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从物理剂量约束到逆向放射治疗计划中的等效均匀剂量约束。

From physical dose constraints to equivalent uniform dose constraints in inverse radiotherapy planning.

作者信息

Thieke Christian, Bortfeld Thomas, Niemierko Andrzej, Nill Simeon

机构信息

Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

出版信息

Med Phys. 2003 Sep;30(9):2332-9. doi: 10.1118/1.1598852.

DOI:10.1118/1.1598852
PMID:14528955
Abstract

Optimization algorithms in inverse radiotherapy planning need information about the desired dose distribution. Usually the planner defines physical dose constraints for each structure of the treatment plan, either in form of minimum and maximum doses or as dose-volume constraints. The concept of equivalent uniform dose (EUD) was designed to describe dose distributions with a higher clinical relevance. In this paper, we present a method to consider the EUD as an optimization constraint by using the method of projections onto convex sets (POCS). In each iteration of the optimization loop, for the actual dose distribution of an organ that violates an EUD constraint a new dose distribution is calculated that satisfies the EUD constraint, leading to voxel-based physical dose constraints. The new dose distribution is found by projecting the current one onto the convex set of all dose distributions fulfilling the EUD constraint. The algorithm is easy to integrate into existing inverse planning systems, and it allows the planner to choose between physical and EUD constraints separately for each structure. A clinical case of a head and neck tumor is optimized using three different sets of constraints: physical constraints for all structures, physical constraints for the target and EUD constraints for the organs at risk, and EUD constraints for all structures. The results show that the POCS method converges stable and given EUD constraints are reached closely.

摘要

逆向放射治疗计划中的优化算法需要有关期望剂量分布的信息。通常,计划者会为治疗计划的每个结构定义物理剂量约束,形式为最小和最大剂量或剂量体积约束。等效均匀剂量(EUD)的概念旨在描述具有更高临床相关性的剂量分布。在本文中,我们提出了一种通过使用凸集投影法(POCS)将EUD视为优化约束的方法。在优化循环的每次迭代中,对于违反EUD约束的器官的实际剂量分布,计算出一个满足EUD约束的新剂量分布,从而产生基于体素的物理剂量约束。通过将当前剂量分布投影到满足EUD约束的所有剂量分布的凸集上来找到新的剂量分布。该算法易于集成到现有的逆向计划系统中,并且允许计划者为每个结构分别在物理约束和EUD约束之间进行选择。使用三组不同的约束对一例头颈部肿瘤的临床病例进行了优化:所有结构的物理约束、靶区的物理约束和危及器官的EUD约束以及所有结构的EUD约束。结果表明,POCS方法收敛稳定,并且能接近达到给定的EUD约束。

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