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Clinical Utility of Computer-Aided Diagnosis of Vertebral Fractures From Computed Tomography Images |
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| Authors: | Nithin Kolanu Elizabeth J Silverstone Bao H Ho Hiep Pham Ash Hansen Emma Pauley Anna R Quirk Sarah C Sweeney Jacqueline R Center Nicholas A Pocock |
| Institution: | 1. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia;2. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia
Contribution: Data curation, Formal analysis, Investigation, Methodology, Resources;3. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia Contribution: Investigation;4. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia Contribution: Resources;5. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia Contribution: Data curation;6. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia Garvan Institute of Medical Research, Sydney, NSW, Australia Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia Contribution: Conceptualization, Methodology, Supervision, Writing - review & editing;7. Endocrinology/Radiology and Nuclear Medicine, St Vincent's Hospital, Darlinghurst, NSW, Australia Garvan Institute of Medical Research, Sydney, NSW, Australia Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia Contribution: Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing - review & editing |
| Abstract: | Osteoporotic vertebral compression fractures (VCFs) are a risk factor for morbidity and mortality, frequently asymptomatic and often present in computed tomography (CT) scans performed for unrelated conditions. Computer-aided diagnosis (CAD) of VCF from such images can potentially improve identification and treatment of osteoporosis. This single-blinded, single tertiary center study compared a CAD (Zebra Medical Vision®) to an adjudicated imaging specialist reevaluation using a retrospective consecutive sample of abdominal and thoracic CT scans (n = 2357) performed as part of routine care. Subjects over 50 years between January 1, 2019 and May 12, 2019 were included. Duplicates and unanalyzable scans were excluded resulting in a total of 1696 CT scans. The sensitivity, specificity, and accuracy were calculated for all VCF and for Genant grades 2 or 3 (ie, height loss of >25%) using imaging specialist as the gold standard. Prestudy VCF reporting by hospital-rostered radiologist was used to calculate the number of scans needed to screen (NNS) to detect one additional VCF using CAD. Prevalence of any VCF was 24% (406/1696) and of Genant 2/3 VCF was 18% (280/1570). The sensitivity and specificity were 54% and 92%, for all fractures, respectively, and 65% and 92% for Genant 2/3 fractures, respectively. Accuracy for any VCF, and for detection of Genant 2/3 VCF, was 83% and 88%, respectively. Of 221 CAD-detected VCFs, 133 (60.2%) were reported prestudy resulting in 88 additional fractures (72 Genant 2/3) being identified by CAD. NNS to detect one additional VCF was 19 scans for all fractures and 23 for Genant 2/3 fractures. Thus, the CAD tested in this study had a high specificity with moderate sensitivity to detect incidental vertebral fractures in CT scans performed for routine care. A low NNS suggests it is an efficient tool to assist radiologists and clinicians to improve detection and reporting of vertebral fractures. © 2020 American Society for Bone and Mineral Research (ASBMR). |
| Keywords: | FRACTURE PREVENTION FRACTURE RISK ASSESSMENT HEALTH SERVICES RESEARCH OSTEOPOROSIS RADIOLOGY |