工作流程
计算机科学
放射治疗
运动(物理)
适应(眼睛)
光学(聚焦)
模态(人机交互)
医学物理学
外照射放疗
人工智能
医学
放射科
物理
近距离放射治疗
光学
数据库
作者
Elia Lombardo,Jennifer Dhont,Denis Pagé,Cristina Garibaldi,Luise A. Künzel,Coen Hurkmans,Rob H.N. Tijssen,Chiara Paganelli,Paul Z. Y. Liu,Paul Keall,Marco Riboldi,Christopher Kurz,Guillaume Landry,Davide Cusumano,M. Fusella,Lorenzo Placidi
标识
DOI:10.1016/j.radonc.2023.109970
摘要
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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