{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T22:34:55Z","timestamp":1792794895507,"version":"4.5.0"},"reference-count":51,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["esskajournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Knee surg. sports traumatol. arthrosc."],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:label\/><jats:p>The potential of Artificial intelligence (AI) is increasingly recognized in musculoskeletal radiology, offering solutions to challenges posed by increasing imaging volumes and fellowship trained radiologist shortages. The integration of AI is not intended to replace radiologists but to augment their capabilities, improving workflow efficiency and diagnostic accuracy. This narrative review examines the current landscape of AI applications in musculoskeletal imaging, focusing on both general\u2010purpose multimodal models and specialized foundation models. AI has proven effective in musculoskeletal imaging, enhancing fracture detection, scoliosis assessment, and lower limb alignment analysis. In osteoarthritis, AI aids early detection by identifying subtle structural changes. AI\u2010accelerated MRI reconstruction reduces scan times by up to 90% while maintaining diagnostic quality, improving efficiency and accessibility. Emerging multimodal models further integrate imaging with clinical data, advancing precision medicine. Technical challenges persist, particularly in addressing motion artifacts and anatomical complexity. Ethical considerations, including data privacy, algorithmic bias, and model transparency, remain crucial for responsible implementation. While challenges remain in clinical validation and implementation, the combination of broad and narrow  AI models shows promise in advancing precision medicine and democratizing quality care.<\/jats:p><\/jats:sec><jats:sec><jats:title>Level of Evidence<\/jats:title><jats:p>Level V.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ksa.12702","type":"journal-article","created":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T05:21:18Z","timestamp":1748755278000},"page":"3032-3038","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Artificial intelligence\u2010assisted analysis of musculoskeletal imaging\u2014A narrative review of the current state of machine learning models"],"prefix":"10.1002","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9721-685X","authenticated-orcid":false,"given":"Felix C.","family":"Oettl","sequence":"first","affiliation":[{"name":"Department of Orthopedic Surgery Balgrist University Hospital University of Z\u00fcrich Zurich Switzerland"},{"name":"Hospital for Special Surgery New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5697-6577","authenticated-orcid":false,"given":"B\u00e1lint","family":"Zsidai","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden"},{"name":"Sahlgrenska Sports Medicine Center G\u00f6teborg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4562-4373","authenticated-orcid":false,"given":"Jacob F.","family":"Oeding","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4014-424X","authenticated-orcid":false,"given":"Michael T.","family":"Hirschmann","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery and Traumatology Kantonsspital Baselland Bruderholz Switzerland"},{"name":"University of Basel Basel Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5179-4205","authenticated-orcid":false,"given":"Robert","family":"Feldt","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Fendrich","sequence":"additional","affiliation":[{"name":"Tenfifty Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2276-7814","authenticated-orcid":false,"given":"Matthew J.","family":"Kraeutler","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden"},{"name":"Department of Orthopaedic Surgery &amp; 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