A Lim, M Andriotty, T Yusufaly, G Agasthya, B Lee, C Wang
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引用次数: 0
摘要
简介:我们开发了一种新方法,可大幅加快放射生物学蒙特卡洛辐射轨迹结构(MC-RTS)计算的速度:我们开发了一种新方法,可大大加快逐个细胞的放射生物学蒙特卡洛辐射轨迹结构(MC-RTS)计算速度:该技术基于随机抽样和单粒子轨道(SPT)标准 DNA 损伤(SDD)文件的叠加,这些文件来自使用 RTS 代码 TOPAS-nBio 构建的 "预计算 "数据文件库,并人工添加了 "时间戳 "以纳入剂量率效应。这种带有时间戳的 SDD 文件随后可输入 MEDRAS,这是一种机理动力学模型,可计算各种辐射诱导的生物终点,如 DNA 双链断裂(DSB)、错误修复和染色体畸变以及细胞死亡。作为该方法的基准验证,我们计算了预测的随能量变化的DSB产量和DNA直接损伤与总损伤之比,两者均与已发表的体外实验数据一致。随后,我们应用该方法对神经内分泌肿瘤细胞均匀培养 177Lu 的体外实验系统进行了逐个细胞的超快速模拟:辐照后24小时和48小时的残余DSB结果与已发表的文献值一致。我们的工作证明了经济有效的 "硅学克隆细胞存活测定 "的可行性,可用于放射性药物和新型放射治疗方法的计算设计和开发。
A fast Monte Carlo cell-by-cell simulation for radiobiological effects in targeted radionuclide therapy using pre-calculated single-particle track standard DNA damage data.
Introduction: We developed a new method that drastically speeds up radiobiological Monte Carlo radiation-track-structure (MC-RTS) calculations on a cell-by-cell basis.
Methods: The technique is based on random sampling and superposition of single-particle track (SPT) standard DNA damage (SDD) files from a "pre-calculated" data library, constructed using the RTS code TOPAS-nBio, with "time stamps" manually added to incorporate dose-rate effects. This time-stamped SDD file can then be input into MEDRAS, a mechanistic kinetic model that calculates various radiation-induced biological endpoints, such as DNA double-strand breaks (DSBs), misrepairs and chromosomal aberrations, and cell death. As a benchmark validation of the approach, we calculated the predicted energy-dependent DSB yield and the ratio of direct-to-total DNA damage, both of which agreed with published in vitro experimental data. We subsequently applied the method to perform a superfast cell-by-cell simulation of an experimental in vitro system consisting of neuroendocrine tumor cells uniformly incubated with 177Lu.
Results and discussion: The results for residual DSBs, both at 24 and 48 h post-irradiation, are in line with the published literature values. Our work serves as a proof-of-concept demonstration of the feasibility of a cost-effective "in silico clonogenic cell survival assay" for the computational design and development of radiopharmaceuticals and novel radiotherapy treatments more generally.