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SmartSequence与SlidingWnd两种子野分割算法的比较 被引量:5

To Comparison the Two Segment Algorithms of SmartSequence and SlidingWnd
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摘要 目的:本研究试图比较Elekta Xio TPS(版本:4.62)计划设计中使用SmartSequence和SlidingWnd两种子野分割算法的特点。方法:对9例宫颈癌患者优化计划设计后的射野通量分布,分别用两种子野分割算法分别分割子野,将剂量归一到95%ptv=5000 cGy。然后利用剂量体积直方图(DVH)、靶区和危及器官的剂量分布、子野数、机器跳数(MU)以及治疗时间,对两组计划进行比较。结果:两种子野分割算法得到的计划均满足临床要求,剂量分布基本一致,DVH接近。相对于SlidingWnd子野分割算法,SmartSequence分割算法得到的子野数数目平均减少了28%,总MU数减少了20%,但是在治疗时间上没有明显优势。结论:在维持治疗计划方案质量相同的条件下,与SlidingWnd子野分割算法相比,SmartSequence分割算法可以显著减少子野数和总MU数。 Objective: In this study, the effects of two segment algorithms of SmartSequence and SlidingWnd used in Elekta Xio TPS (version: 4.62) on the planning quality were compared. Methods:9 patients with cervix cancer were selected for the study. In the first step, an optimized IMRT plan with coresponding beam's intensities for each patient was worked out; And in the second step, the segments for each beam were generated out by using the two segment algorithms of SmartSequence and SlidingWnd used in Elekta Xio TPS. For each patient's IMRT plan, all doses in target were normalized to 95%ptv=5000 cGy; And in the third step, the effects of using the two algorithms on DVHs, the doses in targets and OARs, the segment numbers, the total Mus and the dilivering time. Results: To keep the same or the similar qualities of dose distributions and DVHs in target and OARs for 9 patient's plans, the results showed that compared with the Sliding Wnd algorithm, the SmartSequence algorithm could reduced in average by 28% of the segment's number and 20% off the total Mus for each IMRT plan. For total treatment time, the SmartSequence plan not obvious reduce. Conclusions: Our study showed that for the 9 selected cervix cancer patint's plan, the SmartSequence algorithm can reduces the number of segments for each beam and the total MUs significantly compared with the Slidin~ Wnd one.
出处 《中国医学物理学杂志》 CSCD 2013年第1期3851-3853,3893,共4页 Chinese Journal of Medical Physics
关键词 子野分割算法 宫颈癌调强计划 SmartSequence算法 SlidingWnd算法 cervix cancer planning segmenting algorithms smartSequence algorithm slidingWnd algorithm
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参考文献6

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共引文献9

同被引文献38

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