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不同离子存在缺氧条件下的离子束放射治疗中的肿瘤控制:基于微剂量动力学模型的氧增强比模型。

Tumour control in ion beam radiotherapy with different ions in the presence of hypoxia: an oxygen enhancement ratio model based on the microdosimetric kinetic model.

机构信息

Laboratory of Medical Physics and Expert Systems, National Cancer Institute Regina Elena, Roma, Italy.

出版信息

Phys Med Biol. 2018 Mar 16;63(6):065012. doi: 10.1088/1361-6560/aa89ae.

Abstract

Few attempts have been made to include the oxygen enhancement ratio (OER) in treatment planning for ion beam therapy, and systematic studies to evaluate the impact of hypoxia in treatment with the beam of different ion species are sorely needed. The radiobiological models used to quantify the OER in such studies are mainly based on the dose-averaged LET estimates, and do not explicitly distinguish between the ion species and fractionation schemes. In this study, a new type of OER modelling, based on the microdosimetric kinetic model, taking into account the specificity of the different ions, LET spectra, tissues and fractionation schemes, has been developed. The model has been benchmarked with published in vitro data, HSG, V79 and CHO cells in aerobic and hypoxic conditions, for different ion irradiation. The model has been included in the simulation of treatments for a clinical case (brain tumour) using proton, lithium, helium, carbon and oxygen ion beams. A study of the tumour control probability (TCP) as a function of oxygen partial pressure, dose per fraction and primary ion type has been performed. The modelled OER depends on both the LET and ion type, also showing a decrease for an increased dose per fraction with a slope that depends on the LET and ion type, in good agreement with the experimental data. In the investigated clinical case, a significant increase in TCP has been found upon increasing the ion charge. Higher OER variations as a function of dose per fraction have also been found for low-LET ions (up to 15% varying from 2 to 8 Gy(RBE) for protons). This model could be exploited in the identification of treatment condition optimality in the presence of hypoxia, including fractionation and primary particle selection.

摘要

很少有人尝试将氧增比(OER)纳入离子束治疗的计划中,并且非常需要系统地研究不同离子种类的光束治疗中缺氧的影响。用于量化这些研究中 OER 的放射生物学模型主要基于剂量平均 LET 估计,并且没有明确区分离子种类和分割方案。在这项研究中,开发了一种基于微剂量动力学模型的新型 OER 建模方法,该方法考虑了不同离子的特异性、LET 谱、组织和分割方案。该模型已经使用发表的体外数据、有氧和缺氧条件下的 HSG、V79 和 CHO 细胞进行了基准测试,用于不同离子的照射。该模型已被纳入使用质子、锂、氦、碳和氧离子束对临床病例(脑肿瘤)进行治疗的模拟中。研究了肿瘤控制概率(TCP)作为氧分压、每个分割剂量和初级离子类型的函数。模型化的 OER 取决于 LET 和离子类型,并且随着分割剂量的增加而降低,其斜率取决于 LET 和离子类型,与实验数据非常吻合。在所研究的临床病例中,随着离子电荷的增加,TCP 显著增加。还发现低 LET 离子的剂量分割与 OER 变化之间存在较大的相关性(对于质子,从 2 到 8 Gy(RBE),剂量分割从 2 到 8 Gy(RBE),变化高达 15%)。该模型可用于在存在缺氧的情况下识别治疗条件的最优性,包括分割和初级粒子选择。

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