基于质子 ARC 的 LATTICE 放射治疗:可行性研究、能量层优化和 LET 优化。

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL Physics in medicine and biology Pub Date : 2024-10-25 DOI:10.1088/1361-6560/ad8855
Ya-Nan Zhu, Weijie Zhang, Jufri Setianegara, Yuting Lin, Erik Traneus, Yong Long, Xiaoqun Zhang, Rajeev Badkul, David Akhavan, Fen Wang, Ronald C Chen, Hao Gao
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引用次数: 0

摘要

目标:这项工作将通过质子 ARC(多射束角)开发新型质子 LATTICE 方法,以克服在靶点覆盖和 OAR 疏导方面的这些挑战,并通过能量层优化和 LET 优化来优化输送效率和生物剂量分布,从而实现质子 LATTICE 的临床应用:基于 ARC 的质子 LATTICE 是通过能量层优化来制定和求解的,在此过程中,计划质量和输送效率得到了共同优化。特别是,在计划优化过程中,对能量跳跃次数(NEJ)进行了明确建模和最小化,以提高投放效率,同时优化目标剂量符合性和 OAR 剂量目标。通过考虑最小监测单元(MMU)约束来确保计划的可投放性,并使用稳健优化来考虑计划的稳健性。生物剂量通过 LET 优化进行优化。优化求解算法采用迭代凸松弛法来处理剂量-体积约束和最小监测单元约束,并通过近似下降法解决定点重量优化子问题:与基于 IMPT 的质子 LATTICE 相比,基于 ARC 的质子 LATTCE 大幅提高了计划质量。能量层优化提高了基于 ARC 的质子 LATTICE 的计划交付效率:与 IMPT 相比,质子 ARC 大幅提高了靶剂量覆盖率和 OAR 损伤清除率,证明了通过质子 ARC 实现高质量质子 LATTICE 计划的可行性,同时可以通过能量层优化来优化基于 ARC 的质子 LATTICE 的计划传输效率。
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Proton ARC based LATTICE radiation therapy: feasibility study, energy layer optimization and LET optimization.

Objective.LATTICE, a spatially fractionated radiation therapy (SFRT) modality, is a 3D generalization of GRID and delivers highly modulated peak-valley spatial dose distribution to tumor targets, characterized by peak-to-valley dose ratio (PVDR). Proton LATTICE is highly desirable, because of the potential synergy of the benefit from protons compared to photons, and the benefit from LATTICE compared to GRID. Proton LATTICE using standard proton RT via intensity modulated proton therapy (IMPT) (with a few beam angles) can be problematic with poor target dose coverage and high dose spill to organs-at-risk (OAR). This work will develop novel proton LATTICE method via proton ARC (with many beam angles) to overcome these challenges in target coverage and OAR sparing, with optimized delivery efficiency via energy layer optimization and optimized biological dose distribution via linear energy transfer (LET) optimization, to enable the clinical use of proton LATTICE.Approach.ARC based proton LATTICE is formulated and solved with energy layer optimization, during which plan quality and delivery efficiency are jointly optimized. In particular, the number of energy jumps (NEJ) is explicitly modelled and minimized during plan optimization for improving delivery efficiency, while target dose conformality and OAR dose objectives are optimized. The plan deliverability is ensured by considering the minimum-monitor-unit (MMU) constraint, and the plan robustness is accounted for using robust optimization. The biological dose is optimized via LET optimization. The optimization solution algorithm utilizes iterative convex relaxation method to handle the dose-volume constraint and the MMU constraint, with spot-weight optimization subproblems solved by proximal descent method.Main results.ARC based proton LATTCE substantially improved plan quality from IMPT based proton LATTICE, such as (1) improved conformity index (CI) from 0.47 to 0.81 for the valley target dose and from 0.62 to 0.97 for the peak target dose, (2) reduced esophagus dose from 0.68 Gy to 0.44 Gy (a 12% reduction with respect to 2 Gy valley prescription dose) and (3) improved PVDR from 4.15 to 4.28 in the lung case. Moreover, energy layer optimization improved plan delivery efficiency for ARC based proton LATTICE, such as (1) reduced NEJ from 71 to 56 and (2) reduction of energy layer switching time by 65% and plan delivery time by 52% in the lung case. The biological target and OAR dose distributions were further enhanced via LET optimization. On the other hand, proton ARC LATTCE also substantially improved plan quality from VMAT LATTICE, such as (1) improved CI from 0.45 to 0.81 for the valley target dose and from 0.63 to 0.97 for the peak target dose, (2) reduced esophagus dose from 0.59 Gy to 0.38 Gy (a 10.5% reduction with respect to 2 Gy valley prescription dose) and (3) improved PVDR from 3.88 to 4.28 in the lung case.Significance.The feasibility of high-plan-quality proton LATTICE is demonstrated via proton ARC with substantially improved target dose coverage and OAR sparing compared to IMPT, while the plan delivery efficiency for ARC based proton LATTICE can be optimized using energy layer optimization.

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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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