在线自适应调强放疗计划方法。
Online adaptive planning methods for intensity-modulated radiotherapy.
机构信息
Department of Business Analytics, University of Amsterdam, The Netherlands.
Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America.
出版信息
Phys Med Biol. 2023 May 11;68(10). doi: 10.1088/1361-6560/accdb2.
Abstract
Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.
摘要
在线自适应放射治疗旨在根据每日治疗前分次间的变化，调整患者的治疗计划以适应其当前的解剖结构。由于该过程需要在患者固定在治疗台上时完成，因此需要高效的自适应规划方法来快速生成高质量的每日治疗计划。传统的规划方法无法满足在线自适应放射治疗的时间要求，因为它们通常需要大量的人工干预，从而显著延长了规划阶段的时间。本文回顾了当前商业在线自适应放射治疗系统所采用的规划策略、在线自适应规划方面的研究以及人工智能在在线自适应规划中的潜在应用。
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