Monte Carlo modeling in CT-based geometries: dosimetry for biological modeling experiments with particle beam radiation

The space radiation environment imposes increased dangers of exposure to ionizing radiation, particularly during a solar particle event (SPE). These events consist primarily of low energy protons that produce a highly inhomogeneous dose distribution. Due to this inherent dose heterogeneity, experiments designed to investigate the radiobiological effects of SPE radiation present difficulties in evaluating and interpreting dose to sensitive organs. To address this challenge, we used the Geant4 Monte Carlo simulation framework to develop dosimetry software that uses computed tomography (CT) images and provides radiation transport simulations incorporating all relevant physical interaction processes. We found that this simulation accurately predicts measured data in phantoms and can be applied to model dose in radiobiological experiments with animal models exposed to charged particle (electron and proton) beams. This study clearly demonstrates the value of Monte Carlo radiation transport methods for two critically interrelated uses: (i) determining the overall dose distribution and dose levels to specific organ systems for animal experiments with SPE-like radiation, and (ii) interpreting the effect of random and systematic variations in experimental variables (e.g. animal movement during long exposures) on the dose distributions and consequent biological effects from SPE-like radiation exposure. The software developed and validated in this study represents a critically important new tool that allows integration of computational and biological modeling for evaluating the biological outcomes of exposures to inhomogeneous SPE-like radiation dose distributions, and has potential applications for other environmental and therapeutic exposure simulations.     

Analysis of boron neutron capture reaction sensitivity using Monte Carlo simulation and proposal of a new dosimetry index in boron neutron capture therapy

Boron neutron capture therapy is a cellular-scale heavy-particle therapy. The factor determining the biological effects in the boron neutron capture reaction (BNCR) is the value of , which is the alpha component in the Linear Quadratic (LQ) model. Recently, the factor determining the value of has been revealed to correspond to the structural features of the tumor tissue. However, the relationship and mechanism have yet to be thoroughly studied. In this study, we simulated BNCR in tissues using the Monte Carlo simulation technique and examined the factors that determine the value of . According to this simulation, the nuclear-cytoplasmic (N/C) ratio, nuclear diameter and heterogeneity of the distribution of boron in the tissue have been suggested to determine the value of . Moreover, we proposed Biological Effectivity (BE) as a new dosimetry index based on the surviving fraction (SF), extending the concept of absolute biological effectiveness (ABE) in a previous report.     

蒙特卡罗治疗计划系统MMCTP的临床评估

目的:研究McGill大学开发的蒙特卡罗治疗计划系统MMCTP(McGill Monte Carlo treatment planning system)用于临床剂量学研究的可行性.方法:选取某院2012年6月至2016年12月采用RapidArc加速器治疗的40例患者,按照治疗部位分为头部组、胸部组、腹部组和盆腔组,...     

Computational toxicology of chloroform: reverse dosimetry using Bayesian inference, Markov chain Monte Carlo simulation, and human biomonitoring data

BACKGROUND: One problem of interpreting population-based biomonitoring data is the reconstruction of corresponding external exposure in cases where no such data are available. OBJECTIVES: We demonstrate the use of a computational framework that integrates physiologically based pharmacokinetic (PBPK) modeling, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of environmental chloroform source concentrations consistent with human biomonitoring data. The biomonitoring data consist of chloroform blood concentrations measured as part of the Third National Health and Nutrition Examination Survey (NHANES III), and for which no corresponding exposure data were collected. METHODS: We used a combined PBPK and shower exposure model to consider several routes and sources of exposure: ingestion of tap water, inhalation of ambient household air, and inhalation and dermal absorption while showering. We determined posterior distributions for chloroform concentration in tap water and ambient household air using U.S. Environmental Protection Agency Total Exposure Assessment Methodology (TEAM) data as prior distributions for the Bayesian analysis. RESULTS: Posterior distributions for exposure indicate that 95% of the population represented by the NHANES III data had likely chloroform exposures < or = 67 microg/L [corrected] in tap water and < or = 0.02 microg/L in ambient household air. CONCLUSIONS: Our results demonstrate the application of computer simulation to aid in the interpretation of human biomonitoring data in the context of the exposure-health evaluation-risk assessment continuum. These results should be considered as a demonstration of the method and can be improved with the addition of more detailed data.     

利用Geant4计算生物样品照射时的剂量差异

目的 评估生物样品照射时,容器中间位置处剂量与容器内溶液总体剂量的差异。方法 利用Geant4程序模拟4种照射模式下,容器内的中心处剂量和容器内溶液总剂量,并计算两者的比值。 结果 容器中心处剂量与溶液总体剂量的比值与射线能量、容器大小以及照射方式紧密相关。 结论 生物样品照射实验时,应该根据现有条件选择合适的容器、射线以及照射模式以便中心剂量与总体剂量近似相等。     

Propensity scores used for analysis of cluster randomized trials with selection bias: a simulation study

Cluster randomized trials (CRTs) are often prone to selection bias despite randomization. Using a simulation study, we investigated the use of propensity score (PS) based methods in estimating treatment effects in CRTs with selection bias when the outcome is quantitative. Of four PS‐based methods (adjustment on PS, inverse weighting, stratification, and optimal full matching method), three successfully corrected the bias, as did an approach using classical multivariable regression. However, they showed poorer statistical efficiency than classical methods, with higher standard error for the treatment effect, and type I error much smaller than the 5% nominal level. Copyright © 2013 John Wiley & Sons, Ltd.     

基于MonteCarlo方法的放射治疗剂量分布计算方法的研究

本文应用MonteCarlo方法模拟粒子在生物组织中的输运过程，对肿瘤介入治疗常用源^125I的剂量场分布进行了研究，计算了^125I点源和点源阵列辐射的辐射场分布，对于放射治疗的临床应用具有重要的意义。     

相关生物学研究在HIE发病及其预后的意义

缺血缺氧性脑病是新生儿期以后造成伤残儿童的主要原因之一。近几年大量生物学研究证实 ,脑缺氧缺血后可激活一系列分子反应 ,目前已知脑缺氧缺血后可引起神经元内多种即刻早基因表达增强 ,诱发或阻止神经元死亡 ;同时也发现神经细胞受损过程有多种细胞因子、神经介质蛋白释放 ,可在早期反映脑操作程度。因此相关生物学研究结果对判断HIE程度与预后 ,以及干预治疗有着十分重要意义。     

Characterization of a new commercial single crystal diamond detector for photon- and proton-beam dosimetry

A synthetic single crystal diamond detector (SCDD) is commercially available and is characterized for radiation dosimetry in various radiation beams in this study. The characteristics of the commercial SCDD model 60019 (PTW) with 6- and 15-MV photon beams, and 208-MeV proton beams, were investigated and compared with the pre-characterized detectors: Semiflex (model 31010) and PinPoint (model 31006) ionization chambers (PTW), the EDGE diode detector (Sun Nuclear Corp) and the SFD Stereotactic Dosimetry Diode Detector (IBA). To evaluate the effects of the pre-irradiation, the diamond detector, which had not been irradiated on the day, was set up in the water tank, and the response to 100 MU was measured every 20 s. The depth–dose and profiles data were collected for various field sizes and depths. For all radiation types and field sizes, the depth–dose data of the diamond chamber showed identical curves to those of the ionization chambers. The profile of the diamond detector was very similar to those of the EDGE and SFD detectors, although the Semiflex and PinPoint chambers showed volume-averaging effects in the penumbrae region. The temperature dependency was within 0.7% in the range of 4–41°C. A dose of 900 cGy and 1200 cGy was needed to stabilize the chamber to the level within 0.5% and 0.2%, respectively. The PTW type 60019 SCDD detector showed suitable characteristics for radiation dosimetry, for relative dose, depth–dose and profile measurements for a wide range of field sizes. However, at least 1000 cGy of pre-irradiation will be needed for accurate measurements.     

To pool or not to pool, from whether to when: applications of pooling to biospecimens subject to a limit of detection

Pooling of biological specimens has been utilised as a cost-efficient sampling strategy, but cost is not the unique limiting factor in biomarker development and evaluation. We examine the effect of different sampling strategies of biospecimens for exposure assessment that cannot be detected below a detection threshold (DT). The paper compares use of pooled samples to a randomly selected sample from a cohort in order to evaluate the efficiency of parameter estimates.
The proposed approach shows that a pooling design is more efficient than a random sample strategy under certain circumstances. Moreover, because pooling minimises the amount of information lost below the DT, the use of pooled data is preferable (in a context of a parametric estimation) to using all available individual measurements, for certain values of the DT. We propose a combined design, which applies pooled and unpooled biospecimens, in order to capture the strengths of the different sampling strategies and overcome instrument limitations (i.e. DT). Several Monte Carlo simulations and an example based on actual biomarker data illustrate the results of the article.     

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