A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies
A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies
复制标题
用于带电粒子放射生物学研究的基于机械论相对生物学效应模型的生物剂量优化
DOI：
10.1088/1361-6560/aaf5df
复制
发表时间：
2019-01-01
影响因子：
3.5
通讯作者：
Mohan, Radhe
中科院分区：
文献类型：
--
作者：
Guan, Fada;Geng, Changran;Mohan, Radhe
在带电粒子治疗中，目标是利用带电粒子的物理和放射生物学优势来提高治疗指标。使用光束扫描技术提供了实施生物剂量优化调强离子治疗（IMIT）的灵活性。本研究开发了一种易于实现的算法，利用扫描离子束在靶体积内快速生成均匀的生物剂量分布，即物理剂量与相对生物有效性（RBE）的乘积，用于带电粒子放射生物学研究。选择质子、氦离子和碳离子来证明我们方法的可行性和灵活性。通用蒙特卡罗模拟工具包Geant4用于粒子跟踪和生成后续剂量优化所需的物理和放射生物学数据。使用Python （version 3）编程语言开发剂量优化算法。选取恒定rbe加权剂量（RWD）扩散布拉格峰（SOBP）作为期望的目标剂量分布，以验证优化算法的适用性。将机械修复-错误修复-固定（RMF）模型引入到蒙特卡罗粒子跟踪中生成放射生物学参数，并用于预测三种选定离子在生物剂量优化迭代过程中细胞存活的RBE。优化后生成的束流输送策略可用于辐射生物学实验，获取辐射生物学数据，进一步验证和提高RBE模型的准确性。这种为放射生物学研究开发的生物剂量优化算法有可能被扩展到为患者实施生物优化的IMIT计划。
In charged particle therapy, the objective is to exploit both the physical and radiobiological advantages of charged particles to improve the therapeutic index. Use of the beam scanning technique provides the flexibility to implement biological dose optimized intensity-modulated ion therapy (IMIT). An easy-to-implement algorithm was developed in the current study to rapidly generate a uniform biological dose distribution, namely the product of physical dose and the relative biological effectiveness (RBE), within the target volume using scanned ion beams for charged particle radiobiological studies. Protons, helium ions and carbon ions were selected to demonstrate the feasibility and flexibility of our method. The general-purpose Monte Carlo simulation toolkit Geant4 was used for particle tracking and generation of physical and radiobiological data needed for later dose optimizations. The dose optimization algorithm was developed using the Python (version 3) programming language. A constant RBE-weighted dose (RWD) spread-out Bragg peak (SOBP) in a water phantom was selected as the desired target dose distribution to demonstrate the applicability of the optimization algorithm. The mechanistic repair-misrepair-fixation (RMF) model was incorporated into the Monte Carlo particle tracking to generate radiobiological parameters and was used to predict the RBE of cell survival in the iterative process of the biological dose optimization for the three selected ions. The post-optimization generated beam delivery strategy can be used in radiation biology experiments to obtain radiobiological data to further validate and improve the accuracy of the RBE model. This biological dose optimization algorithm developed for radiobiology studies could potentially be extended to implement biologically optimized IMIT plans for patients.