{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T01:34:13Z","timestamp":1790300053077,"version":"4.1.0"},"reference-count":25,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["362575"],"award-info":[{"award-number":["362575"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002341","name":"Academy of Finland","doi-asserted-by":"publisher","award":["359186"],"award-info":[{"award-number":["359186"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Magnetic Resonance Fingerprinting (MRF) enables rapid quantitative parameter mapping from which synthetic clinical contrast images can be derived using deep learning (DL).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study evaluates the reliability and interchangeability of MRF\u2010derived synthetic knee MRI relative to conventional MRI in patients with osteoarthritis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Type<\/jats:title>\n                    <jats:p>Prospective single\u2010center comparative study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Subjects<\/jats:title>\n                    <jats:p>Between March 2022 and 2023, 78 participants (54 females, mean age 57.2, range 33\u201378\u2009years) with knee osteoarthritis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Field Strength\/Sequence<\/jats:title>\n                    <jats:p>3.0\u2009T; proton density weighted (PDw) imaging, T2\u2010weighted fat\u2010saturated (T2w fs) imaging, and MRF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Assessment<\/jats:title>\n                    <jats:p>U\u2010Nets were trained to produce synthetic contrasts from MRF data. Three musculoskeletal radiologists performed MRI OsteoArthritis Knee Score (MOAKS) assessments and image quality evaluation using a Likert scale (1\u20135).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Statistical Tests<\/jats:title>\n                    <jats:p>\n                      The inter\u2010rater and inter\u2010method reliability were evaluated using prevalence\u2010and\u2010bias\u2010adjusted kappa (PABAK), and percentages of exact matches. Image quality scores were compared using the Wilcoxon test. The limit of statistical significance was set at\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05 and no multiple comparisons corrections were applied.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The inter\u2010rater reliability for synthetic MR images varied between 0.980\u20130.994 (CI 0.975\u20130.997; exact matches 77.%\u201389.2%) and for conventional MR images between 0.979 and 0.994 (CI 0.973\u20130.997; exact matches 75.3%\u201389.5%). Inter\u2010method reliability between synthetic and conventional MR images was near\u2010perfect: mean PABAK\u2010values and exact matches were 0.927 and 77.9% for cartilage, 0.915 and 89.7% for bone marrow lesions, 0.922 and 65.2% for osteophytes, 0.950 and 72.9% for meniscus pathology, 0.934 and 66.6% for effusion, and 0.857 and 92.5% for Baker's cyst. Average Likert scores were significantly better for conventional than synthetic images: 4.5 vs. 3.9 for PDw and 4.1 vs. 3.2 for T2w fs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Conclusion<\/jats:title>\n                    <jats:p>MRF\u2010derived DL\u2010based synthetic clinical contrasts provide excellent inter\u2010rater reliability and interchangeability against conventional MR sequences in knee OA; however, image quality needs further development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evidence Level<\/jats:title>\n                    <jats:p>2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Stage of Technical Efficacy<\/jats:title>\n                    <jats:p>2.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.70300","type":"journal-article","created":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T05:04:23Z","timestamp":1774501463000},"page":"90-109","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Clinical Feasibility of Deep Learning Contrast Synthesis From\n                    <scp>MR<\/scp>\n                    Fingerprinting in Knee Osteoarthritis"],"prefix":"10.1002","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9483-7690","authenticated-orcid":false,"given":"Mika T.","family":"Nevalainen","sequence":"first","affiliation":[{"name":"Research Unit of Health Sciences and Technology, Faculty of Medicine University of Oulu  Oulu Finland"},{"name":"Medical Research Center Oulu Oulu University Hospital and University of Oulu  Oulu 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