Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects.
Field | Value | Language |
dc.contributor.author | Lombardo, Elia | |
dc.contributor.author | Dhont, Jennifer | |
dc.contributor.author | Page, Denis | |
dc.contributor.author | Garibaldi, Cristina | |
dc.contributor.author | Kunzel, Luise | |
dc.contributor.author | Hurkmans, Coen | |
dc.contributor.author | Tijssen, Rob | |
dc.contributor.author | Paganelli, Chiara | |
dc.contributor.author | Liu, Paul | |
dc.contributor.author | Keall, Paul | |
dc.contributor.author | Riboldi, M | |
dc.contributor.author | Kurz, Christopher | |
dc.contributor.author | Landry, Guillaume | |
dc.contributor.author | Cusumano, Davide | |
dc.contributor.author | Fusella, Marco | |
dc.contributor.author | Placidi, Lorenzo | |
dc.date.accessioned | 2024-09-20T02:44:31Z | |
dc.date.available | 2024-09-20T02:44:31Z | |
dc.date.issued | 2024 | en_AU |
dc.identifier.uri | https://hdl.handle.net/2123/33099 | |
dc.description.abstract | MRI-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.iso | en | en_AU |
dc.publisher | Elsevier | en_AU |
dc.relation.ispartof | Radiotherapy and Oncology | en_AU |
dc.rights | Creative Commons Attribution 4.0 | en_AU |
dc.subject | MRI | en_AU |
dc.subject | radiation therapy | en_AU |
dc.title | Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects. | en_AU |
dc.type | Article | en_AU |
dc.subject.asrc | ANZSRC FoR code::32 BIOMEDICAL AND CLINICAL SCIENCES::3211 Oncology and carcinogenesis::321110 Radiation therapy | en_AU |
dc.identifier.doi | 10.1016/j.radonc.2023.109970 | |
dc.type.pubtype | Author accepted manuscript | en_AU |
dc.relation.nhmrc | 1194004 | |
usyd.faculty | SeS faculties schools::Faculty of Medicine and Health | en_AU |
usyd.department | Image X Institute | en_AU |
usyd.citation.volume | 190 | en_AU |
usyd.citation.spage | 109970 | en_AU |
workflow.metadata.only | No | en_AU |
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