| Chen Yan,Wang Haiyang,Liu Hongjia,et al.Modeling of automated planning for esophageal cancer under complex dose prescription and anatomical sections[J].Chinese Journal of Radiological Medicine and Protection,2020,40(12):932-937 |
| Modeling of automated planning for esophageal cancer under complex dose prescription and anatomical sections |
| Received:August 28, 2020 |
| DOI：10.3760/cma.j.issn.0254-5098.2020.12.007 |
| KeyWords:Esophageal cancer Radiotherapy Rapidplan model Automated treatment planning |
| FundProject:首都卫生发展科研专项（首发2018-4-1027，2018-2-1024）；国家自然科学基金（11505012，11905150，81672969）；中央高校基本科研业务费/北京大学临床医学+X青年专项（PKU2020LCXQ019）；国际抗癌协会（UICC-TF/20/722837）；教育部科技发展中心产学研创新基金-"智融兴教"基金（2018A01019）；国家重点研发计划资助项目（2019YFF01014405）；四川省科技计划资助项目（2018HH0099）；北京市属医院科研培育计划项目（PX2019042） |
| Author Name | Affiliation | E-mail | | Chen Yan | Department of Radiation Oncology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang 621000, China | | | Wang Haiyang | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Liu Hongjia | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Wang Meijiao | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Han Jianjun | Department of Radiation Oncology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang 621000, China | | | He Jun | Department of Radiation Oncology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang 621000, China | | | Jia Dong | Department of Radiation Oncology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang 621000, China | | | Li Sha | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Wu Hao | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Pu Yichen | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | | | Zhang Yibao | Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China | ybzhang66@163.com |
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| Abstract:: |
| Objective To study the feasibility and dosimetric characteristics of establishing a comprehensive model for automated treatment planning for esophageal cancer based on Varian RapidPlan module under complex conditions such as different prescriptions and anatomical sections. Methods In total, 301 historical plans with multi-prescription and multi-sectional esophageal cancer were imported into RapidPlan system. Assisted by the ModelAnalytics(MA) tool, statistical verification was performed to profess outliers, yielding the initial model; Additional 40 clinical esophageal cancer treatment plans were duplicated as validation set. The RapidPlan-based re-optimization result was assessed and used as feedback data to fine-tune the model parameters iteratively. The primary dosimetric parameters of the two groups were then compared. Results Through enlarged training set sample size and structure matching (based on relative dose rather than nomenclature), a comprehensive model feasible of handling various anatomic sections and dose prescriptions was successfully established. Both clinical plans and RapidPlan re-optimization were clinically acceptable, displaying complementary dosimetric advantages. Compared with the trial-and-error process of conventional manual planning, RapidPlan method was more efficient and independent from subjective influence, which induced inconsistency of plan quality. Conclusions This work proposed and validated a modeling method of automated treatment planning for esophageal cancer under complex anatomic section and dose prescription. Dosimetric performance of the model is assessed based on independent validation set. |
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