A systematic characterization of plastic scintillation dosimeters response in magnetic fields: II. Monte Carlo simulations.

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Yunuen Cervantes, Simon Lambert-Girard, Ilias Billas, François Therriault-Proulx, Hugo Bouchard, Louis Archambault, Luc Beaulieu
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引用次数: 0

Abstract

Purpose.This study aims to investigate and validate the response of plastic scintillation dosimeters (PSDs) in the presence of magnetic fields using Monte Carlo simulations, focusing on the accuracy of electron fluence, dose calculations, and the optical processes of scintillation and Cherenkov radiation.Methods.Monte Carlo simulations, using EGSnrc and TOPAS, of the PSD response under magnetic fields were performed. First, electron fluence simulations were conducted with three different physics listsg4em-penelope,g4em-standard_opt3andg4em-standard_opt4, with the goal of benchmarking their performance in magnetic fields. Secondly, a Fano test for dose calculations was performed using only theg4em-penelopephysics list. Thirdly, the Cherenkov process under magnetic fields was validated against theoretical predictions. Finally, a PSD probe was modeled and simulated, with results compared against measurements.Results.Theg4em-penelopephysics list demonstrated a most balanced performance, showing the closest agreement with EGSnrc simulations and lower variability in magnetic fields thang4em-standard_opt4. Fano test results showed an accuracy of at least 0.36% for dose calculations. Simulations of Cherenkov radiation in ideal conditions were in agreement with theoretical predictions at both 0 T and 1.5 T. Monte Carlo simulations successfully reproduced experimental trends for Cherenkov radiation under magnetic fields. However, discrepancies were found, with deviations of up to 7.7% when electrons were deflected towards the tip and up to 21.0% in the opposite direction, likely due to modeling limitations. A key result is that Monte Carlo simulations of the scintillation process in magnetic fields failed to reproduce experimental observations. While experimental results showed a significant effect of magnetic fields on scintillation yield, the simulations did not reflect this behavior.Conclusion.This study establishes that TOPAS, specifically using theg4em-penelopephysics list, is a reliable tool for simulating dose, electron fluence, and Cherenkov radiation in the presence of magnetic fields. However, significant discrepancies were observed in the scintillation processes, where Monte Carlo simulations failed to reproduce the effect of magnetic fields seen in experimental measurements. These findings point out the need for further refinement of simulation models, particularly in accurately representing scintillation under magnetic fields.

塑料闪烁剂量计在磁场中响应的系统表征:II。蒙特卡罗模拟。
目的。本文利用蒙特卡罗模拟方法研究和验证了塑料闪烁剂量计(PSD)在磁场作用下的响应,重点研究了电子影响、剂量计算以及闪烁和切伦科夫辐射的光学过程的准确性。方法:利用EGSnrc和TOPAS对PSD在磁场作用下的响应进行了蒙特卡罗模拟。首先,采用三种不同的物理列表(g4em-penelope、g4em-standard_opt3和g4em-standard_opt4)进行了电子影响模拟,以测试它们在磁场中的性能。其次,仅使用g4em-penelopephysics列表进行剂量计算的Fano测试。第三,与理论预测相比,验证了磁场作用下的切伦科夫过程。最后,对PSD探针进行了建模和仿真,并将结果与测量结果进行了比较。g4em- penelopophysics表表现出最平衡的性能,显示出与EGSnrc模拟最接近的一致性,并且磁场变异性比ang4em-standard_opt4更低。Fano试验结果表明,剂量计算精度至少为0.36%。切伦科夫辐射在理想条件下的模拟与0 T和1.5 T的理论预测一致。蒙特卡罗模拟成功地再现了切伦科夫辐射在磁场下的实验趋势。然而,发现了差异,当电子向尖端偏转时偏差高达7.7%,相反方向偏差高达21.0%,可能是由于建模限制。一个关键的结果是,蒙特卡罗模拟的闪烁过程在磁场未能再现实验观测。实验结果表明,磁场对闪烁率有显著影响,但模拟并没有反映这种行为。结论:本研究建立了TOPAS,特别是使用g4em-penelopephysics表,是模拟磁场存在下的剂量、电子影响和切伦科夫辐射的可靠工具。然而,在闪烁过程中观察到显著的差异,其中蒙特卡罗模拟未能再现实验测量中看到的磁场效应。这些发现指出需要进一步改进模拟模型,特别是在准确表示磁场下的闪烁方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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