Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
Phys Med Biol. 2010 Apr 7;55(7):1935-47. doi: 10.1088/0031-9155/55/7/010. Epub 2010 Mar 12.
IMRT treatment planning requires consideration of two competing objectives: achieving the required amount of radiation for the planning target volume and minimizing the amount of radiation delivered to all other tissues. It is important for planners to understand the tradeoff between competing factors so that the time-consuming human interaction loop (plan-evaluate-modify) can be eliminated. Treatment-plan-surface models have been proposed as a decision support tool to aid treatment planners and clinicians in choosing between rival treatment plans in a multi-plan environment. In this paper, an empirical approach is introduced to determine the minimum number of treatment plans (minimum knowledge base) required to build accurate representations of the IMRT plan surface in order to predict organ-at-risk (OAR) dose-volume (DV) levels and complications as a function of input DV constraint settings corresponding to all involved OARs in the plan. We have tested our approach on five head and neck patients and five whole pelvis/prostate patients. Our results suggest that approximately 30 plans were sufficient to predict DV levels with less than 3% relative error in both head and neck and whole pelvis/prostate cases. In addition, approximately 30-60 plans were sufficient to predict saliva flow rate with less than 2% relative error and to classify rectal bleeding with an accuracy of 90%.
调强适形放疗(IMRT)治疗计划需要考虑两个相互竞争的目标:达到计划靶区所需的辐射量,以及尽量减少对所有其他组织的辐射量。对于规划者来说,了解竞争因素之间的权衡是很重要的,这样可以避免耗时的人机交互循环(计划-评估-修改)。治疗计划表面模型已被提议作为一种决策支持工具,以帮助治疗计划者和临床医生在多计划环境中选择有竞争力的治疗计划。在本文中,引入了一种经验方法来确定构建准确的调强适形放疗计划表面表示所需的最小治疗计划数量(最小知识库),以便根据与计划中所有涉及的器官相关的输入剂量体积(DV)约束设置来预测危及器官(OAR)剂量体积(DV)水平和并发症。我们已经在五名头颈部患者和五名全骨盆/前列腺患者上测试了我们的方法。我们的结果表明,在头颈部和全骨盆/前列腺病例中,大约 30 个计划足以预测 DV 水平,相对误差小于 3%。此外,大约 30-60 个计划足以预测唾液流量,相对误差小于 2%,并以 90%的准确率分类直肠出血。