{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T04:13:46Z","timestamp":1788495226553,"version":"build-2803163510"},"reference-count":18,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","phiro.science","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Physics and Imaging in Radiation Oncology"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.phro.2026.101040","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T23:10:19Z","timestamp":1783984219000},"page":"101040","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Integrating computed tomography image features improves clinical prediction models for outcomes in nasopharyngeal carcinoma patients treated with (chemo)radiation"],"prefix":"10.1016","volume":"40","author":[{"given":"Guanzhi","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baoqiang","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingrui","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arjen","family":"van der Schaaf","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisanne V.","family":"van Dijk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes A.","family":"Langendijk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nanna M.","family":"Sijtsema","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.phro.2026.101040_bb0005","doi-asserted-by":"crossref","first-page":"4873","DOI":"10.1200\/JCO.2007.11.5501","article-title":"Prospective randomized study of intensity-modulated radiotherapy on salivary gland function in early-stage nasopharyngeal carcinoma patients","volume":"25","author":"Kam","year":"2007","journal-title":"J Clin Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0010","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1016\/j.ijrobp.2010.03.024","article-title":"How does intensity-modulated radiotherapy versus conventional two-dimensional radiotherapy influence the treatment results in nasopharyngeal carcinoma patients?","volume":"80","author":"Lai","year":"2011","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.phro.2026.101040_bb0015","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.radonc.2014.02.003","article-title":"Evolution of treatment for nasopharyngeal cancer \u2013 success and setback in the intensity-modulated radiotherapy era","volume":"110","author":"Lee","year":"2014","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0020","first-page":"93","article-title":"The eighth edition AJCC cancer staging manual: continuing to build a bridge from a population-based to a more \u201cpersonalized\u201d approach to cancer staging","volume":"67","author":"Amin","year":"2017","journal-title":"CA Cancer J Clin"},{"key":"10.1016\/j.phro.2026.101040_bb0025","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.21037\/tcr-22-1196","article-title":"Bioinformatics analysis based on ferroptosis-related lncRNAs: construction of a clinical prognostic model for nasopharyngeal carcinoma and correlation analysis","volume":"11","author":"Dai","year":"2022","journal-title":"Transl Cancer Res"},{"key":"10.1016\/j.phro.2026.101040_bb0030","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","article-title":"Radiomics: extracting more information from medical images using advanced feature analysis","volume":"48","author":"Lambin","year":"2012","journal-title":"Eur J Cancer"},{"key":"10.1016\/j.phro.2026.101040_bb0035","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.radonc.2017.07.013","article-title":"Improving the prediction of overall survival for head and neck cancer patients using image biomarkers in combination with clinical parameters","volume":"124","author":"Zhai","year":"2017","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0040","doi-asserted-by":"crossref","first-page":"6911","DOI":"10.2147\/CMAR.S325373","article-title":"CT-based radiomics nomogram for prediction of progression-free survival in locoregionally advanced nasopharyngeal carcinoma","volume":"13","author":"Yan","year":"2021","journal-title":"Cancer Manag Res"},{"key":"10.1016\/j.phro.2026.101040_bb0045","article-title":"A clinical-radiomics nomogram based on computed tomography for predicting risk of local recurrence after radiotherapy in nasopharyngeal carcinoma","volume":"11","author":"Zhu","year":"2021","journal-title":"Front Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0050","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2022.775248","article-title":"Tumor prognostic prediction of nasopharyngeal carcinoma using CT-based radiomics in non-Chinese patients","volume":"12","author":"Intarak","year":"2022","journal-title":"Front Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0055","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s00066-021-01874-2","article-title":"Computed tomography-based deep-learning prediction of induction chemotherapy treatment response in locally advanced nasopharyngeal carcinoma","volume":"198","author":"Yang","year":"2022","journal-title":"Strahlenther Onkol"},{"key":"10.1016\/j.phro.2026.101040_bb0060","doi-asserted-by":"crossref","DOI":"10.1186\/s12885-026-15570-w","article-title":"Prediction of treatment outcome in nasopharyngeal carcinoma patients","volume":"26","author":"Zhou","year":"2026","journal-title":"BMC Cancer"},{"key":"10.1016\/j.phro.2026.101040_bb0065","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"Van Griethuysen","year":"2017","journal-title":"Cancer Res"},{"key":"10.1016\/j.phro.2026.101040_bb0070","doi-asserted-by":"crossref","first-page":"4006","DOI":"10.1038\/ncomms5006","article-title":"Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach","volume":"5","author":"Aerts","year":"2014","journal-title":"Nat Commun"},{"key":"10.1016\/j.phro.2026.101040_bb0075","doi-asserted-by":"crossref","first-page":"100733","DOI":"10.1016\/j.phro.2025.100733","article-title":"The prognostic value of pathologic lymph node imaging using deep learning-based outcome prediction in oropharyngeal cancer patients","volume":"33","author":"Ma","year":"2025","journal-title":"Phys Imaging Radiat Oncol"},{"key":"10.1016\/j.phro.2026.101040_bb0080","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.neunet.2018.07.011","article-title":"A systematic study of the class imbalance problem in convolutional neural networks","volume":"106","author":"Buda","year":"2018","journal-title":"Neural Netw"},{"key":"10.1016\/j.phro.2026.101040_bb0085","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1146\/annurev-bioeng-071516-044442","article-title":"Deep learning in medical image analysis","volume":"19","author":"Shen","year":"2017","journal-title":"Annu Rev Biomed Eng"},{"key":"10.1016\/j.phro.2026.101040_bb0090","doi-asserted-by":"crossref","first-page":"1713","DOI":"10.1002\/ijc.31856","article-title":"The addition of pretreatment plasma Epstein\u2013Barr virus DNA into the eighth edition of nasopharyngeal cancer TNM stage classification","volume":"144","author":"Lee","year":"2019","journal-title":"Int J Cancer"}],"container-title":["Physics and Imaging in Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631626001405?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631626001405?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T03:30:33Z","timestamp":1788492633000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405631626001405"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":18,"alternative-id":["S2405631626001405"],"URL":"https:\/\/doi.org\/10.1016\/j.phro.2026.101040","relation":{},"ISSN":["2405-6316"],"issn-type":[{"value":"2405-6316","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Integrating computed tomography image features improves clinical prediction models for outcomes in nasopharyngeal carcinoma patients treated with (chemo)radiation","name":"articletitle","label":"Article Title"},{"value":"Physics and Imaging in Radiation Oncology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.phro.2026.101040","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.","name":"copyright","label":"Copyright"}],"article-number":"101040"}}