{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T03:05:00Z","timestamp":1792206300809,"version":"4.4.0"},"reference-count":25,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"},{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:00:00Z","timestamp":1700179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100020344","name":"Gesellschaft f\u00fcr Forschungsf\u00f6rderung Nieder\u00f6sterreich","doi-asserted-by":"publisher","award":["LS20-020"],"award-info":[{"award-number":["LS20-020"]}],"id":[{"id":"10.13039\/100020344","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Danube University Krems University for Continuing Education"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knee surg. sports traumatol. arthrosc."],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>The aim of this study was to investigate the performance of an artificial intelligence (AI)\u2010based software for fully automated analysis of leg alignment pre\u2010 and postoperatively after high tibial osteotomy (HTO) on long\u2010leg radiographs (LLRs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Long\u2010leg radiographs of 95 patients with varus malalignment that underwent medial open\u2010wedge HTO were analyzed pre\u2010 and postoperatively. Three investigators and an AI software using deep learning algorithms (LAMA\u2122, ImageBiopsy Lab, Vienna, Austria) evaluated the hip\u2013knee\u2013ankle angle (HKA), mechanical axis deviation (MAD), joint line convergence angle (JLCA), medial proximal tibial angle (MPTA), and mechanical lateral distal femoral angle (mLDFA). All measurements were performed twice and the performance of the AI software was compared with individual human readers using a Bayesian mixed model. In addition, the inter\u2010observer intraclass correlation coefficient (ICC) for inter\u2010observer reliability was evaluated by comparing measurements from manual readers. The intra\u2010reader variability for manual measurements and the AI\u2010based software was evaluated using the intra\u2010observer ICC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Initial varus malalignment was corrected to slight valgus alignment after HTO. Measured by the AI algorithm and manually HKA (5.36\u00b0\u2009\u00b1\u20093.03\u00b0 and 5.47\u00b0\u2009\u00b1\u20092.90\u00b0 to \u2212 0.70\u2009\u00b1\u20092.34 and \u2212 0.54\u2009\u00b1\u20092.31), MAD (19.38\u00a0mm\u2009\u00b1\u200911.39\u00a0mm and 20.17\u00a0mm\u2009\u00b1\u200910.99\u00a0mm to \u2212 2.68\u2009\u00b1\u20098.75 and \u2212 2.10\u2009\u00b1\u20098.61) and MPTA (86.29\u00b0\u2009\u00b1\u20092.42\u00b0 and 86.08\u00b0\u2009\u00b1\u20092.34\u00b0 to 91.6\u2009\u00b1\u20093.0 and 91.81\u2009\u00b1\u20092.54) changed significantly from pre\u2010 to postoperative, while JLCA and mLDFA were not altered. The fully automated AI\u2010based analyses showed no significant differences for all measurements compared with manual reads neither in native preoperative radiographs nor postoperatively after HTO. Mean absolute differences between the AI\u2010based software and mean manual observer measurements were 0.5\u00b0 or less for all measurements. Inter\u2010observer ICCs for manual measurements were good to excellent for all measurements, except for JLCA, which showed moderate inter\u2010observer ICCs. Intra\u2010observer ICCs for manual measurements were excellent for all measurements, except for JLCA and for MPTA postoperatively. For the AI\u2010aided analyses, repeated measurements showed entirely consistent results for all measurements with an intra\u2010observer ICC of 1.0.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The AI\u2010based software can provide fully automated analyses of native long\u2010leg radiographs in patients with varus malalignment and after HTO with great accuracy and reproducibility and could support clinical workflows.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of evidence<\/jats:title>\n                    <jats:p>Diagnostic study, Level III.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00167-023-07644-0","type":"journal-article","created":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T01:14:22Z","timestamp":1700183662000},"page":"5885-5895","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Artificial intelligence\u2010based analyses of varus leg alignment and after high tibial osteotomy show high accuracy and reproducibility"],"prefix":"10.1002","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4829-2711","authenticated-orcid":false,"given":"Christoph","family":"Stotter","sequence":"first","affiliation":[{"name":"Department for Orthopedics and Traumatology Landesklinikum Baden\u2010M\u00f6dling 2340 M\u00f6dling Austria"},{"name":"Department for Health Sciences Medicine and Research University for Continuing Education Krems 3500 Krems Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Klestil","sequence":"additional","affiliation":[{"name":"Department for Orthopedics and Traumatology Landesklinikum Baden\u2010M\u00f6dling 2340 M\u00f6dling Austria"},{"name":"Department for Health Sciences Medicine and Research University for Continuing Education Krems 3500 Krems Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenneth","family":"Chen","sequence":"additional","affiliation":[{"name":"Department for Orthopedics and Traumatology Landesklinikum Baden\u2010M\u00f6dling 2340 M\u00f6dling Austria"},{"name":"Department for Health Sciences Medicine and Research University for Continuing Education Krems 3500 Krems Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allan","family":"Hummer","sequence":"additional","affiliation":[{"name":"ImageBiopsy Lab 1140 Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Salzlechner","sequence":"additional","affiliation":[{"name":"ImageBiopsy Lab 1140 Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Angele","sequence":"additional","affiliation":[{"name":"Clinic for Trauma and Reconstructive Surgery University Medical Center Regensburg 93042 Regensburg Germany"},{"name":"Sporthopaedicum Regensburg 93053 Regensburg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Nehrer","sequence":"additional","affiliation":[{"name":"Department for Health Sciences Medicine and Research University for Continuing Education Krems 3500 Krems 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distribution of knee morphology according to CPAK and functional phenotype classification: analysis of 8739 osteoarthritic knees prior to total knee arthroplasty using artificial intelligence","volume":"31","author":"Huber S","year":"2023","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167\u2010022\u201007124\u2010x"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278\u2010022\u201000671\u20102"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11999\u2010013\u20103146\u20109"},{"key":"e_1_2_12_16_1","volume-title":"Artificial intelligence in medicine","author":"Nehrer S","year":"2021"},{"issue":"1","key":"e_1_2_12_17_1","first-page":"18","article-title":"Prinzipien der kniegelenknahen Deformit\u00e4tenkorrektur [Principles of deformity correction around the knee]","volume":"29","author":"Paley D","year":"2000","journal-title":"Orthopade"},{"key":"e_1_2_12_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167\u2010022\u201007181\u20102"},{"key":"e_1_2_12_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167\u2010022\u201007155\u20104"},{"key":"e_1_2_12_20_1","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.2020200198"},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167\u2010012\u20102114\u20103"},{"key":"e_1_2_12_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00167\u2010022\u201007037\u20109"},{"key":"e_1_2_12_23_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746\u2010023\u201000829\u20104"},{"key":"e_1_2_12_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00256\u2010021\u201003948\u20109"},{"key":"e_1_2_12_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00256\u2010021\u201003844\u20102"},{"key":"e_1_2_12_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcot.2016.05.010"}],"container-title":["Knee Surgery, Sports 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Arthroscopy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/esskajournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1007\/s00167-023-07644-0","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00167-023-07644-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/esskajournals.onlinelibrary.wiley.com\/doi\/full-xml\/10.1007\/s00167-023-07644-0","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00167-023-07644-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/esskajournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1007\/s00167-023-07644-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T14:37:50Z","timestamp":1786113470000},"score":1,"resource":{"primary":{"URL":"https:\/\/esskajournals.onlinelibrary.wiley.com\/doi\/10.1007\/s00167-023-07644-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,17]]},"references-count":25,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["10.1007\/s00167-023-07644-0"],"URL":"https:\/\/doi.org\/10.1007\/s00167-023-07644-0","archive":["Portico"],"relation":{},"ISSN":["0942-2056","1433-7347"],"issn-type":[{"value":"0942-2056","type":"print"},{"value":"1433-7347","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,17]]},"assertion":[{"value":"27 July 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 October 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"CSa and AH are employees of ImageBiopsy Lab. SN is member of the medical advisory board for ImageBiopsy Lab. PA is a consultant for Arthrex and Aesculap. All other authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This research was funded by the Gesellschaft f\u00fcr Forschungsf\u00f6rderung Nieder\u00f6sterreich m.b.H. (GFF), grant number LS20-020.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Lower Austria, Austria (GS1-EK-3\/171-2020).","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Patient consent was waived due to the retrospective image acquisition and anonymization of the data.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}