Real-time motion management in MRI-guided radiotherapy: current status and AI-enabled prospects
Authors
Lombardo, EDhont, J
Page, Dennis
Garibaldi, C
Künzel, LA
Hurkmans, C
Tijssen, RHN
Paganelli, C
Liu, PZY
Keall, PJ
Riboldi, M
Kurz, C
Landry, G
Cusumano, D
Fusella, M
Placidi, L
Affiliation
University of Manchester, Division of Cancer Sciences, Manchester, United Kingdom.Issue Date
2023
Metadata
Show full item recordAbstract
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.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.Journal
Radiotherapy and OncologyDOI
10.1016/j.radonc.2023.109970PubMed ID
37898437Additional Links
https://dx.doi.org/10.1016/j.radonc.2023.109970Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1016/j.radonc.2023.109970
Scopus Count
Collections
Related articles
- Modeling of artificial intelligence-based respiratory motion prediction in MRI-guided radiotherapy: a review.
- Authors: Zhang X, Yan D, Xiao H, Zhong R
- Issue date: 2024 Oct 8
- Real-time motion-including dose estimation of simulated multi-leaf collimator-tracked magnetic resonance-guided radiotherapy.
- Authors: Persson E, Goodwin E, Eiben B, Wetscherek A, Nill S, Oelfke U
- Issue date: 2024 Mar
- Adaptive Radiotherapy Enabled by MRI Guidance.
- Authors: Hunt A, Hansen VN, Oelfke U, Nill S, Hafeez S
- Issue date: 2018 Nov
- Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives.
- Authors: Cusumano D, Boldrini L, Dhont J, Fiorino C, Green O, Güngör G, Jornet N, Klüter S, Landry G, Mattiucci GC, Placidi L, Reynaert N, Ruggieri R, Tanadini-Lang S, Thorwarth D, Yadav P, Yang Y, Valentini V, Verellen D, Indovina L
- Issue date: 2021 May
- Integrated MRI-guided radiotherapy - opportunities and challenges.
- Authors: Keall PJ, Brighi C, Glide-Hurst C, Liney G, Liu PZY, Lydiard S, Paganelli C, Pham T, Shan S, Tree AC, van der Heide UA, Waddington DEJ, Whelan B
- Issue date: 2022 Jul