Clinical Utility Of Computer-Aided Diagnosis Of Vertebral Fractures From Computed Tomography Images

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 (R)) 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. (c) 2020 American Society for Bone and Mineral Research (ASBMR).