王海洋,吴昊,项小羽,黄宇亮,李晨光,胡俏俏,杜伊筱,弓健,李玮博,张艺宝.肺癌立体定向放疗RapidPlan商业模型的本地改造可行性探究[J].中华放射医学与防护杂志,2020,40(3):203-208
肺癌立体定向放疗RapidPlan商业模型的本地改造可行性探究
A feasibility study of local adaptation of Lung SBRT RapidPlan commercial model
投稿时间:2019-07-10  
DOI:10.3760/cma.j.issn.0254-5098.2020.03.008
中文关键词:  放射治疗计划  RapidPlan模型  本地化  肺癌  立体定向放疗
英文关键词:Radiotherapy planning  RapidPlan  Localize  Lung cancer  Stereotactic body radiation therapy
基金项目:首都卫生发展科研专项(首发2018-4-1027);教育部科技发展中心产学研创新基金-"智融兴教"基金(2018A01019);国家自然科学基金(11505012,11905150);国家重点研发计划(2019YFF01014405);四川省科技计划(2018HH0099);北京市自然科学基金(7172048);北京市属医院科研培育计划项目(PX2019042)
作者单位E-mail
王海洋 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
吴昊 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
项小羽 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
黄宇亮 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
李晨光 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
胡俏俏 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
杜伊筱 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
弓健 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142  
李玮博 德国亥姆霍兹慕尼黑研究中心-德国环境健康研究中心放射医学所, 纽贺堡 185764  
张艺宝 北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科 恶性肿瘤发病机制及转化研究教育部重点实验室 100142 ybzhang66@163.com 
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中文摘要:
      目的 探究以本地需求为目标改造亨利福特医院健康系统(HFHS)RapidPlan肺癌立体定向放疗(SBRT)商用模型后用于放疗计划的可行性和优化效果。方法 结合最新临床指南证据和本单位临床实际对Eclipse内置HFHS模型做出如下适应性改造:1增加靶区结构内在肿瘤靶区体积(IGTV)、危及器官结构肺(Lung),并设置相应参数。2将计划靶区体积(PTV)结构上限(Upper)值由109%调整至125%。3用本单位73例历史同步推量计划替换其原训练集,并在模型分析(Model Analytics)软件辅助下进行统计学确认和离群值处置。选取10例未参与建模的病例用于独立验证和比较改造前后模型在相同布野条件下的自动优化结果。靶区剂量归一后比较:PTV适形指数、危及器官平均剂量、最大剂量和剂量-体积参数等。结果 改造后的模型验证计划(Mlocal_P)PTV DVH"尾部"与IGTV DVH"肩部"及"尾部"表现较原HFHS模型验证计划(HFHS_P)高。Mlocal_P的PTV_CI(1.07±0.13)显著小于HFHS_P(1.25±0.24),差异有统计学意义(Z=-2.497,P<0.05)。除心脏_D15cc、心脏_Dmax外Mlocal_P绝大部分危及器官剂量学参数均较HFHS_P更低,且标准差更小。但对于心脏_D15cc和心脏_Dmax,两种计划差异不超过3.06%。HFHS_P不满足要求剂量学参数达10项次,其中两项未通过例数的PTV_CI值为1.52与1.74,远超临床可接受范围。结论 HFHS商用模型可通过计划训练集替换、参数调整等方法进行本地化改造。且改造后模型优化的计划在靶区适形性与高量等方面更满足本单位临床要求,在危及器官保护和一致性等方面也表现更优。
英文摘要:
      Objective To explore the feasibility and optimization effect of modifying the Henry Ford Hospital (HFHS) RapidPlan model for stereotactic body radiation therapy planning based on local requirements. Methods The following changes were made based on Henry Ford Health System(HFHS) Rapid Plan Lung SBRT model, taking the latest clinical guideline evidence and local clinical practice into account:Internal gross target volume(IGTV) and organ at risk(OAR) structure, lung, were added and set corresponding parameters.The upper value of planning target volume (PTV) was adjusted from 109% to 125%. The original training library was replaced with 73 local historical simultaneous integrated boosting plans, and statistical verification and outlier cleaning of the initial trained model were performed using Model Analytics software. Totally 10 cases not included in the model library were selected for independent verification, and automatic optimization result of the models before and after modifying were compared under the same beam condition. The following dosimetric parameters were compared after target dose normalization:conformal index (CI) of target volume, the mean doses, maximum doses and dose-volume parameters of OARs. Results The "tail" of the PTV's DVH and the "shoulder"and "tail" of the IGTV's DVH of model M(local) validation plan (M(local)_P) performs higher than the original model HFHS (HFHS_P). The PTV_CI (1.07±0.13) of Mlocal_P were significantly smaller than HFHS_P (1.25±0.24) (Z=-2.497, P<0.05). Except for Heart_D15 cm3 and Heart_Dmax, most of the Mlocal_P dosimetric parameters of OARs were lower than HFHS_P, and the standard deviation was smaller. However, the difference of between two plans was no more than 3.06%. 10 HFHS_P plans don't satisfy dose parameters requirement, two of which PTV_CI values are 1.52 and 1.74, far beyond the clinically acceptable range. Conclusions Commercial model HFHS could be localized by replacing training library and adjusting parameters. Moreover, plans optimized by the modified model are local clinical acceptable in the aspects of target volume conformity and hotspots, and have a better performance in terms of OAR sparing and plan consistency.
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