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早期一代动态和静态质子弧形治疗计划算法在口咽癌患者中的评估

Early generation dynamic and static proton arc treatment planning algorithms assessment in oropharyngeal cancer patients.

作者信息

De Jong Bas Adriaan, Zhao Lewei, Liu Peilin, Wase Viktor, Marthin Otte, Sundström Johan, Liu Gang, Deroniyagala Rohan, Li Xiaoqiang, Cong Xiaoda, Janssens Guillaume, Engwall Erik, Korevaar Erik W, Ding Xuanfeng, Langendijk Johannes Albertus, Both Stefan

机构信息

Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Department of Radiation Oncology, Stanford University, Palo Alto, California, USA.

出版信息

Med Phys. 2025 Jul;52(7):e17916. doi: 10.1002/mp.17916.

Abstract

BACKGROUND

Compared with intensity modulated proton therapy (IMPT), proton arc treatment (PAT) employs an increased number of gantry angles, potentially reducing healthy tissues doses, especially for complex target geometries found in oropharyngeal cancer (OPC) treatment. PAT plans can be optimized with algorithms, based either on "static" gantry position or "dynamic" gantry movement during dose delivery. Recent results have shown target coverage may suffer more from inter-fraction patient anatomical- and setup changes In PAT than IMPT.

PURPOSE

We assessed if PAT plans generated with one static and two dynamic PAT planning algorithms can improve expected plan toxicity, delivery time, and inter-fraction robustness compared to clinical volumetric modulated arc therapy (VMAT) and IMPT plans for OPC patients.

METHODS

Six OPC patients were included that qualified for proton therapy based on model-based selection, with IMPT plans superior to the VMAT plans in terms of toxicities. Static PAT plans were produced using an energy layer filtration (ELF) algorithm, and dynamic PAT plans were produced with two different methods: (1) Spot scanning Proton Arc (SPArc), and (2) Early Layer and Spot Assignment (ELSA). Two sets of PAT plans with about 360 or 240 energy layers and an additional ELF plan employing anterior oblique range shifted fields were produced. All proton plans were robustly optimized. Expected plan toxicity was determined using normal tissue complication probability (NTCP) models for dysphagia and xerostomia. A delivery time model was calibrated using experimental machine log-files and gantry dynamics from an IBA Proteus PLUS system (IBA Ltd, Belgium). Inter-fraction robustness was evaluated on a fraction-wise (on weekly repeated CT) and course-wise (accumulated over all weekly repeated CTs) basis.

RESULTS

All PAT strategies showed significantly (p-values < 0.05) reduced NTCPs for dysphagia and xerostomia grade ≥ 2 compared to IMPT and VMAT. Relative to VMAT, NTCP for xerostomia reduced by on average 4.0% in IMPT plans, 9.8% in ELF-, 9.6% in SPArc-, and 8.7% in ELSA PAT plans with 360 energy layers, and NTCP for dysphagia reduced by on average 9.6% in IMPT plans, 13.1% in ELF, 12.9% in SPArc, and 12.3% in ELSA PAT plans. Average clinical IMPT delivery time was 11.4 ± 2.1 min, while dynamic PAT delivery time was on average 7.6 ± 0.5 min for ELSA and 8.2 ± 0.5 min for SPArc plans with 360 energy layers and auto beam sequencing delivery for 360 energy layer 30 beam angle ELF plans was 9.9 ± 1.0 min. Reduction of energy layers to 240 resulted in limited NTCP increase, globally < 1%, and reduced delivery time by up to 3 min, where changes in delivery time and NTCP were largest in ELF plans. Fraction-wise target coverage was worse in the PAT plans compared to IMPT; however the course-wise coverage showed to be less impacted by inter-fraction changes. The addition of anterior oblique fields with range shifters markedly improved fraction- and course-wise target coverage for the ELF plans.

CONCLUSIONS

The tested static and dynamic PAT planning strategies showed similar significant reductions in NTCP compared to IMPT and VMAT. Estimated PAT delivery times were shorter compared to times for current delivery procedures of clinical IMPT plans. Dynamic PAT delivery is faster than static PAT. Fraction-wise robustness suffered more than course-wise robustness due to anatomical changes found in repeated CTs. Range shifters can be employed to improve PAT plan robustness.

摘要

背景

与调强质子治疗(IMPT)相比,质子弧形治疗(PAT)采用了更多的机架角度,有可能降低健康组织的剂量,特别是对于口咽癌(OPC)治疗中发现的复杂靶区几何形状。PAT计划可以通过算法进行优化,这些算法基于剂量输送过程中的“静态”机架位置或“动态”机架运动。最近的结果表明,与IMPT相比,PAT中患者分次间的解剖结构和摆位变化可能对靶区覆盖产生更大影响。

目的

我们评估了与OPC患者的临床容积调强弧形治疗(VMAT)和IMPT计划相比,使用一种静态和两种动态PAT计划算法生成的PAT计划是否能改善预期的计划毒性、输送时间和分次间稳健性。

方法

纳入6例基于模型选择符合质子治疗条件的OPC患者,其IMPT计划在毒性方面优于VMAT计划。使用能量层过滤(ELF)算法生成静态PAT计划,并使用两种不同方法生成动态PAT计划:(1)点扫描质子弧形(SPArc),以及(2)早期层和点分配(ELSA)。生成了两组具有约360或240个能量层的PAT计划,以及一个采用前斜野范围移位的额外ELF计划。所有质子计划均进行了稳健优化。使用吞咽困难和口干的正常组织并发症概率(NTCP)模型确定预期计划毒性。使用来自IBA Proteus PLUS系统(比利时IBA有限公司)的实验机器日志文件和机架动力学校准输送时间模型。在分次层面(每周重复CT)和疗程层面(所有每周重复CT累积)评估分次间稳健性。

结果

与IMPT和VMAT相比,所有PAT策略在吞咽困难和≥2级口干的NTCP方面均显著降低(p值<0.05)。相对于VMAT,IMPT计划中口干的NTCP平均降低4.0%,ELF计划中降低9.8%,SPArc计划中降低9.6%,360个能量层的ELSA PAT计划中降低8.7%;吞咽困难的NTCP在IMPT计划中平均降低9.6%,ELF计划中降低13.1%,SPArc计划中降低12.9%,ELSA PAT计划中降低12.3%。临床IMPT的平均输送时间为11.4±2.1分钟,而对于360个能量层的ELSA计划,动态PAT输送时间平均为7.6±0.5分钟,SPArc计划为8.2±0.5分钟,360个能量层、30个射野角度的ELF计划采用自动束流排序输送时为9.9±1.0分钟。将能量层数减少到240导致NTCP增加有限,总体<1%,并使输送时间最多减少3分钟,其中ELF计划中输送时间和NTCP的变化最大。与IMPT相比,PAT计划中分次层面的靶区覆盖较差;然而,疗程层面的覆盖受分次间变化的影响较小。添加带有范围移位器的前斜野显著改善了ELF计划的分次和疗程层面的靶区覆盖。

结论

与IMPT和VMAT相比,测试的静态和动态PAT计划策略在NTCP方面均有显著类似降低。与临床IMPT计划的当前输送程序时间相比,估计的PAT输送时间更短。动态PAT输送比静态PAT更快。由于在重复CT中发现的解剖结构变化,分次层面的稳健性比分次疗程层面的稳健性受到的影响更大。可以采用范围移位器来提高PAT计划的稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0fc/12260774/7cac2893add9/MP-52-0-g004.jpg

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