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Abstract：
OBJECTIVE: To evaluate the quality of robust stereotactic body proton therapy (RSBPT) plans generated by one-clicking scripting method for patients with lung cancer.
METHODS: Retrospective analysis was performed on fifty lung cancer patients whose plan with robustly stereotactic body radiation therapy (SBRT). Thirty out of fifty patients were used for training to build a regression model, based on robust SBRT reference doses, to predict EUD values of ROIs for robust SBPT planning. Thereafter, robust SBPT plans with both automated EUD-Based mimicking (Automated Robust Proton ARP) and manual (Manual Robust Proton MRP) methods were evaluated in the remaining 20 patients. Plans were compared in terms of dosimetric parameters and planning time.
RESULTS: A statistically significantly improvement in target dose fall off was observed for ARP plans compare to MRP plans (Dose fall off: 135 for MRP and 88 for ARP, p < 0.01), while no differences in target coverage and conformity. A statistically significantly reduce in normal lung tissue were observed for ARP plans compare to MRP plans (Lung [Dmean cGy (RBE)]: MRP: 478 vs. ARP: 351, p < 0.01; Lung [V5Gy (RBE) (%)]: MRP: 16.1 vs. ARP: 12.1, p < 0.01; Lung [V20Gy (RBE) (%)]: MRP: 8.5 vs. ARP: 6.8, p < 0.01). Planning time was reduced for ARP plans compare to MRP plans (optimization time: 12 min for MRP vs. 8 min for ARP; total plan time: 23 min for MRP vs. 18 min for ARP).
CONCLUSIONS: The automated robust SBPT plans using EUD-Based mimicking of SBRT reference dose improve target dose fall off, reduced the radiation doses to the lungs, reduce planning time, which might be beneficial for patient with lung cancer in clinical.
METHODS: Retrospective analysis was performed on fifty lung cancer patients whose plan with robustly stereotactic body radiation therapy (SBRT). Thirty out of fifty patients were used for training to build a regression model, based on robust SBRT reference doses, to predict EUD values of ROIs for robust SBPT planning. Thereafter, robust SBPT plans with both automated EUD-Based mimicking (Automated Robust Proton ARP) and manual (Manual Robust Proton MRP) methods were evaluated in the remaining 20 patients. Plans were compared in terms of dosimetric parameters and planning time.
RESULTS: A statistically significantly improvement in target dose fall off was observed for ARP plans compare to MRP plans (Dose fall off: 135 for MRP and 88 for ARP, p < 0.01), while no differences in target coverage and conformity. A statistically significantly reduce in normal lung tissue were observed for ARP plans compare to MRP plans (Lung [Dmean cGy (RBE)]: MRP: 478 vs. ARP: 351, p < 0.01; Lung [V5Gy (RBE) (%)]: MRP: 16.1 vs. ARP: 12.1, p < 0.01; Lung [V20Gy (RBE) (%)]: MRP: 8.5 vs. ARP: 6.8, p < 0.01). Planning time was reduced for ARP plans compare to MRP plans (optimization time: 12 min for MRP vs. 8 min for ARP; total plan time: 23 min for MRP vs. 18 min for ARP).
CONCLUSIONS: The automated robust SBPT plans using EUD-Based mimicking of SBRT reference dose improve target dose fall off, reduced the radiation doses to the lungs, reduce planning time, which might be beneficial for patient with lung cancer in clinical.
摘要：
目的：评估通过一键式脚本方法为肺癌患者生成的稳健立体定向身体质子治疗（RSBPT）计划的质量。
方法：对50例肺癌患者进行回顾性分析，这些患者计划采用强力立体定向放射治疗（SBRT）。50名患者中有30名接受训练，建立回归模型，基于稳健的SBRT参考剂量，为稳健的SBPT规划预测ROI的EUD值。此后,在其余20例患者中评估了采用基于EUD的自动模拟(自动稳健质子ARP)和手动(手动稳健质子MRP)方法的稳健SBPT计划.在剂量学参数和计划时间方面比较了计划。
结果：与MRP计划相比，ARP计划的目标剂量下降有统计学上的显着改善（剂量下降：MRP为135，ARP为88，p<0.01),而目标覆盖率和一致性没有差异。与MRP计划相比，ARP计划观察到正常肺组织的统计学显着减少（肺[DmeancGy（RBE）]：MRP：478vs.ARP:351,p<0.01;肺[V5Gy(RBE)(%)]:MRP:16.1vs.ARP:12.1,p<0.01;肺[V20Gy(RBE)(%)]:MRP:8.5vs.ARP:6.8,p<0.01)。与MRP计划相比，ARP计划的计划时间减少了(优化时间：MRP与12分钟ARP为8分钟；总计划时间：MRP为23分钟ARP18分钟)。
结论：使用基于EUD的SBRT参考剂量模拟的自动化稳健SBPT计划可改善目标剂量下降，减少了对肺部的辐射剂量，减少规划时间，这在临床上可能对肺癌患者有益。
方法：对50例肺癌患者进行回顾性分析，这些患者计划采用强力立体定向放射治疗（SBRT）。50名患者中有30名接受训练，建立回归模型，基于稳健的SBRT参考剂量，为稳健的SBPT规划预测ROI的EUD值。此后,在其余20例患者中评估了采用基于EUD的自动模拟(自动稳健质子ARP)和手动(手动稳健质子MRP)方法的稳健SBPT计划.在剂量学参数和计划时间方面比较了计划。
结果：与MRP计划相比，ARP计划的目标剂量下降有统计学上的显着改善（剂量下降：MRP为135，ARP为88，p<0.01),而目标覆盖率和一致性没有差异。与MRP计划相比，ARP计划观察到正常肺组织的统计学显着减少（肺[DmeancGy（RBE）]：MRP：478vs.ARP:351,p<0.01;肺[V5Gy(RBE)(%)]:MRP:16.1vs.ARP:12.1,p<0.01;肺[V20Gy(RBE)(%)]:MRP:8.5vs.ARP:6.8,p<0.01)。与MRP计划相比，ARP计划的计划时间减少了(优化时间：MRP与12分钟ARP为8分钟；总计划时间：MRP为23分钟ARP18分钟)。
结论：使用基于EUD的SBRT参考剂量模拟的自动化稳健SBPT计划可改善目标剂量下降，减少了对肺部的辐射剂量，减少规划时间，这在临床上可能对肺癌患者有益。
