{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T21:04:16Z","timestamp":1791493456076,"version":"4.3.4"},"reference-count":16,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T00:00:00Z","timestamp":1708992000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T00:00:00Z","timestamp":1708992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100002839","name":"Charit\u00e9 - Universit\u00e4tsmedizin Berlin","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100002839","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Skeletal Radiol"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Subtle spinal compression fractures can easily be missed. AI may help in interpreting these images. We propose to test the performance of an FDA-approved algorithm for fracture detection in radiographs on a per vertebra basis, assessing performance based on grade of compression, presence of foreign material, severity of degenerative changes, and acuity of the fracture.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Thoracic and lumbar spine radiographs with inquiries for fracture were retrospectively collected and analyzed by the AI. The presence or absence of fracture was defined by the written report or cross-sectional imaging where available. Fractures were classified semi-quantitatively by the Genant classification, by acuity, by the presence of foreign material, and overall degree of degenerative change of the spine. The results of the AI were compared to the gold standard.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 512 exams were included, depicting 4114 vertebra with 495 fractures. Overall sensitivity was 63.2% for the lumbar spine, significantly higher than the thoracic spine with 50.6%. Specificity was 96.7 and 98.3% respectively. Sensitivity increased with fracture grade, without a significant difference between grade 2 and 3 compression fractures (lumbar spine: grade 1, 52.5%; grade 2, 72.3%; grade 3, 75.8%; thoracic spine: grade 1, 42.4%; grade 2, 60.0%; grade 3, 60.0%). The presence of foreign material and a high degree of degenerative changes reduced sensitivity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Overall performance of the AI on a per vertebra basis was degraded in clinically relevant scenarios such as for low-grade compression fractures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00256-024-04626-2","type":"journal-article","created":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T16:21:04Z","timestamp":1709050864000},"page":"1563-1571","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["An overview of the performance of AI in fracture detection in lumbar and thoracic spine radiographs on a per vertebra basis"],"prefix":"10.1007","volume":"53","author":[{"given":"Oppenheimer","family":"J.","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L\u00fcken","family":"S.","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geveshausen","family":"S.","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamm","family":"B.","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niehues","family":"S. 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Epidemiology of fractures in the United Kingdom 1988\u20132012: Variation with age, sex, geography, ethnicity and socioeconomic status. Bone. 2016;87:19\u201326. https:\/\/doi.org\/10.1016\/j.bone.2016.03.006.","journal-title":"Bone"},{"issue":"11","key":"4626_CR3","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1016\/j.crad.2020.07.020","volume":"75","author":"DC Howlett","year":"2020","unstructured":"Howlett DC, Drinkwater KJ, Griffin J, Javaid K. Improving outcomes for patients with osteoporotic vertebral fragility fractures: the role of the radiologist. Clin Radiol. 2020;75(11):811\u20132. https:\/\/doi.org\/10.1016\/j.crad.2020.07.020.","journal-title":"Clin Radiol"},{"key":"4626_CR4","doi-asserted-by":"publisher","unstructured":"Rhee PM, Bridgeman A, Acosta JA, Kennedy S, Wang DS, Sarveswaran J, Rhea JT, Lumbar fractures in adult blunt trauma: axial and single-slice helical abdominal and pelvic computed tomographic scans versus portable plain films. 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Eur J Radiol. 2010;74(1):6\u201315. https:\/\/doi.org\/10.1016\/j.ejrad.2009.06.021.","journal-title":"Eur J Radiol"},{"issue":"1","key":"4626_CR7","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1186\/s12891-018-2171-y","volume":"19","author":"Y Li","year":"2018","unstructured":"Li Y, Yan L, Cai S, Wang P, Zhuang H, Yu H. The prevalence and under-diagnosis of vertebral fractures on chest radiograph. BMC Musculoskelet Disord. 2018;19(1):235. https:\/\/doi.org\/10.1186\/s12891-018-2171-y.","journal-title":"BMC Musculoskelet Disord"},{"key":"4626_CR8","doi-asserted-by":"publisher","unstructured":"Guermazi A, Tannoury C, Kompel AJ, Murakami AM, Ducarouge A, Gillibert A, Li X, Tournier A, Lahoud Y, Jarraya M, Lacave E, Rahimi H, Pourchot A, Parisien RL, Merritt AC, Comeau D, Regnard NE, Hayashi D, Improving Radiographic fracture recognition performance and efficiency using artificial intelligence. 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All patient data was anonymized, and no identifiable data or images were used in this study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Stefan Niehues has received research grants from Bracco Group, Bayer Vital GmbH, Canon Medical Systems and Guerbet. Bernd Hamm has received research grants for the Department of Radiology, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin from the following companies: (1) Abbott, (2) Actelion Pharmaceuticals, (3) Bayer Schering Pharma, (4) Bayer Vital, (5) BRACCO Group, (6) Bristol-Myers Squibb, (7) Charite Research Organisation GmbH, (8) Deutsche Krebshilfe, (9) Dt. Stiftung f\u00fcr Herzforschung, (10) Essex Pharma, (11) EU Programmes, (12) FibrexMedical Inc, (13) Focused Ultrasound Surgery Foundation, (14) Fraunhofer Gesellschaft, (15) Guerbet, (16) INC Research, (17) lnSightec Ud, (18) IPSEN Pharma, (19) Kendlel MorphoSys AG, (20) Lilly GmbH, (21) Lundbeck GmbH, (22) MeVis Medical Solutions AG, (23) Nexus Oncology, (24) Novartis, (25) Parexel Clinical Research Organisation Service, (26) Perceptive, (27) Pfizer GmbH, (28) Philipps, (29) Sanofis-Aventis S.A., (30) Siemens, (31) Spectranetics GmbH, (32) Terumo Medical Corporation, (33) TNS Healthcare GMbH, (34) Toshiba, (35) UCB Pharma, (36) Wyeth Pharma, (37) Zukunftsfond Berlin (TSB), (38) Amgen, (39) AO Foundation, (40) BARD, (41) BBraun, (42) Boehring Ingelheimer, (43) Brainsgate, (44) PPD (Clinical Research Organisation), (45) CELLACT Pharma, (46) Celgene, (47) CeloNova Bio-Sciences, (48) Covance, (49) DC Deviees, Ine. USA, (50) Ganymed, (51) Gilead Sciences, (52) GlaxoSmithKline, (53) ICON (Clinical Research Organisation), (54) Jansen, (55) LUX Bioseienees, (56) MedPass, (57) Merek, (58) Mologen, (59) Nuvisan, (60) Pluristem, (61) Quintiles, (62) Roehe, (63) SehumaeherGmbH (Sponsoring eines Workshops), (64) Seattle Geneties, (65) Symphogen, (66) TauRx Therapeuties Ud, (67) Accovion, (68) AIO: Arbeitsgemeinschaft Internistische Onkologie, (69) ASR Advanced sleep research, (70) Astellas, (71) Theradex, (72) Galena Biopharma, (73) Chiltern, (74) PRAint, (75) lnspiremd, (76) Medronic, (77) Respicardia, (78) Silena Therapeutics, (79) Spectrum Pharmaceuticals, (80) St Jude, (81) TEVA, (82) Theorem, (83) Abbvie, (84) Aesculap, (85) Biotronik, (86) Inventivhealth, (87) ISATherapeutics, (88) LYSARC, (89) MSD, (90) Novocure, (91) Ockham Oncology, (92) Premier-Research, (93) Psi-cro, (94) Tetec-ag, (95) Winicker-Norimed, (96) Achaogen Inc, (97) ADIR, (98) AstraZenaca AB, (99) Demira Inc, (100) Euroscreen S.A., (101) Galmed Research and Development Ltd, (102) GETNE, (103) Guidant Europe NV, (104) Holaira Inc, (105) Immunomedics Inc, (106) Innate Pharma, (107) Isis Pharmaceuticals Inc, (108) Kantar Health GmbH, (109) MedImmune Inc, (110) Medpace Germany GmbH (CRO), (111) Merrimack Pharmaceuticals Inc, (112) Millenium Pharmaceuticals Inc, (113) Orion Corporation Orion Pharma, (114) Pharmacyclics Inc, (115) PIQUR Therapeutics Ltd, (116) Pulmonx International S\u00e1rl, (117) Servier (CRO), (118) SGS Life Science Services (CRO), and (119) Treshold Pharmaceuticals Inc. These grants had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The remaining authors declare that they have no conflicts of interest and did not receive any funds.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}