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dc.contributor.authorLombardo, Elia
dc.contributor.authorDhont, Jennifer
dc.contributor.authorPage, Denis
dc.contributor.authorGaribaldi, Cristina
dc.contributor.authorKunzel, Luise
dc.contributor.authorHurkmans, Coen
dc.contributor.authorTijssen, Rob
dc.contributor.authorPaganelli, Chiara
dc.contributor.authorLiu, Paul
dc.contributor.authorKeall, Paul
dc.contributor.authorRiboldi, M
dc.contributor.authorKurz, Christopher
dc.contributor.authorLandry, Guillaume
dc.contributor.authorCusumano, Davide
dc.contributor.authorFusella, Marco
dc.contributor.authorPlacidi, Lorenzo
dc.date.accessioned2024-09-20T02:44:31Z
dc.date.available2024-09-20T02:44:31Z
dc.date.issued2024en_AU
dc.identifier.urihttps://hdl.handle.net/2123/33099
dc.description.abstractMRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.en_AU
dc.language.isoenen_AU
dc.publisherElsevieren_AU
dc.relation.ispartofRadiotherapy and Oncologyen_AU
dc.rightsCreative Commons Attribution 4.0en_AU
dc.subjectMRIen_AU
dc.subjectradiation therapyen_AU
dc.titleReal-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects.en_AU
dc.typeArticleen_AU
dc.subject.asrcANZSRC FoR code::32 BIOMEDICAL AND CLINICAL SCIENCES::3211 Oncology and carcinogenesis::321110 Radiation therapyen_AU
dc.identifier.doi10.1016/j.radonc.2023.109970
dc.type.pubtypeAuthor accepted manuscripten_AU
dc.relation.nhmrc1194004
usyd.facultySeS faculties schools::Faculty of Medicine and Healthen_AU
usyd.departmentImage X Instituteen_AU
usyd.citation.volume190en_AU
usyd.citation.spage109970en_AU
workflow.metadata.onlyNoen_AU


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