[1]邵凯南,翁邓胡,李玉成,等. 基于Python脚本的RayStation治疗计划系统逆向调强放疗计划半自动设计[J].中国医学物理学杂志,2018,35(2):156-160.[doi:DOI:10.3969/j.issn.1005-202X.2018.02.007]
　SHAO Kainan,WENG Denghu,LI Yucheng,et al. Semi-automatic design of inverse intensity-modulated radiotherapy treatment plans based on Python scripts in RayStation treatment planning system[J].Chinese Journal of Medical Physics,2018,35(2):156-160.[doi:DOI:10.3969/j.issn.1005-202X.2018.02.007]
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 基于Python脚本的RayStation治疗计划系统逆向调强放疗计划半自动设计()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
35卷
期数:
2018年第2期
页码:
156-160
栏目:
医学放射物理
出版日期:
2018-02-08

文章信息/Info

Title:
 Semi-automatic design of inverse intensity-modulated radiotherapy treatment plans based on Python scripts in RayStation treatment planning system
文章编号:
1005-202X（2018）02-0156-05
作者:
 邵凯南1; 翁邓胡1; 李玉成2; 杨一威1; 李浦1
 1.浙江省肿瘤医院放射物理室/浙江省肿瘤放射治疗重点实验室， 浙江 杭州 310022； 2.南华大学核科学技术学院， 湖南 衡阳 421001
Author(s):
SHAO Kainan1;  WENG Denghu1;  LI Yucheng2;  YANG Yiwei1;  LI Pu1
 1. Key Laboratory of Tumor Radiation Therapy/Department of Radiotherapy Physics, Zhejiang Cancer Hospital, Hangzhou 310022, China; 2. Department of Nuclear Science and Technology, University of South China, Hengyang 421001, China
关键词:
 ; 胸部肿瘤; 调强放射治疗; RayStation治疗计划系统; 半自动放疗计划
Keywords:
 ; Keywords: chest tumor;  intensity-modulated radiotherapy;  RayStation treatment planning system;  semi-automatic radiotherapy planning
分类号:
R730.55
DOI:
DOI:10.3969/j.issn.1005-202X.2018.02.007
文献标志码:
A
摘要:
 目的：利用RayStation治疗计划系统提供的基于Python语言的脚本平台，进行逆向调强放疗计划半自动设计。方法：以胸部放疗计划设计为例，介绍了RayStation治疗计划系统下利用Python脚本进行半自动计划设计的关键步骤，包括感兴趣区轮廓名称和颜色的标准化、计划的创建和修改、 临床目标和优化函数的设置、优化函数的自动更新等。 结果：通过Python语言可以实现放疗计划制定过程中各步骤的自动化，并编写成可根据处方剂量一键生成放疗计划的脚本程序，支持不同肿瘤类型、处方和其他个性化设置。 结论：使用Python脚本的半自动计划工具可提高RayStation治疗计划系统下放疗计划制定的效率，物理师可将更多时间留给个体化的计划修改和优化，有利于提高放疗计划的水平。
Abstract:
 Objective To semi-automatically design inverse intensity-modulated radiotherapy (IMRT) plans with the use of Python scripts in RayStation planning system. Methods Taking the chest radiotherapy plan as an example, we introduced the key steps of the semi-automatical plan design based on Python scripts in RayStation treatment planning system, including the standardization of the name and color of regions of interest, the creation and modification of treatment plan, the setting of clinical goals and optimization functions, and the automatically updating of optimization parameters. Results The radiotherapy planning process was automatically completed using Python scripts. Furthermore, an applet was programmed to create plans based on given prescription doses, which supported different tumor types, prescriptions and other personal settings. Conclusion The use of semi-automatic planning tools of Python scripts can improve the efficiency of radiotherapy planning in RayStation treatment planning system. Physicists can spare more time for individualized revisions and optimizations, which is beneficial for the improvement of radiotherapy plans.

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备注/Memo

备注/Memo:
 【收稿日期】2017-09-19
【基金项目】浙江省医药卫生科技计划项目（2017PY014）
【作者简介】邵凯南，博士，工程师，研究方向：放射物理治疗，E-mail: shaokn@zjcc.org.cn
更新日期/Last Update: 2018-01-29