{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:44:35Z","timestamp":1786977875476,"version":"build-2736575974"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T00:00:00Z","timestamp":1687737600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100002429","name":"Amgen","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002429","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["asbmr.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["JBMR Plus"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Vertebral compression fractures (VCF) are common in patients older than 50\u2009years but are often undiagnosed. Zebra Medical Imaging developed a VCF detection algorithm, with machine learning, to detect VCFs from CT images of the chest and\/or abdomen\/pelvis. In this study, we evaluated the diagnostic performance of the algorithm in identifying VCF. We conducted a blinded validation study to estimate the operating characteristics of the algorithm in identifying VCFs using previously completed CT scans from 1200 women and men aged 50\u2009years and older at a tertiary\u2010care center. Each scan was independently evaluated by two of three neuroradiologists to identify and grade VCF. Disagreements were resolved by a senior neuroradiologist. The algorithm evaluated the CT scans in a separate workstream. The VCF algorithm was not able to evaluate CT scans for 113 participants. Of the remaining 1087 study participants, 588 (54%) were women. Median age was 73\u2009years (range 51\u2013102\u2009years; interquartile range 66\u201381). For the 1087 algorithm\u2010evaluated participants, the sensitivity and specificity of the VCF algorithm in diagnosing any VCF were 0.66 (95% confidence interval [CI] 0.59\u20130.72) and 0.90 (95% CI 0.88\u20130.92), respectively, and for diagnosing moderate\/severe VCF were 0.78 (95% CI 0.70\u20130.85) and 0.87 (95% CI 0.85\u20130.89), respectively. Implementing this VCF algorithm within radiology systems may help to identify patients at increased fracture risk and could support the diagnosis of osteoporosis and facilitate appropriate therapy. \u00a9 2023 Amgen, Inc.\n                    <jats:italic>JBMR Plus<\/jats:italic>\n                    published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.\n                  <\/jats:p>","DOI":"10.1002\/jbm4.10778","type":"journal-article","created":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T00:04:10Z","timestamp":1687824250000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Opportunistic\n                    <scp>CT<\/scp>\n                    Screening\u2014Machine Learning Algorithm Identifies Majority of Vertebral Compression Fractures: A Cohort Study"],"prefix":"10.1093","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5299-4524","authenticated-orcid":false,"given":"John H","family":"Page","sequence":"first","affiliation":[{"name":"Center for Observational Research, Amgen Inc.  Thousand Oaks CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Franklin G","family":"Moser","sequence":"additional","affiliation":[{"name":"Department of Imaging Cedars\u2010Sinai Medical Center  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcel M","family":"Maya","sequence":"additional","affiliation":[{"name":"Department of Imaging Cedars\u2010Sinai Medical Center  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravi","family":"Prasad","sequence":"additional","affiliation":[{"name":"Department of Imaging Cedars\u2010Sinai Medical Center  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barry D","family":"Pressman","sequence":"additional","affiliation":[{"name":"Department of Imaging Cedars\u2010Sinai Medical Center  Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,6,26]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0002-9343(93)90218-E"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(18)32112-3"},{"key":"e_1_2_9_4_1","first-page":"1","article-title":"Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. 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