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多准则容积旋转调强优化。

Multicriteria VMAT optimization.

机构信息

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

出版信息

Med Phys. 2012 Feb;39(2):686-96. doi: 10.1118/1.3675601.

Abstract

PURPOSE

To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency.

METHODS

A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE.

RESULTS

VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average.

CONCLUSIONS

VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

摘要

目的

使容积调强弧形治疗(VMAT)的计划更快,并探索规划目标与交付效率之间的权衡。

方法

为 180 个等间距光束的角度网格解决凸多准则剂量优化问题。这允许规划者在理想的剂量分布 Pareto 表面上进行导航,并选择所需的目标覆盖范围与器官风险保护之间的平衡计划。然后,通过通量图合并和排序算法使选定的计划成为可交付的 VMAT,该算法基于相似度得分合并相邻的通量图,然后一起输送合并的通量图,简化了输送过程。只要保持剂量分布质量,就会进行连续合并。完整的算法称为 VMERGE。

结果

VMERGE 应用于三个病例:前列腺、胰腺和大脑。在每种情况下,所选的 Pareto 最优计划几乎与 VMAT 合并例程完全匹配,从而在不到 5 分钟的时间内使用单个弧形输送高质量的计划。

结论

VMERGE 提供了比现有 VMAT 算法显著的改进。第一个是多准则规划方面,这大大加快了规划时间,并允许用户选择最能在目标覆盖范围和器官风险保护之间达成最佳折衷的计划。第二个是用户选择的最终 VMAT 计划的 epsilon-最优性保证。最后,用户可以探索交付时间和计划质量之间的权衡,这是 VMAT 的一个基本方面,无法通过当前的商业规划系统轻松进行调查。

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