{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T15:28:15Z","timestamp":1791300495574,"version":"4.1.0"},"reference-count":37,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T00:00:00Z","timestamp":1707264000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal Orthopaedic Research"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In this study, we investigated the discriminative capacity of knee morphology in automatic detection of osteophytes defined by the Osteoarthritis Research Society International atlas, using X\u2010ray and magnetic resonance imaging (MRI) data. For the X\u2010ray analysis, we developed a deep learning (DL) based model to segment femur and tibia. In case of MRIs, we utilized previously validated segmentations of femur, tibia, corresponding cartilage tissues, and menisci. Osteophyte detection was performed using DL models in four compartments: medial femur (FM), lateral femur (FL), medial tibia (TM), and lateral tibia (TL). To analyze the confounding effects of soft tissues, we investigated their morphology in combination with bones, including bones+cartilage, bones+menisci, and all the tissues. From X\u2010ray\u2010based 2D morphology, the models yielded balanced accuracy of 0.73, 0.69, 0.74, and 0.74 for FM, FL, TM, TL, respectively. Using 3D bone morphology from MRI, balanced accuracy was 0.80, 0.77, 0.71, and 0.76, respectively. The performance was higher than in 2D for all the compartments except for TM, with significant improvements observed for femoral compartments. Adding menisci or cartilage morphology consistently improved balanced accuracy in TM, with the greatest improvement seen for small osteophyte. Otherwise, the models performed similarly to bones\u2010only. Our experiments demonstrated that MRI\u2010based models show higher detection capability than X\u2010ray based models for identifying knee osteophytes. This study highlighted the feasibility of automated osteophyte detection from X\u2010ray and MRI data and suggested further need for development of osteophyte assessment criteria in addition to OARSI, particularly, for early osteophytic changes.<\/jats:p>","DOI":"10.1002\/jor.25800","type":"journal-article","created":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T08:59:04Z","timestamp":1707296344000},"page":"1473-1481","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Deep learning based detection of osteophytes in radiographs and magnetic resonance imagings of the knee using 2D and 3D morphology"],"prefix":"10.1002","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7431-190X","authenticated-orcid":false,"given":"Mitra","family":"Daneshmand","sequence":"first","affiliation":[{"name":"Faculty of Medicine University of Oulu Oulu Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2500-6375","authenticated-orcid":false,"given":"Egor","family":"Panfilov","sequence":"additional","affiliation":[{"name":"Faculty of Medicine University of Oulu Oulu Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neslihan","family":"Bayramoglu","sequence":"additional","affiliation":[{"name":"Faculty of Medicine University of Oulu Oulu Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rami K.","family":"Korhonen","sequence":"additional","affiliation":[{"name":"University of Eastern Finland Kuopio Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2850-5484","authenticated-orcid":false,"given":"Simo","family":"Saarakkala","sequence":"additional","affiliation":[{"name":"University of Oulu and Oulu University Hospital Oulu Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,2,7]]},"reference":[{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMcp051726"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/art.1780290816"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1136\/ard.16.4.494"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13075-022-02905-8"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/10717544.2018.1482971"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/19476035221077403"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep44470"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1063-4584(97)80002-7"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13075-018-1734-5"},{"key":"e_1_2_8_12_1","first-page":"3","article-title":"Atlas of individual radio\u2010 graphic features in osteoarthritis","volume":"3","author":"Altman RD","year":"1995","journal-title":"Osteoarthr Cartil"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2011.05.004"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2014.11.026"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2022.02.360"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2013.10.007"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep22365"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1177\/2325967120927481"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2015.03.003"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1093\/rheumatology\/39.11.1218"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47157-0_6"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-62416-7_27"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10110932"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joca.2022.02.378"},{"key":"e_1_2_8_25_1","first-page":"3","article-title":"Automatic segmentation of hip osteophytes in DXA scans using U\u2010Nets","volume":"13435","author":"Ebsim R","year":"2022","journal-title":"MICCAI"},{"key":"e_1_2_8_26_1","unstructured":"Osteoarthritis Initiative.2016. Central reading of knee X\u2010rays for Kellgren and Lawrence grade and individual radiographic features of tibiofemoral knee OA. 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