Monte Carlo track structure applications in microdosimetry and radiation response

在放射治疗中，电离辐射被用来对DNA造成不可修复的损伤，并抑制癌细胞的细胞周期。叠加在DNA模型上的粒子轨迹表明，损伤发生在簇中。这些聚集的DNA损伤是电离辐射引起的标志性DNA损伤。生物对辐射的反应是用相对生物有效性(RBE)来量化的，其定义是给定生物终点的参考辐射的吸收剂量与测试辐射的吸收剂量之间的比率。低能量的近距离照射源、质子和离子束与高的RBE值有关。对初始DNA损伤的许多模拟表明，以DNA片段为代表的体积中电离或能量的频率分布对于考虑辐射质量和模拟电离辐射造成的生物损伤是有用的。蒙特卡罗(MC)方法是模拟人体等非均质系统中辐射输运和能量沉积的一种精确而严谨的工具。轨道结构代码是一类特殊的MC传输代码，它可以通过逐个事件地模拟粒子相互作用，生成详细的能量沉积点的空间图案。*这项建议的目的是通过详细研究不同辐射质量引起的电离和激发模式，增加对不同放射和肿瘤细胞类型组合以及正常组织的不同RBE背后的机制的了解，以获得与传统放射治疗相同的对低能光子发射近距离照射源、质子和粒子治疗的信心和控制。分析将与不同细胞系和辐射质量的观测辐射响应相结合，并将在已知和受控的物理束特性与临床观测的辐射响应参数之间建立基于证据的联系。在治疗计划中使用这种模型，临床医生可以更好地选择和优化每个患者的放射类型和剂量分布。*目标A：使用早期研究中开发的方法，调查由于组织样本中细胞及其核的大小不同，每个细胞所传递的能量的微剂量学变化是否会对实验确定的细胞存活曲线和肿瘤控制概率产生影响。*目标B：开发和使用轨道结构代码，以寻找能量沉积位置簇的顺序的频率分布之间的关系，作为辐射影响的描述符，以及针对各种辐射质量的细胞存活的RBE。将开发一种方法，根据从光子获得的剂量反应数据来预测低能光子、质子和其他离子的RBE值，并将其纳入放射治疗计划。**

In radiation therapy ionizing radiation is used to cause irreparable damage to the DNA and inhibit cell cycling of the cancer cells. Particle tracks superimposed on models of DNA indicate that damage occurs in clusters. These clustered DNA damages are the signature DNA lesion induced by ionizing radiation. The biological response to radiation is quantified in terms of the relative biological effectiveness (RBE), defined as the ratio between the absorbed dose of a reference radiation and that of a test radiation for a given biological endpoint. Low energy brachytherapy sources, proton and ion beams are associated with high RBE values. Numerous simulations of initial DNA damage suggest that the frequency distributions for ionisation or energy imparted in volumes representative of DNA segments are useful for considering radiation quality and for modelling biological damage produced by ionising radiation. ***Monte Carlo (MC) method is an accurate and rigorous tool to simulate radiation transport and score energy deposition in heterogeneous systems such as the human body. Track structure codes are a specific class of MC transport codes that can generate in detail the spatial pattern of energy deposit sites due to the event-by-event simulation of particle interactions. ******The aim of this proposal is to increase the knowledge about the mechanisms behind the varying RBE for different combinations of radiation and tumour cell types and normal tissues by studying in detail the ionization and excitation patterns caused by different radiation qualities, in order to gain the same confidence and control for low energy photon emitting brachytherapy sources, proton and particle therapy as for conventional radiation therapy. The analysis will be combined with observed radiation responses for different cell lines and radiation qualities, and an evidence based link between well-known and controlled physical beam properties and clinically observed radiation response parameterizations will be established. With such models in treatment planning, the clinicians can better choose and optimize the type of radiation and dose distribution for each patient. ***Aim A: Use methods developed in an earlier study to investigate if the microdosimetric variation of energy imparted per cell, due to the different size of the cells and their nuclei within a tissue sample, have an impact on experimentally determined cell survival curves and tumour control probability. ***Aim B: Develop and use track structure codes to search for a relationship between frequency distribution of order of clusters of energy deposit sites, as a descriptor of radiation impact, and RBE for cell survival for various radiation qualities. A method for predicting RBE values for low energy photons, protons and other ions on the basis of dose-response data obtained from photons will be developed and included in radiation therapy treatment plans. **