Monaco放疗计划系统的金标准射束模型临床应用可行性分析

钟阳; 杨彦举; 赵俊; 胡伟刚

doi:10.19401/j.cnki.1007-3639.2023.05.005

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Monaco放疗计划系统的金标准射束模型临床应用可行性分析

论著 | 更新时间：2025-12-31

- Monaco放疗计划系统的金标准射束模型临床应用可行性分析
- The feasibility and implementation of a golden beam model in Monaco treatment planning system
- 中国癌症杂志 2023年33卷第5期页码：452-459
- 作者机构：
  
  复旦大学附属肿瘤医院放射治疗中心，复旦大学上海医学院肿瘤学系，上海市放射肿瘤学重点实验室，上海市放射治疗临床医学研究中心，上海200032
- 作者简介：
  
  [ "钟阳（ORCID: 0000-0002-2940-1479，博士，助理研究员。" ]
  胡伟刚（ORCID: 0000-0002-4409-6804），博士，研究员，复旦大学附属肿瘤医院放射治疗中心副主任。
- 基金信息：
  
  中华国际医学交流基金会“肿瘤精准放疗星火计划”临床研究基金项目(2019-N-11-32)
- DOI：10.19401/j.cnki.1007-3639.2023.05.005
  中图分类号： R730.55
- 收稿：2022-08-30，
  
  修回：2022-11-04，
  
  纸质出版：2023-05-30
- 稿件说明：
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钟阳, 杨彦举, 赵俊, 等. Monaco放疗计划系统的金标准射束模型临床应用可行性分析[J]. 中国癌症杂志, 2023,33(5):452-459.

Yang ZHONG, Yanju YANG, Jun ZHAO, et al. The feasibility and implementation of a golden beam model in Monaco treatment planning system[J]. China Oncology, 2023, 33(5): 452-459.
钟阳, 杨彦举, 赵俊, 等. Monaco放疗计划系统的金标准射束模型临床应用可行性分析[J]. 中国癌症杂志, 2023,33(5):452-459. DOI： 10.19401/j.cnki.1007-3639.2023.05.005.

Yang ZHONG, Yanju YANG, Jun ZHAO, et al. The feasibility and implementation of a golden beam model in Monaco treatment planning system[J]. China Oncology, 2023, 33(5): 452-459. DOI： 10.19401/j.cnki.1007-3639.2023.05.005.

摘要

背景与目的：

“快速验收流程”（accelerated go live，AGL）是医科达加速器从安装、调试、建模到放疗实施的整个管理流程。该流程是基于医科达上千台加速器大数据而建立的一套金标准射束模型，较传统繁琐耗时的加速器验收步骤而言，在数据采集和射束建模阶段得到很大程度优化。本研究旨在评估基于金标准射束数据（gold beam data，GBD）的Monaco放疗计划系统（treatment planning system，TPS）建模临床应用可行性。

方法：

基于复旦大学附属肿瘤医院放射治疗中心安装的两台Elekta Infinity™直线加速器，按照AGL与GBD进行调试和射束建模。然后，利用三维水箱对百分深度剂量（percentage depth dose，PDD）、离轴剂量分布曲线（pro

file）和开野（open filed，OF）点剂量进行客户验收测试（customer acceptance tests，CAT）和射束模型验证，并利用16例不同部位临床病例进行放疗计划设计、测量及剂量分析，进一步测试和验证射束模型精确度。

结果：

对于射束模型的误差分析发现，所有PDD和profile的一致性均大于90%，其中加速器1和加速器2点通过率大于95%的比例（以GBD为参考）分别为99.4%和98.5%。对于点剂量验证，96.8%和97.2%的OF点剂量测量结果与加速器1和加速器2的TPS计算结果的一致性均在2%以内。对于电子束模型，TPS计算结果与实测值的R50和R90偏差均在3 mm以内。当使用3%/3 mm标准时，16例临床放疗计划的Gamma通过率都大于90%，点剂量一致性在3%以内。

结论：

基于GBD的Monaco TPS建模流程，较传统加速器从安装到验收流程而言，在保证模型精度的同时，整个流程时间缩短，具有临床应用可行性。

Abstract

Background and purpose:

Accelerated go live (AGL) is the entire management process for medical accelerators from installation

commissioning

modeling to radiotherapy implementation. Compared with the traditional time-consuming accelerator acceptance process

AGL has established a set of gold standard models based on the big data of thousands of medical accelerators

which makes the accelerator installation greatly optimized in the data acquisition and modeling stage. This study aimed to evaluate and verify an efficient beam modeling method for Monaco treatment planning system (TPS) using golden beam data (GBD).

Methods:

Two Elekta Infinity™ linear accelerators with agility head in the Department of Radiation Oncology

Fudan University Shanghai Cancer Center

were installed and matched with the GBD. Then

a customer acceptance test (CAT) and beam model validations were performed on measured percentage depth dose (PDD) and profile for open-field (OF) point-doses in a three-dimensional water tank. Furthermore

a total of 16 clinical cases from different sites were used for radiotherapy planning design

measurement and dose analysis to validate and verify the accuracy of the beam model.

Results:

For beam model verification

the agreement of all validation PDD and profile was larger than 90%

and the majority point passing rate was larger than 95% (99.4% for linac 1 and 98.5% for linac 2). For point-dose validation

96.8% and 97.2% of OF point meas

ured were found to be within 2% agreement of TPS-calculations for linac 1 and linac 2

respectively. The deviation of R50 and R90 between TPS calculation and measured were within 3 mm at all evaluated points of electron beam. The Gamma passing rate for all plans was greater than 90% when using 3%/3 mm criteria

and point-dose agreement was within 3%.

Conclusion:

Compared with the traditional accelerator process from installation to commission

the Monaco TPS modeling process AGL based on GBD can not only ensure the model accuracy

but also shorten the entire process time

which has the feasibility of clinical application.

关键词

Keywords

references

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