Study of automatic planning of multi-disease and multi-plan type based on Raystation planning system
10.3760/cma.j.cn113030-20190426-00154
- VernacularTitle:基于Raystation计划系统实现多病种多类型自动计划技术的研究
- Author:
Zhaoyang LOU
1
;
Ronghu MAO
;
Dingjie LI
;
Lingling TIAN
;
Bing LI
;
Hong GE
Author Information
1. 郑州大学附属肿瘤医院 河南省肿瘤医院放疗科 450008
- From:
Chinese Journal of Radiation Oncology
2020;29(11):968-972
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To propose an automatic planning platform of the Raystation planning system suitable for multi-disease and multi-plan technique by using the Raystation built-in script function.Methods:IronPython and WPF user interface framework were utilized for programming and resolving the differences in the design of different types of plans for different diseases. The program was designed from prescription identification, visual plan parameter input and cost-function setting. The efficiency of automatic planning and manual planning was compared when applied in whole brain irradiation, nasopharyngeal carcinoma, cervical cancer, esophageal cancer and breast cancer, including IMRT and VMAT. The dosimetric parameters of the whole brain irradiation were chosen.Results:Physicists were only required to enter and select the necessary parameters to achieve the plan design by using the program. Compared with the five types of diseases, the maximum efficiency of automatic planning was 1.4 times higher than that of manual planning. In the dosimetric evaluation of the whole brain irradiation plan, both manual and automatic planning could meet the clinical needs, and the D 2%, CI and HI of the target area did not significantly differ (all P>0.05). The mean D 98% of the target area and the D max of lens in the manual plan were significantly higher than those in the automatic plan by 0.4% and 7.1%(both P<0.05). Conclusion:The developed program has the function of automatic planning system, which can realize the automatic planning of multi-disease and multi-type radiotherapy, significantly improve the efficiency of plan design and has important clinical application value.
