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基于肿瘤控制概率(TCP)和正常组织并发症概率(NTCP)预期的调强放射治疗(IMRT)优化,包括随机和系统几何误差。

IMRT optimization including random and systematic geometric errors based on the expectation of TCP and NTCP.

作者信息

Witte Marnix G, van der Geer Joris, Schneider Christoph, Lebesque Joos V, Alber Markus, van Herk Marcel

机构信息

Department of Radiation Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.

出版信息

Med Phys. 2007 Sep;34(9):3544-55. doi: 10.1118/1.2760027.

Abstract

The purpose of this work was the development of a probabilistic planning method with biological cost functions that does not require the definition of margins. Geometrical uncertainties were integrated in tumor control probability (TCP) and normal tissue complication probability (NTCP) objective functions for inverse planning. For efficiency reasons random errors were included by blurring the dose distribution and systematic errors by shifting structures with respect to the dose. Treatment plans were made for 19 prostate patients following four inverse strategies: Conformal with homogeneous dose to the planning target volume (PTV), a simultaneous integrated boost using a second PTV, optimization using TCP and NTCP functions together with a PTV, and probabilistic TCP and NTCP optimization for the clinical target volume without PTV. The resulting plans were evaluated by independent Monte Carlo simulation of many possible treatment histories including geometrical uncertainties. The results showed that the probabilistic optimization technique reduced the rectal wall volume receiving high dose, while at the same time increasing the dose to the clinical target volume. Without sacrificing the expected local control rate, the expected rectum toxicity could be reduced by 50% relative to the boost technique. The improvement over the conformal technique was larger yet. The margin based biological technique led to toxicity in between the boost and probabilistic techniques, but its control rates were very variable and relatively low. During evaluations, the sensitivity of the local control probability to variations in biological parameters appeared similar for all four strategies. The sensitivity to variations of the geometrical error distributions was strongest for the probabilistic technique. It is concluded that probabilistic optimization based on tumor control probability and normal tissue complication probability is feasible. It results in robust prostate treatment plans with an improved balance between local control and rectum toxicity, compared to conventional techniques.

摘要

这项工作的目的是开发一种具有生物成本函数的概率规划方法,该方法无需定义边界。将几何不确定性纳入肿瘤控制概率(TCP)和正常组织并发症概率(NTCP)目标函数中以进行逆向规划。出于效率考虑,通过模糊剂量分布纳入随机误差,并通过相对于剂量移动结构纳入系统误差。按照四种逆向策略为19例前列腺癌患者制定治疗计划:对计划靶区(PTV)进行均匀剂量的适形放疗、使用第二个PTV进行同步整合加量、使用TCP和NTCP函数以及PTV进行优化,以及对无PTV的临床靶区进行概率性TCP和NTCP优化。通过对包括几何不确定性在内的许多可能治疗过程进行独立的蒙特卡罗模拟来评估所得计划。结果表明,概率优化技术减少了接受高剂量的直肠壁体积,同时增加了临床靶区的剂量。在不牺牲预期局部控制率的情况下,相对于加量技术,预期直肠毒性可降低50%。相对于适形技术的改善更大。基于边界的生物技术导致的毒性介于加量技术和概率技术之间,但其控制率变化很大且相对较低。在评估过程中,所有四种策略的局部控制概率对生物学参数变化的敏感性似乎相似。概率技术对几何误差分布变化的敏感性最强。得出的结论是,基于肿瘤控制概率和正常组织并发症概率的概率优化是可行的。与传统技术相比,它能产生稳健的前列腺癌治疗计划,在局部控制和直肠毒性之间实现更好的平衡。

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