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本文引用的文献

1
Trade-off bounds for the Pareto surface approximation in multi-criteria IMRT planning.多准则调强放射治疗计划中的帕累托曲面逼近的权衡界限。
Phys Med Biol. 2009 Oct 21;54(20):6299-311. doi: 10.1088/0031-9155/54/20/018. Epub 2009 Oct 7.
2
How many plans are needed in an IMRT multi-objective plan database?调强放射治疗多目标计划数据库中需要多少个计划?
Phys Med Biol. 2008 Jun 7;53(11):2785-96. doi: 10.1088/0031-9155/53/11/002. Epub 2008 May 1.
3
A comparison of an algorithm for automated sequential beam orientation selection (Cycle) with simulated annealing.一种用于自动顺序射束方向选择的算法(循环算法)与模拟退火算法的比较。
Phys Med Biol. 2008 Apr 21;53(8):2003-18. doi: 10.1088/0031-9155/53/8/001. Epub 2008 Mar 26.
4
Pareto navigation: algorithmic foundation of interactive multi-criteria IMRT planning.帕累托导航:交互式多标准调强放疗计划的算法基础
Phys Med Biol. 2008 Feb 21;53(4):985-98. doi: 10.1088/0031-9155/53/4/011. Epub 2008 Jan 24.
5
Approximating convex pareto surfaces in multiobjective radiotherapy planning.多目标放射治疗计划中凸帕累托曲面的逼近
Med Phys. 2006 Sep;33(9):3399-407. doi: 10.1118/1.2335486.
6
A unifying framework for multi-criteria fluence map optimization models.多标准注量图优化模型的统一框架。
Phys Med Biol. 2004 May 21;49(10):1991-2013. doi: 10.1088/0031-9155/49/10/011.
7
Beam orientation optimization in intensity-modulated radiation treatment planning.调强放射治疗计划中的射束方向优化
Med Phys. 2000 Jun;27(6):1238-45. doi: 10.1118/1.599001.

同时导航多个 Pareto 曲面,应用于具有多个射束角度配置的多准则调强放疗计划。

Simultaneous navigation of multiple Pareto surfaces, with an application to multicriteria IMRT planning with multiple beam angle configurations.

机构信息

Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

出版信息

Med Phys. 2010 Feb;37(2):736-41. doi: 10.1118/1.3292636.

DOI:10.1118/1.3292636
PMID:20229883
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2821423/
Abstract

PURPOSE

To introduce a method to simultaneously explore a collection of Pareto surfaces. The method will allow radiotherapy treatment planners to interactively explore treatment plans for different beam angle configurations as well as different treatment modalities.

METHODS

The authors assume a convex optimization setting and represent the Pareto surface for each modality or given beam set by a set of discrete points on the surface. Weighted averages of these discrete points produce a continuous representation of each Pareto surface. The authors calculate a set of Pareto surfaces and use linear programming to navigate across the individual surfaces, allowing switches between surfaces. The switches are organized such that the plan profits in the requested way, while trying to keep the change in dose as small as possible.

RESULTS

The system is demonstrated on a phantom pancreas IMRT case using 100 different five beam configurations and a multicriteria formulation with six objectives. The system has intuitive behavior and is easy to control. Also, because the underlying linear programs are small, the system is fast enough to offer real-time exploration for the Pareto surfaces of the given beam configurations.

CONCLUSIONS

The system presented offers a sound starting point for building clinical systems for multicriteria exploration of different modalities and offers a controllable way to explore hundreds of beam angle configurations in IMRT planning, allowing the users to focus their attention on the dose distribution and treatment planning objectives instead of spending excessive time on the technicalities of delivery.

摘要

目的

介绍一种同时探索一系列 Pareto 曲面的方法。该方法将允许放射治疗计划者交互式地探索不同射束角度配置和不同治疗方式的治疗计划。

方法

作者假设凸优化设置,并通过曲面上的一组离散点来表示每种方式或给定射束集的 Pareto 曲面。这些离散点的加权平均值产生每个 Pareto 曲面的连续表示。作者计算了一组 Pareto 曲面,并使用线性规划在各个曲面之间导航,允许在曲面之间切换。切换的组织方式使得计划以请求的方式获利,同时尽量减小剂量变化。

结果

该系统在一个使用 100 种不同五束配置的胰腺 IMRT 病例和一个具有六个目标的多准则公式上进行了演示。该系统具有直观的行为,易于控制。此外,由于基础线性程序较小,该系统足够快,可以实时探索给定射束配置的 Pareto 曲面。

结论

所提出的系统为构建用于不同方式的多准则探索的临床系统提供了一个良好的起点,并提供了一种可控的方法来探索 IMRT 计划中的数百种射束角度配置,使用户能够将注意力集中在剂量分布和治疗计划目标上,而不是在输送的技术细节上花费过多时间。