基于优化参数树搜索算法的直肠癌调强放疗自动计划

Automatic planning of IMRT for rectum cancer based on optimization parameters tree search algorithm

目的针对调强放疗(IMRT)计划大量耗费人工及计划质量高度依赖物理师临床经验且差异较大等问题,探讨一种可实现无监督调强放疗自动计划的方案。方法采用Varian Eclipse 15.6治疗计划系统(TPS)自带的脚本应用程序接口(ESAPI)和优化参数树搜索算法(OPTSA)模拟,实现整个计划设计过程。通过ESAPI进行交互,自动输入输出相关参数;利用OPTSA对靶区和危及器官(OAR)的剂量学参数进行评估,并迭代调整优化目标参数来逐步改善,最终获得满足临床需求的IMRT计划。为验证自动计划的有效性,从临床数据库中选取20例既往已完成治疗的直肠癌病例,比较基于OPTSA算法的自动计划和临床人工计划在剂量分布和特定剂量学参数上的差异。结果所有的自动计划均满足临床要求。90%的自动计划质量超过既往人工计划,10%的自动计划则与人工计划质量基本一致。PTV平均适形指数(CI)在自动计划和人工计划中分别为0.88和0.80。与人工计划相比,自动计划OAR剂量学指标平均降低11%。自动计划和人工计划平均运行时间分别为(28.15±3.61)和(36.7±4.6)min。结论利用ESAPI所创建的OPTSA自动计划质量不劣于人工计划。在保证计划质量和一致性的情况下,OPTSA自动计划可缩短计划设计中所耗费的人力时间。

Objective To solve the problems in intensity-modulated radiation therapy(IMRT)planning,such as large labor cost and high dependence on the experience of physicists and great inconsistency in the quality of plan,and to discuss an unsupervised automatic treatment planning procedure of IMRT.Methods The eclipse scripting application programming interface(ESAPI)within the Eclipse treatment planning system(TPS)15.6 and optimization parameters tree search algorithm(OPTSA)were used to emulate and realize the whole planning process.Interacted with the TPS through ESAPI,relevant dosimetric parameters were input and output.The OPTSA evaluated the plan qualities based on dosimetric parameters of the targets and organs at risk(OARs)and iteratively adjusted the optimization objective parameters to achieve a progressively improving IMRT plan.In order to verify the effectiveness of the automatic planning,twenty historical rectum cancer cases were selected from the clinical database,and the dose distribution and specific dosimetric parameters were compared between the plans generated by the OPTSA and the manual plans under the same constraints.Results All the auto plans have met clinical requirements.Furthermore,90%and 10%of the auto plans were deemed as clinically improved and equally compared with the manual plans,respectively.The average CI for the PTV was 0.88 and 0.80 for the auto and manual plans respectively.Compared with the manual plans,the mean doses of all the OARs in the auto plans were reduced by 11%in average.The average elapsed time of automatic planning and manual planning was(28.15±3.61)and(36.7±4.6)min,respectively.Conclusions The plans created by the proposed algorithm have been shown to be at least as good as the manual plans.In addition,this method can shorten the labor time in plan designing while ensuring the plan quality and consistency of the plan.