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The purpose of this study is to systematically synthesize the performance of delta\u2010radiomics\u2010based models for radiotherapy (RT)\u2010induced toxicity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A literature search was performed following the PRISMA guidelines. Systematic searches were performed in PubMed, Scopus, Cochrane and Embase databases in October 2022. Retrospective and prospective studies on the delta\u2010radiomics model for RT\u2010induced toxicity were included based on predefined PICOS criteria. A random\u2010effect meta\u2010analysis of AUC was performed on the performance of delta\u2010radiomics models, and a comparison with non\u2010delta radiomics models was included.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of the 563 articles retrieved, 13 selected studies of RT\u2010treated patients on different types of cancer (HNC\u2009=\u2009571, NPC\u2009=\u2009186, NSCLC\u2009=\u2009165, oesophagus\u2009=\u2009106, prostate\u2009=\u200933, OPC\u2009=\u200921) were eligible for inclusion in the systematic review. Included studies show that morphological and dosimetric features may improve the predictive model performance for the selected toxicity. Four studies that reported both delta and non\u2010delta radiomics features with AUC were included in the meta\u2010analysis. The AUC random effects estimate for delta and non\u2010delta radiomics models were 0.80 and 0.78 with heterogeneity, <jats:italic>I<\/jats:italic><jats:sup>2<\/jats:sup> of 73% and 27% respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Delta\u2010radiomics\u2010based models were found to be promising predictors of predefined end points. Future studies should consider using standardized methods and radiomics features and external validation to the reviewed delta\u2010radiomics model.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1754-9485.13546","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T08:49:49Z","timestamp":1686646189000},"page":"564-579","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Delta\u2010radiomics\u2010based models for toxicity prediction in radiotherapy: A systematic review and meta\u2010analysis"],"prefix":"10.1111","volume":"67","author":[{"given":"Daryl","family":"Tan","sequence":"first","affiliation":[{"name":"Faculty of Health Sciences Universiti Kebangsaan Malaysia  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siti Athiyah","family":"Mohamad Salleh","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences Universiti Kebangsaan Malaysia  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanani Abdul","family":"Manan","sequence":"additional","affiliation":[{"name":"Functional Image Processing Laboratory, Department of Radiology Universiti Kebangsaan Malaysia Medical Centre  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2736-6489","authenticated-orcid":false,"given":"Noorazrul","family":"Yahya","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences Universiti Kebangsaan Malaysia  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,6,13]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.7150\/ijms.3635"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.18632\/oncotarget.18409"},{"key":"e_1_2_9_4_1","unstructured":"Mohd RazifS SuhainaS NadzirahHZet\u00a0al.Insights into the knowledge attitude and practices of head and neck cancer survivors at otorhinolaryngology outpatient clinic of UKM Medical Center. 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