Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany.
Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Department of Medical Physics, Brussels, Belgium; Université Libre De Bruxelles (ULB), Radiophysics and MRI Physics Laboratory, Brussels, Belgium.
Radiother Oncol. 2024 Jan;190:109970. doi: 10.1016/j.radonc.2023.109970. Epub 2023 Oct 26.
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.
MRI 引导的放射治疗（MRIgRT）是一种高度复杂的治疗方式，允许根据每天治疗（分次间）发生的解剖变化进行调整，也允许根据治疗期间（分次内）发生的运动进行调整。在本透视论文中，我们描述了 MRIgRT 期间分次内运动管理的不同步骤，从成像到射束适应，以及临床和研究水平上目前可用的解决方案。此外，考虑到文献中的最新发展，预计将采用一种工作流程，通过 3D 方式补偿运动引起的超量和/或欠量，对放射治疗时间的影响最小。考虑到实时适应的时间限制，特别关注人工智能（AI）解决方案，将其作为传统算法的快速准确替代方案。
