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dc.contributor.authorEnderling, Heiko
dc.contributor.authorAlfonso, Juan Carlos López
dc.contributor.authorMoros, Eduardo
dc.contributor.authorCaudell, Jimmy J.
dc.contributor.authorHarrison, Louis B.
dc.creatorEnderling, H.
dc.date.accessioned2019-08-27T09:13:23Z
dc.date.available2019-08-27T09:13:23Z
dc.date.issued2019-08-01
dc.identifier.issn24058033
dc.identifier.doi10.1016/j.trecan.2019.06.006
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068509350&origin=inward
dc.identifier.urihttp://hdl.handle.net/10033/621920
dc.description.abstractIn current radiation oncology practice, treatment protocols are prescribed based on the average outcomes of large clinical trials, with limited personalization and without adaptations of dose or dose fractionation to individual patients based on their individual clinical responses. Predicting tumor responses to radiation and comparing predictions against observed responses offers an opportunity for novel treatment evaluation. These analyses can lead to protocol adaptation aimed at the improvement of patient outcomes with better therapeutic ratios. We foresee the integration of mathematical models into radiation oncology to simulate individual patient tumor growth and predict treatment response as dynamic biomarkers for personalized adaptive radiation therapy (RT).en_US
dc.language.isoenen_US
dc.publisherElsevier(Cell Press)en_US
dc.relation.ispartofTrends in Cancer
dc.relation.ispartofseries8en_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectadaptive therapyen_US
dc.subjectmathematical oncologyen_US
dc.subjectradiationen_US
dc.subjectradiotherapyen_US
dc.subjectsystems medicineen_US
dc.titleIntegrating Mathematical Modeling into the Roadmap for Personalized Adaptive Radiation Therapyen_US
dc.typeArticleen_US
dc.contributor.departmentBRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.en_US
dc.identifier.journalTrends in Canceren_US
dc.identifier.eid2-s2.0-85068509350
dc.identifier.eid2-s2.0-85059309527
dc.identifier.scopusidSCOPUS_ID:85068509350
dc.identifier.piiS2405803319301256
dc.relation.volume5


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