{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T08:10:09Z","timestamp":1788768609243,"version":"build-2803163510"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["World j. otorhinolaryngol.-head neck surg."],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To develop a multi\u2010sequence fusion model based on MRI images to differentiate between recurrent nasopharyngeal carcinoma (rNPC) and osteoradionecrosis (ORN) in patients with nasopharyngeal carcinoma (NPC) after radiotherapy, and to evaluate its diagnostic performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We retrospectively reviewed 370 patients with pathologically confirmed recurrent nasopharyngeal carcinoma (rNPC) or osteoradionecrosis (ORN). After screening, 346 patients (207 rNPC and 139 ORN) with both axial T1\u2010weighted contrast\u2010enhanced imaging (T1C) and T2\u2010weighted imaging (T2WI) were included and randomly split into a training set (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009212), validation set (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200961), and test set (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200973). A dual\u2010branch 3D\u2010ResNet\u201050\u2010based fusion model was developed to integrate multi\u2010sequence MRI features. Model performance was evaluated using AUC, accuracy, sensitivity, specificity, precision, and F1 score.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      On the test set, the proposed 3D\u2010ResNet\u2010Fusion model achieved an AUC of 0.86 and an accuracy of 84%, with a sensitivity of 91%, specificity of 72%, precision of 83%, and an F1 score of 0.87. Based on AUC comparisons, the fusion model outperformed comparator models based on EfficientNet (0.77,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.20) and DenseNet (0.70,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.02), as well as single\u2010sequence 3D\u2010ResNet models trained on T1C alone (0.71,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.02) or T2WI alone (0.73,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.046). In the human\u2013AI comparison experiment, the proposed AI model achieved a 3% higher ACC than the senior otolaryngologist (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.83), and outperformed the two junior otolaryngologists by 15% (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.05) and 22% (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01), respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed AI model effectively integrates information from multiple MRI sequences, significantly improving classification performance in distinguishing rNPC from ORN.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/wjo2.70165","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T07:46:58Z","timestamp":1788767218000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi\u2010Sequence Fusion MRI Deep Learning Models for Discrimination of Recurrent Nasopharyngeal Carcinoma and Osteoradionecrosis"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1263-8513","authenticated-orcid":false,"given":"Wen\u2010Tao","family":"Gong","sequence":"first","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"},{"name":"School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6237-2147","authenticated-orcid":false,"given":"Xue\u2010Li","family":"Liu","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Chen","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Li","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming\u2010Yan","family":"Qiu","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shang","family":"Shi","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"},{"name":"School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5435-978X","authenticated-orcid":false,"given":"Xuan\u2010Yu","family":"Zhao","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quan","family":"Liu","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1423-0942","authenticated-orcid":false,"given":"Xi\u2010Cai","family":"Sun","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu\u2010Xuan","family":"Shi","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong\u2010Meng","family":"Yu","sequence":"additional","affiliation":[{"name":"ENT Institute and Department of Otolaryngology, Eye &amp; ENT Hospital Fudan University Shanghai China"},{"name":"Research Units of New Technologies of Endoscopic Surgery in Skull Base Tumor (2018RU003), Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(19)30956-0"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21492"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40880-016-0167-2"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2015.08.006"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.4193\/Rhin22.303"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2018.06.027"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40880-016-0124-0"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/14737140.2024.2433265"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bjorl.2023.101366"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/cac2.12159"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.767134"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2013.06.003"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2023.102202"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-020-00502-2"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ctrv.2019.101890"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr\/60136051"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-005-0054-6"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12093077"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102973"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers15184443"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014-022-02121-3"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-022-09289-y"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2021.103631"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj-2023-078378"},{"key":"e_1_2_10_26_1","doi-asserted-by":"crossref","unstructured":"K.He X.Zhang S.Ren andJ.Sun \u201cDeep Residual Learning for Image Recognition \u201d in2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(2016) 770\u2013778 https:\/\/doi.org\/10.1109\/CVPR.2016.90.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_10_27_1","doi-asserted-by":"crossref","unstructured":"G.Huang Z.Liu L.Van Der Maaten andK. Q.Weinberger \u201cDensely Connected Convolutional Networks \u201d in2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(2017) 2261\u20132269 https:\/\/doi.org\/10.1109\/CVPR.2017.243.","DOI":"10.1109\/CVPR.2017.243"},{"key":"e_1_2_10_28_1","unstructured":"M.TanandQ.Le \u201cEfficientNet: Rethinking Model Scaling for Convolutional Neural Networks \u201d 2019 https:\/\/mlanthology.org\/icml\/2019\/tan2019icml-efficientnet\/."},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014-022-01980-0"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.3389\/fsurg.2021.713926"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-020-07451-y"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.21037\/qims-22-1226"}],"container-title":["World Journal of Otorhinolaryngology - Head and Neck Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/wjo2.70165","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/wjo2.70165","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/wjo2.70165","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T07:47:01Z","timestamp":1788767221000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/wjo2.70165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,7]]},"references-count":31,"alternative-id":["10.1002\/wjo2.70165"],"URL":"https:\/\/doi.org\/10.1002\/wjo2.70165","archive":["Portico"],"relation":{},"ISSN":["2095-8811","2589-1081"],"issn-type":[{"value":"2095-8811","type":"print"},{"value":"2589-1081","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,7]]},"assertion":[{"value":"2025-09-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"wjo2.70165"}}