfield units (HU) to distinguish between patients with and without osteoporotic vertebral fractures (VFs). A total of 144 patients (median age: 70.7 years, 93 females) with clinical routine CT (eight different CT scanners, 120 kVp or 140 kVp, with and without intravenous contrast medium) and dedicated QCT acquired within ≤30 days were included. Vertebral measurements included (i) vBMD from the CNN-based approach including automated vertebral body labeling, segmentation, and correction of the contrast media phase for routine CT data (vBMD_OPP), (ii) vBMD from dedicated QCT (vBMD_QCT), and (iii) noncalibrated HU from vertebral bodies of routine CT data as previously proposed for immanent opportunistic osteoporosis screening based on CT attenuation. The intraclass correlation coefficient (ICC) for vBMD_QCT versus vBMD_OPP indicated better agreement (ICC = 0.913) than the ICC for vBMD_QCT versus noncalibrated HU (ICC = 0.704). Bland-Altman analysis showed data points from 137 patients (95.1%) within the limits of agreement (LOA) of −23.2 to 25.0 mg/cm3 for vBMD_QCT versus vBMD_OPP. Osteoporosis (vBMD <80 mg/cm3) was detected in 89 patients (vBMD_QCT) and 88 patients (vBMD_OPP), whereas no patient crossed the diagnostic thresholds from normal vBMD to osteoporosis or vice versa. In a subcohort of 88 patients (thoracolumbar spine covered by imaging for VF reading), 69 patients showed one or more prevalent VFs, and the performance for discrimination between patients with and without VFs was best for vBMD_OPP (area under the curve [AUC] = 0.862; 95% confidence interval [CI], 0.771–0.953). In conclusion, automated opportunistic osteoporosis screening in routine CT of various scanner setups is feasible and may demonstrate high diagnostic accuracy for prevalent VFs. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
Keywords:bone QCT  fracture prevention  fracture risk assessment  osteoporosis  screening
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