{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T21:11:19Z","timestamp":1790111479818,"version":"4.0.1"},"reference-count":45,"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":[[2026,7,15]],"date-time":"2026-07-15T00:00:00Z","timestamp":1784073600000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013795","name":"Fujian Medical University","doi-asserted-by":"publisher","award":["2023QH1346"],"award-info":[{"award-number":["2023QH1346"]}],"id":[{"id":"10.13039\/501100013795","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Fujian Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2024J011556"],"award-info":[{"award-number":["2024J011556"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.acra.2026.07.015","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T20:26:30Z","timestamp":1785529590000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Response to Radiotherapy in Locally Advanced Cervical Squamous Cell Carcinoma Based on Multisequence MRI and Clinical Variables"],"prefix":"10.1016","author":[{"given":"Yanhong","family":"Zhuo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youjia","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yimin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongmei","family":"Ke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Furong","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiyu","family":"Zhuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunnuan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-0996-0266","authenticated-orcid":false,"given":"Yuanfu","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.acra.2026.07.015_bib1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Freddie","year":"2024","journal-title":"CA Cancer J Clin"},{"issue":"12","key":"10.1016\/j.acra.2026.07.015_bib2","doi-asserted-by":"crossref","first-page":"1531","DOI":"10.1136\/ijgc-2022-003801","article-title":"Proportions and incidence of locally advanced cervical cancer: a global systematic literature review","volume":"32","author":"Monk","year":"2022","journal-title":"Int J Gynecol Cancer"},{"issue":"12","key":"10.1016\/j.acra.2026.07.015_bib3","doi-asserted-by":"crossref","first-page":"2913","DOI":"10.3390\/cancers14122913","article-title":"Review of the standard and advanced screening, staging systems and treatment modalities for cervical cancer","volume":"14","author":"Boon","year":"2022","journal-title":"Cancers"},{"issue":"15","key":"10.1016\/j.acra.2026.07.015_bib4","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1056\/NEJM199904153401502","article-title":"Concurrent cisplatin-based radiotherapy and chemotherapy for locally advanced cervical cancer","volume":"340","author":"Rose","year":"1999","journal-title":"N Engl J Med"},{"issue":"4","key":"10.1016\/j.acra.2026.07.015_bib5","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/S1470-2045(20)30753-1","article-title":"MRI-guided adaptive brachytherapy in locally advanced cervical cancer (EMBRACE-I): a multicentre prospective cohort study","volume":"22","author":"P\u00f6tter","year":"2021","journal-title":"Lancet Oncol"},{"issue":"10434","key":"10.1016\/j.acra.2026.07.015_bib6","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1016\/S0140-6736(24)00317-9","article-title":"Pembrolizumab or placebo with chemoradiotherapy followed by pembrolizumab or placebo for newly diagnosed, high-risk, locally advanced cervical cancer (ENGOT-cx11\/GOG-3047\/KEYNOTE-A18): a randomised, double-blind, phase 3 clinical trial","volume":"403","author":"Lorusso","year":"2024","journal-title":"The Lancet"},{"issue":"10463","key":"10.1016\/j.acra.2026.07.015_bib7","doi-asserted-by":"crossref","first-page":"1668","DOI":"10.1016\/S0140-6736(24)02135-4","article-title":"Cadonilimab plus platinum-based chemotherapy with or without bevacizumab as first-line treatment for persistent, recurrent, or metastatic cervical cancer (COMPASSION-16): a randomised, double-blind, placebo-controlled phase 3 trial in China","volume":"404","author":"Wu","year":"2024","journal-title":"The Lancet"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib8","article-title":"Prognostic analysis of nimotuzumab combined with concurrent chemoradiotherapy for locally advanced cervical cancer: a multicenter real-world study","volume":"15","author":"Li","year":"2025","journal-title":"Sci Rep"},{"issue":"10462","key":"10.1016\/j.acra.2026.07.015_bib9","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1016\/S0140-6736(24)01438-7","article-title":"Induction chemotherapy followed by standard chemoradiotherapy versus standard chemoradiotherapy alone in patients with locally advanced cervical cancer (GCIG INTERLACE): an international, multicentre, randomised phase 3 trial","volume":"404","author":"McCormack","year":"2024","journal-title":"Lancet Lond Engl"},{"issue":"3","key":"10.1016\/j.acra.2026.07.015_bib10","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1016\/j.ygyno.2020.03.027","article-title":"FIGO 2018 staging criteria for cervical cancer: Impact on stage migration and survival","volume":"157","author":"Grigsby","year":"2020","journal-title":"Gynecol Oncol"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib11","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1097\/AOG.0000000000003311","article-title":"Prognostic performance of the 2018 International Federation of Gynecology and Obstetrics Cervical Cancer Staging Guidelines","volume":"134","author":"Wright","year":"2019","journal-title":"Obstet Gynecol"},{"issue":"9","key":"10.1016\/j.acra.2026.07.015_bib12","doi-asserted-by":"crossref","first-page":"5999","DOI":"10.1007\/s00432-022-04558-1","article-title":"Establishment of a risk stratification model based on the combination of post-treatment serum squamous cell carcinoma antigen levels and FIGO stage of cervical cancer for treatment and surveillance decision-making","volume":"149","author":"Shi","year":"2023","journal-title":"J Cancer Res Clin Oncol"},{"issue":"6","key":"10.1016\/j.acra.2026.07.015_bib13","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1007\/s11912-013-0344-2","article-title":"Functional imaging to predict tumor response in locally advanced cervical cancer","volume":"15","author":"Barwick","year":"2013","journal-title":"Curr Oncol Rep"},{"issue":"3","key":"10.1016\/j.acra.2026.07.015_bib14","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1016\/j.acra.2022.08.002","article-title":"Nomograms combining clinical and imaging parameters to predict recurrence and disease-free survival after concurrent chemoradiotherapy in patients with locally advanced cervical cancer","volume":"30","author":"Zhang","year":"2023","journal-title":"Acad Radiol"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib15","doi-asserted-by":"crossref","DOI":"10.1148\/rycan.2021209038","article-title":"Multiparameter MRI and clinical factors for predicting early response to chemoradiotherapy in cervical cancer","volume":"3","author":"Javadi","year":"2021","journal-title":"Radiol Imaging Cancer"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib16","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1007\/s00261-022-03665-4","article-title":"MRI-based radiomics for pretreatment prediction of response to concurrent chemoradiotherapy in locally advanced cervical squamous cell cancer","volume":"48","author":"Zhang","year":"2023","journal-title":"Abdom Radiol N Y."},{"issue":"1108","key":"10.1016\/j.acra.2026.07.015_bib17","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20190948","article-title":"Radiomics: from qualitative to quantitative imaging","volume":"93","author":"Rogers","year":"2020","journal-title":"Br J Radiol"},{"issue":"9","key":"10.1016\/j.acra.2026.07.015_bib18","doi-asserted-by":"crossref","first-page":"3753","DOI":"10.1007\/s11263-024-02032-8","article-title":"Multimodal machine learning in image-based and clinical biomedicine: survey and prospects","volume":"132","author":"Warner","year":"2024","journal-title":"Int J Comput Vis"},{"issue":"4","key":"10.1016\/j.acra.2026.07.015_bib19","first-page":"631","article-title":"Pretreatment MRI radiomics based response prediction model in locally advanced cervical cancer","volume":"11","author":"Gui","year":"2021","journal-title":"Diagn Basel Switz"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib20","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s40644-022-00474-2","article-title":"MRI-based radiomics value for predicting the survival of patients with locally advanced cervical squamous cell cancer treated with concurrent chemoradiotherapy","volume":"22","author":"Zhang","year":"2022","journal-title":"Cancer Imaging"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib21","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1186\/s13014-024-02574-8","article-title":"Longitudinal dynamic MRI radiomic models for early prediction of prognosis in locally advanced cervical cancer treated with concurrent chemoradiotherapy","volume":"19","author":"Cai","year":"2024","journal-title":"Radiat Oncol"},{"key":"10.1016\/j.acra.2026.07.015_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108593","article-title":"Machine learning-based radiomics for predicting outcomes in cervical cancer patients undergoing concurrent chemoradiotherapy","volume":"177","author":"Xin","year":"2024","journal-title":"Comput Biol Med"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib23","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1038\/s41746-025-01903-9","article-title":"Multimodal deep learning model for prognostic prediction in cervical cancer receiving definitive radiotherapy: a multi-center study","volume":"8","author":"Wang","year":"2025","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.acra.2026.07.015_bib24","article-title":"Deep learning with radiomics for disease diagnosis and treatment: challenges and potential","volume":"12","author":"Zhang","year":"2022","journal-title":"Front Oncol"},{"key":"10.1016\/j.acra.2026.07.015_bib25","article-title":"The prognostic value of tumor size, volume and tumor volume reduction rate during concurrent chemoradiotherapy in patients with cervical cancer","volume":"12","author":"Sun","year":"2022","journal-title":"Front Oncol"},{"issue":"3","key":"10.1016\/j.acra.2026.07.015_bib26","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1136\/ijgc-2018-000168","article-title":"Magnetic resonance imaging after external beam radiotherapy and concurrent chemotherapy for locally advanced cervical cancer helps to identify patients at risk of recurrence","volume":"29","author":"Angeles","year":"2019","journal-title":"Int J Gynecol Cancer"},{"key":"10.1016\/j.acra.2026.07.015_bib27","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2024.1366777","article-title":"The prognostic effect of tumor volume, reduction ratio, and cumulative doses on external beam radiotherapy with central-shielding method and image-guided adaptive brachytherapy for cervical cancer","volume":"14","author":"Ohtaka","year":"2024","journal-title":"Front Oncol"},{"issue":"11","key":"10.1016\/j.acra.2026.07.015_bib28","doi-asserted-by":"crossref","DOI":"10.3390\/jcm9113471","article-title":"Prognostic significance of tumor regression rate during concurrent chemoradiotherapy in locally advanced cervix cancer: analysis by radiation phase and histologic type","volume":"9","author":"Kang","year":"2020","journal-title":"J Clin Med"},{"issue":"6","key":"10.1016\/j.acra.2026.07.015_bib29","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1136\/ijgc-2024-005336","article-title":"RECIST 1.1 versus clinico-radiological response assessment for locally advanced cervical cancer: implications on interpreting survival outcomes of future trials","volume":"34","author":"Charnalia","year":"2024","journal-title":"Int J Gynecol Cancer Off J Int Gynecol Cancer Soc"},{"issue":"7","key":"10.1016\/j.acra.2026.07.015_bib30","article-title":"Progression-free survival 2: Is it ready for prime time?","volume":"128","author":"Ben","year":"2022","journal-title":"Cancer"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib31","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1186\/s13014-025-02623-w","article-title":"Prognostic implications of tumor volume reduction during radiotherapy in locally advanced cervical cancer: a risk-stratified analysis","volume":"20","author":"Lin","year":"2025","journal-title":"Radiat Oncol"},{"issue":"2","key":"10.1016\/j.acra.2026.07.015_bib32","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.ijrobp.2018.06.014","article-title":"Tumor shrinkage during chemoradiation in locally advanced cervical cancer patients: prognostic significance, and impact for image-guided adaptive brachytherapy","volume":"102","author":"Schernberg","year":"2018","journal-title":"Int J Radiat Oncol Biol Phys"},{"issue":"18","key":"10.1016\/j.acra.2026.07.015_bib33","doi-asserted-by":"crossref","DOI":"10.1002\/cam4.71251","article-title":"Early tumor shrinkage and depth of response as predictive markers of treatment response and prognosis in solid tumors","volume":"14","author":"Cao","year":"2025","journal-title":"Cancer Med"},{"issue":"8","key":"10.1016\/j.acra.2026.07.015_bib34","doi-asserted-by":"crossref","first-page":"5408","DOI":"10.21037\/qims-24-560","article-title":"Integrating a deep neural network and transformer architecture for the automatic segmentation and survival prediction in cervical cancer","volume":"14","author":"Zhu","year":"2024","journal-title":"Quant Imaging Med Surg"},{"key":"10.1016\/j.acra.2026.07.015_bib35","series-title":"Cervical cancer (Version 4.2025)","author":"National Comprehensive Cancer Network","year":"2025"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib36","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1007\/s00330-021-08066-7","article-title":"Correction to: staging, recurrence and follow-up of uterine cervical cancer using MRI: updated guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018","volume":"32","author":"Manganaro","year":"2022","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2026.07.015_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.clon.2024.103702","article-title":"Progression-free survival prediction for locally advanced cervical cancer after chemoradiotherapy with MRI-based radiomics","volume":"38","author":"Tang","year":"2025","journal-title":"Clin Oncol"},{"issue":"11","key":"10.1016\/j.acra.2026.07.015_bib38","doi-asserted-by":"crossref","first-page":"4372","DOI":"10.1016\/j.acra.2024.05.003","article-title":"Construction and validation of a MRI\u2011based radiomic nomogram to predict overall survival in patients with local advanced cervical cancer: a multicenter study","volume":"31","author":"Lin","year":"2024","journal-title":"Acad Radiol"},{"key":"10.1016\/j.acra.2026.07.015_bib39","article-title":"Recurrence risk stratification for locally advanced cervical cancer using multi-modality transformer network","volume":"13","author":"Wang","year":"2023","journal-title":"Front Oncol"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib40","article-title":"Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy","volume":"13","author":"Wu","year":"2023","journal-title":"Sci Rep"},{"issue":"11","key":"10.1016\/j.acra.2026.07.015_bib41","doi-asserted-by":"crossref","first-page":"5328","DOI":"10.1097\/MS9.0000000000001288","article-title":"Patient survival prediction in locally advanced cervical squamous cell carcinoma using MRI-based radiomics: retrospective cohort study","volume":"85","author":"Bseiso","year":"2023","journal-title":"Ann Med Surg"},{"key":"10.1016\/j.acra.2026.07.015_bib42","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1038\/s41598-024-51742-z","article-title":"Comparing deep learning and handcrafted radiomics to predict chemoradiotherapy response for locally advanced cervical cancer using pretreatment MRI","volume":"14","author":"Jeong","year":"2024","journal-title":"Sci Rep"},{"issue":"17","key":"10.1016\/j.acra.2026.07.015_bib43","doi-asserted-by":"crossref","DOI":"10.1002\/hbm.26783","article-title":"A multimodal vision transformer for interpretable fusion of functional and structural neuroimaging data","volume":"45","author":"Bi","year":"2024","journal-title":"Hum Brain Mapp"},{"issue":"1","key":"10.1016\/j.acra.2026.07.015_bib44","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/s13244-024-01618-7","article-title":"Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study","volume":"15","author":"Qin","year":"2024","journal-title":"Insights Imaging"},{"issue":"11","key":"10.1016\/j.acra.2026.07.015_bib45","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1016\/S2213-2600(18)30425-9","article-title":"Medicine. Opening the black box of machine learning","volume":"6","author":"Lancet Respiratory","year":"2018","journal-title":"Lancet Respir Med"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226005258?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633226005258?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T20:48:32Z","timestamp":1790110112000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633226005258"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":45,"alternative-id":["S1076633226005258"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2026.07.015","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting Response to Radiotherapy in Locally Advanced Cervical Squamous Cell Carcinoma Based on Multisequence MRI and Clinical Variables","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2026.07.015","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Association of Academic Radiology. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}