{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T12:39:11Z","timestamp":1793104751727,"version":"4.5.0"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"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":[[2026,9]]},"DOI":"10.1016\/j.phro.2026.101074","type":"journal-article","created":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T14:59:07Z","timestamp":1788620347000},"page":"101074","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Computed tomography and magnetic resonance imaging radiomics for predicting non-complete response after chemoradiotherapy in unresectable locally advanced head and neck squamous cell carcinoma"],"prefix":"10.1016","volume":"41","author":[{"given":"Krittee","family":"Chesdachai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kullathorn","family":"Thephamongkhol","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anucha","family":"Chaichana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiraporn","family":"Setakornnukul","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.phro.2026.101074_bb0005","doi-asserted-by":"crossref","first-page":"224","DOI":"10.6004\/jnccn.2022.0016","article-title":"NCCN guidelines(R) insights: head and neck cancers, version 1.2022","volume":"20","author":"Caudell","year":"2022","journal-title":"J Natl Compr Cancer Netw"},{"key":"10.1016\/j.phro.2026.101074_bb0010","article-title":"Locally advanced head and neck squamous cell carcinoma treatment efficacy and safety: a systematic review and network meta-analysis","volume":"14","author":"Wang","year":"2023","journal-title":"Front Pharmacol"},{"key":"10.1016\/j.phro.2026.101074_bb0015","doi-asserted-by":"crossref","first-page":"1632","DOI":"10.1002\/hed.25586","article-title":"Failure patterns of head and neck squamous cell carcinoma treated with radical radiotherapy by intensity modulated radiotherapy technique using focal volume and dosimetric method","volume":"41","author":"Tandon","year":"2019","journal-title":"Head Neck"},{"key":"10.1016\/j.phro.2026.101074_bb0020","doi-asserted-by":"crossref","first-page":"51059","DOI":"10.18632\/oncotarget.10595","article-title":"Nomograms predicting long-term overall survival and cancer-specific survival in head and neck squamous cell carcinoma patients","volume":"7","author":"Ju","year":"2016","journal-title":"Oncotarget"},{"key":"10.1016\/j.phro.2026.101074_bb0025","doi-asserted-by":"crossref","first-page":"10117","DOI":"10.1038\/s41598-017-10371-5","article-title":"Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer","volume":"7","author":"Vallieres","year":"2017","journal-title":"Sci Rep"},{"key":"10.1016\/j.phro.2026.101074_bb0030","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.wjorl.2016.05.007","article-title":"Intra-tumor heterogeneity in head and neck cancer and its clinical implications","volume":"2","author":"Mroz","year":"2016","journal-title":"World J Otorhinolaryngol Head Neck Surg"},{"key":"10.1016\/j.phro.2026.101074_bb0035","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1002\/1097-0142(20010201)91:3<548::AID-CNCR1033>3.0.CO;2-A","article-title":"Predictors of response and survival after concurrent chemotherapy and radiation for locally advanced squamous cell carcinomas of the head and neck","volume":"91","author":"Suntharalingam","year":"2001","journal-title":"Cancer"},{"key":"10.1016\/j.phro.2026.101074_bb0040","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.clon.2019.12.004","article-title":"A review of modern radiation therapy dose escalation in locally advanced head and neck cancer","volume":"32","author":"Atwell","year":"2020","journal-title":"Clin Oncol (R Coll Radiol)"},{"key":"10.1016\/j.phro.2026.101074_bb0045","doi-asserted-by":"crossref","first-page":"371","DOI":"10.21037\/tcr.2016.07.18","article-title":"Radiomics in head and neck cancer: from exploration to application","volume":"5","author":"Wong","year":"2016","journal-title":"Transl Cancer Res"},{"key":"10.1016\/j.phro.2026.101074_bb0050","doi-asserted-by":"crossref","DOI":"10.3390\/cancers15041174","article-title":"Radiomics applications in head and neck tumor imaging: a narrative review","volume":"15","author":"Tortora","year":"2023","journal-title":"Cancers (Basel)"},{"key":"10.1016\/j.phro.2026.101074_bb0055","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.mric.2021.08.001","article-title":"Role of MR imaging in head and neck squamous cell carcinoma","volume":"30","author":"Abdel Razek","year":"2022","journal-title":"Magn Reson Imaging Clin N Am"},{"key":"10.1016\/j.phro.2026.101074_bb0060","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1186\/s13014-023-02326-0","article-title":"Impact of MRI on target volume definition in head and neck cancer patients","volume":"18","author":"Clasen","year":"2023","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.phro.2026.101074_bb0065","doi-asserted-by":"crossref","DOI":"10.3390\/jpm12071092","article-title":"Prediction of incomplete response of primary tumour based on clinical and radiomics features in inoperable head and neck cancers after definitive treatment","volume":"12","author":"Kazmierska","year":"2022","journal-title":"J Pers Med"},{"key":"10.1016\/j.phro.2026.101074_bb0070","doi-asserted-by":"crossref","first-page":"9451","DOI":"10.1038\/s41598-024-60009-6","article-title":"MRI radiomics in head and neck cancer from reproducibility to combined approaches","volume":"14","author":"Corti","year":"2024","journal-title":"Sci Rep"},{"key":"10.1016\/j.phro.2026.101074_bb0075","article-title":"Radiomics and the image biomarker standardisation initiative (IBSI): a narrative review using a six-question map and implementation framework for reproducible imaging biomarkers","volume":"17","author":"Aguirre-Meneses","year":"2025","journal-title":"Cureus"},{"key":"10.1016\/j.phro.2026.101074_bb0080","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.ejca.2008.10.026","article-title":"New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)","volume":"45","author":"Eisenhauer","year":"2009","journal-title":"Eur J Cancer"},{"key":"10.1016\/j.phro.2026.101074_bb0085","doi-asserted-by":"crossref","first-page":"1310","DOI":"10.1109\/TMI.2010.2046908","article-title":"N4ITK: improved N3 bias correction","volume":"29","author":"Tustison","year":"2010","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.phro.2026.101074_bb0090","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.2026.101074_bb0095","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J Artif Intell Res"},{"key":"10.1016\/j.phro.2026.101074_bb0100","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J R Stat Soc Ser B Stat Methodol"},{"key":"10.1016\/j.phro.2026.101074_bb0105","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene selection for cancer classification using support vector machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Mach Learn"},{"key":"10.1016\/j.phro.2026.101074_bb0110","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","article-title":"Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy","volume":"27","author":"Peng","year":"2005","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.phro.2026.101074_bb0115","series-title":"Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining","first-page":"785","article-title":"XGBoost: a scalable tree boosting system","author":"Chen","year":"2016"},{"key":"10.1016\/j.phro.2026.101074_bb0120","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1006\/jcss.1997.1504","article-title":"A decision-theoretic generalization of on-line learning and an application to boosting","volume":"55","author":"Freund","year":"1997","journal-title":"J Comput Syst Sci"},{"key":"10.1016\/j.phro.2026.101074_bb0125","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1002\/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3","article-title":"Index for rating diagnostic tests","volume":"3","author":"Youden","year":"1950","journal-title":"Cancer"},{"key":"10.1016\/j.phro.2026.101074_bb0130","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"10.1016\/j.phro.2026.101074_bb0135","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1177\/0272989X06295361","article-title":"Decision curve analysis: a novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med Decis Mak"},{"key":"10.1016\/j.phro.2026.101074_bb0140","series-title":"Advances in large-margin classifiers","first-page":"61","article-title":"Probabilities for SV machines","author":"Platt","year":"2000"},{"key":"10.1016\/j.phro.2026.101074_bb0145","first-page":"4765","article-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017","journal-title":"Adv Neural Inf Proces Syst"},{"key":"10.1016\/j.phro.2026.101074_bb0150","article-title":"RadiomiX for radiomics analysis: automated approaches to overcome challenges in replicability","volume":"15","author":"Kotler","year":"2025","journal-title":"Diagnostics (Basel)"},{"key":"10.1016\/j.phro.2026.101074_bb0155","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.radonc.2020.08.013","article-title":"Non-operative management for oral cavity carcinoma: definitive radiation therapy as a potential alternative treatment approach","volume":"154","author":"Hosni","year":"2021","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2026.101074_bb0160","doi-asserted-by":"crossref","DOI":"10.3390\/biomedicines13020417","article-title":"Prognostic factors and long-term outcome prediction in patients with hypopharyngeal carcinoma treated with (chemo)radiotherapy: development of a prognostic model","volume":"13","author":"Pala","year":"2025","journal-title":"Biomedicines"},{"key":"10.1016\/j.phro.2026.101074_bb0165","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1002\/lary.30279","article-title":"Outcomes for organ preservation with chemoradiation therapy for T4 larynx and hypopharynx cancer","volume":"133","author":"Eita","year":"2023","journal-title":"Laryngoscope"},{"key":"10.1016\/j.phro.2026.101074_bb0170","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.radonc.2016.11.008","volume":"121","author":"Linge","year":"2016","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2026.101074_bb0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.radonc.2023.109638","article-title":"Prognostic radiomic signature for head and neck cancer: development and validation on a multi-centric MRI dataset","volume":"183","author":"Bologna","year":"2023","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.phro.2026.101074_bb0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2024.105464","article-title":"Artificial intelligence-driven radiomics in head and neck cancer: current status and future prospects","volume":"188","author":"Alabi","year":"2024","journal-title":"Int J Med Inform"},{"key":"10.1016\/j.phro.2026.101074_bb0185","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics12112733","article-title":"Radiomics in head and neck cancer outcome predictions","volume":"12","author":"Gon\u00e7alves","year":"2022","journal-title":"Diagnostics"},{"key":"10.1016\/j.phro.2026.101074_bb0190","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1007\/s11547-023-01650-5","article-title":"Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma","volume":"128","author":"Teng","year":"2023","journal-title":"Radiol Med"}],"container-title":["Physics and Imaging in Radiation Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631626001740?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2405631626001740?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T12:29:32Z","timestamp":1793104172000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2405631626001740"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":38,"alternative-id":["S2405631626001740"],"URL":"https:\/\/doi.org\/10.1016\/j.phro.2026.101074","relation":{},"ISSN":["2405-6316"],"issn-type":[{"value":"2405-6316","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Computed tomography and magnetic resonance imaging radiomics for predicting non-complete response after chemoradiotherapy in unresectable locally advanced head and neck squamous cell carcinoma","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.2026.101074","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":"101074"}}