中国癌症杂志 ›› 2020, Vol. 30 ›› Issue (10): 821-825.doi: 10.19401/j.cnki.1007-3639.2020.10.014

• 论著 • 上一篇    下一篇

加速器模型和治疗计划系统对知识库计划模型的影响:一项基于宫颈癌适形调强放射放疗计划的研究

陈晓慧,王佳舟,胡伟刚,彭佳元,翟 鹏   

  1. 复旦大学附属肿瘤医院放疗科,复旦大学上海医学院肿瘤学系,上海 200032
  • 出版日期:2020-10-30 发布日期:2020-11-13
  • 通信作者: 翟 鹏 E-mail: 790010365@qq.com

Dosimetric impact of machine and treatment planning system on knowledge-based planning: a study based on cervical cancer IMRT plan

CHEN Xiaohui, WANG Jiazhou, HU Weigang, PENG Jiayuan, ZHAI Peng   

  1. Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
  • Published:2020-10-30 Online:2020-11-13
  • Contact: ZHAI Peng E-mail: 790010365@qq.com

摘要: 背景与目的:“RapidPlan”利用适形调强放射治疗(intensity-modulated radiotherapy,IMRT)中的患者解剖和剂量信息,以剂量体积直方图(dose-volume histogram,DVH)预测模型的方式来预测新计划的剂量分布。针对每种治疗计划系统(treatment planning system,TPS)和治疗机器模型分别建立知识库模型需耗费大量精力且选择繁琐,因此本研究评估基于特定TPS和加速器模型建立的知识库计划模型能否适用于其他TPS和加速器模型。方法:选取2015—2016年于复旦大学附属肿瘤医院采用IMRT技术治疗的50例临床治疗的宫颈癌患者的放疗资料,使用RapidPlan建立基于知识库的计划预测模型。训练数据均基于Pinnacle计划系统,机器模型采用Synergy加速器6 MV光子射线。使用该预测模型对15例宫颈癌病例进行预测,提取目标函数数值后,分别在3组不同的优化环境中重新优化以评估加速器模型和TPS对知识库计划模型的影响:① 与模型构建一致的TPS和加速器模型,即Pinnacle与Synergy;② TPS一致但加速器模型不一致,即Pinnacle与Truebeam;③ TPS和加速器模型都不一致,即Eclipse和Truebeam。评估方法为基于知识库模型生成的计划与相应环境下人工计划进行剂量学比较。结果:组2和组3中,知识库计划与人工计划得到相似质量的计划靶区(planning target volume,PTV)剂量覆盖,而在组1中知识库计划改善了PTV的D 2 %(0.95 Gy,P<0.01)和剂量均一性指数(homogeneity index,HI)(0.02,P<0.01)。知识库计划降低了所有3组计划的膀胱V 30 、V 45 和平均剂量,同时知识库计划还降低了肠道的平均剂量。结论:基于知识库的计划模型对加速器和TPS的依赖并不显著。

关键词: 宫颈癌, RapidPlan, 适形调强放射治疗

Abstract: Background and purpose: RapidPlan can be used to extract patient’s anatomy and dose information from intensity-modulated radiotherapy (IMRT) plans to predict the dose-volume histogram (DVH) of a new one, in the method of DVH estimation models. Establishing a knowledge-based model for treatment planning system (TPS) and accelerator separately requires a lot of efforts, and the selection will be cumbersome. This study aimed to investigate whether a knowledge-based treatment planning model can smoothly migrate to different machine and TPS. Methods: The clinical treatment plans of 50 cervical cancer patients treated in Fudan University Shanghai Cancer Center from 2015 to 2016 were added in RapidPlan to develop a knowledge-based planning model. All training data were created with Pinnacle and optimized for 6 MV photon beams from a Synergy accelerator. Model was used to estimate the DVH in 15 IMRT plans. Plans were reoptimized to evaluate the impact of the accelerator model and TPS on knowledge-based planning model after extracting the objective function value. The evaluation included 3 groups. In Group 1, the knowledge based plan (KBP) and manual plan used the same accelerator and TPS as model training data (Pinnacle and Synergy). In Group 2, the KBP and manual plan used the same TPS, while the accelerator model was different (Pinnacle and Truebeam). In Group 3, the KBP and manual plan used different TPS and accelerator models (Eclipse and Truebeam). DVH quantitative analysis was performed to make comparison between the KBP and the manual plans in 3 groups respectively. Results: In Group 2 and Group 3, KBP plans showed similar quality of planning target volume (PTV) as manual plans. However, KBP plans improved D 2 % (0.95 Gy, P<0.01) and HI (0.02, P<0.01) in Group 1. RapidPlan decreased the average values of V 30 , V 45 and mean dose of bladder in all 3 groups. RapidPlan also generated better mean dose of bowel in 3 groups. Conclusion: KBP does not significantly depend on machine and TPS .

Key words:  Cervical cancer, RapidPlan, Intensity-modulated radiotherapy