4.7 Article

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects

Journal

RADIOTHERAPY AND ONCOLOGY
Volume 190, Issue -, Pages -

Publisher

ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2023.109970

Keywords

MRI-linac; Intra-fractional motion; Motion estimation; Tumour tracking; Motion prediction; AI

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This paper describes the steps and available solutions for intra-fractional motion management in MRIgRT, and proposes a 3D compensation method for motion-induced over- or under-dosage with minimal impact on radiotherapy treatment time. Artificial intelligence is emphasized as a fast and accurate alternative to conventional algorithms.
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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