Real-time motion management in MRI-guided radiotherapy: current status and AI-enabled prospects
Lombardo, E Dhont, J Page, Dennis Garibaldi, C Künzel, LA Hurkmans, C Tijssen, RHN Paganelli, C Liu, PZY Keall, PJ
Lombardo, E
Dhont, J
Page, Dennis
Garibaldi, C
Künzel, LA
Hurkmans, C
Tijssen, RHN
Paganelli, C
Liu, PZY
Keall, PJ
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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.
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Date
2023
Publisher
Collections
Keywords
Type
Article
Citation
Lombardo E, Dhont J, Page D, Garibaldi C, Künzel LA, Hurkmans C, et al. Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology. 2023 Oct 26;190:109970. PubMed PMID: 37898437. Epub 2023/10/29. eng.