Wang Aoxiang, Zhu Ya-Nan, Setianegara Jufri, Lin Yuting, Xiao Peng, Xie Qingguo, Gao Hao
Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China.
Department of Radiation Oncology, University of Kansas Medical Center, USA.
ArXiv. 2024 Nov 27:arXiv:2411.18074v1.
Intensity-modulated proton therapy (IMPT) using pencil beam technique scans tumor in a layer by layer, then spot by spot manner. It can provide highly conformal dose to tumor targets and spare nearby organs-at-risk (OAR). Fast delivery of IMPT can improve patient comfort and reduce motion-induced uncertainties. Since energy layer switching time dominants the plan delivery time, reducing the number of energy layers is important for improving delivery efficiency. Although various energy layer optimization (ELO) methods exist, they are rarely experimentally validated or clinically implemented, since it is technically challenging to integrate these methods into commercially available treatment planning system (TPS) that is not open-source.
This work develops and experimentally validates an in-house TPS (IH-TPS) that incorporates a novel ELO method for the purpose of fast IMPT.
The dose calculation accuracy of IH-TPS is verified against the measured beam data and the RayStation TPS. For treatment planning, a novel ELO method via greed selection algorithm is proposed to reduce energy layer switching time and total plan delivery time. To validate the planning accuracy of IH-TPS, the 3D gamma index is calculated between IH-TPS plans and RayStation plans for various scenarios. Patient-specific quality-assurance (QA) verifications are conducted to experimentally verify the delivered dose from the IH-TPS plans for several clinical cases.
Dose distributions in IH-TPS matched with those from RayStation TPS, with 3D gamma index results exceeding 95% (2mm, 2%). The ELO method significantly reduced the delivery time while maintaining plan quality. For instance, in a brain case, the number of energy layers was reduced from 78 to 40, leading to a 62% reduction in total delivery time. Patient-specific QA validation with the IBA ProteusONE proton machine confirmed a >95% pass rate for all cases.
An IH-TPS equipped with a novel ELO algorithm is developed and experimentally validated for the purpose of fast IMPT, with enhanced delivery efficiency and preserved plan quality.
使用笔形束技术的调强质子治疗（IMPT）以逐层、逐点的方式扫描肿瘤。它可以为肿瘤靶区提供高度适形的剂量，并保护附近的危及器官（OAR）。快速的IMPT递送可以提高患者的舒适度并减少运动引起的不确定性。由于能量层切换时间主导着计划递送时间，减少能量层数对于提高递送效率很重要。尽管存在各种能量层优化（ELO）方法，但它们很少经过实验验证或临床应用，因为将这些方法集成到非开源的商用治疗计划系统（TPS）在技术上具有挑战性。
这项工作开发并通过实验验证了一种内部TPS（IH-TPS），该系统结合了一种新颖的ELO方法以实现快速IMPT。
根据测量的射束数据和RayStation TPS验证IH-TPS的剂量计算准确性。对于治疗计划，提出了一种通过贪婪选择算法的新颖ELO方法，以减少能量层切换时间和总计划递送时间。为了验证IH-TPS的计划准确性，在各种情况下计算IH-TPS计划和RayStation计划之间的3D伽马指数。针对几个临床病例进行患者特定的质量保证（QA）验证，以实验验证IH-TPS计划的递送剂量。
IH-TPS中的剂量分布与RayStation TPS中的剂量分布相匹配，3D伽马指数结果超过95%（2mm，2%）。ELO方法在保持计划质量的同时显著减少了递送时间。例如，在一个脑部病例中，能量层数从78层减少到40层，总递送时间减少了62%。使用IBA ProteusONE质子机器进行的患者特定QA验证证实所有病例的通过率>95%。
开发并通过实验验证了一种配备新颖ELO算法的IH-TPS，用于快速IMPT，提高了递送效率并保持了计划质量。
