A method for converting dose-to-medium to dose-to-tissue in Monte Carlo studies of gold nanoparticle-enhanced radiotherapy

A method for converting dose-to-medium to dose-to-tissue in Monte Carlo studies of gold nanoparticle-enhanced radiotherapy
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DOI:
10.1088/0031-9155/61/5/2014
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发表时间:
2016-03-07
影响因子:
3.5
通讯作者:
Kirkby, C.
Kirkby, C.
中科院分区:
工程技术2区
文献类型:
--
作者:
Koger, B.;Kirkby, C.

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近年来,金纳米颗粒 (GNP) 作为放射治疗中增加治疗剂量的一种手段显示出潜力。然而,走向临床实施的一个主要挑战是它们提供的剂量增强的确切特征。蒙特卡罗研究试图探索这一特性,但它们在检查宏观场景时经常面临计算限制。在这项研究中,建立了一种将宏观模拟剂量(介质定义为含有金和组织成分的混合物)转换为微观尺度上组织的平均剂量的方法。对组织中明确建模的 GNP 以及组织和金的均匀混合物进行了蒙特卡罗模拟。获得剂量比,用于将每种情况下混合介质中评分的剂量转换为组织剂量。光子源的剂量比为 0.69 至 1.04,电子源的剂量比为 0.97 至 1.03。剂量比高度依赖于源能量以及 GNP 直径和浓度,尽管这种效应对于电子源来说不太明显。通过对获得的单能剂量比进行适当加权,可以确定任意光谱的剂量比。这允许对复杂的场景进行精确建模,而无需显式模拟每个单独的国民生产总值。
Gold nanoparticles (GNPs) have shown potential in recent years as a means of therapeutic dose enhancement in radiation therapy. However, a major challenge in moving towards clinical implementation is the exact characterisation of the dose enhancement they provide. Monte Carlo studies attempt to explore this property, but they often face computational limitations when examining macroscopic scenarios. In this study, a method of converting dose from macroscopic simulations, where the medium is defined as a mixture containing both gold and tissue components, to a mean dose-to-tissue on a microscopic scale was established. Monte Carlo simulations were run for both explicitly-modeled GNPs in tissue and a homogeneous mixture of tissue and gold. A dose ratio was obtained for the conversion of dose scored in a mixture medium to dose-to-tissue in each case. Dose ratios varied from 0.69 to 1.04 for photon sources and 0.97 to 1.03 for electron sources. The dose ratio is highly dependent on the source energy as well as GNP diameter and concentration, though this effect is less pronounced for electron sources. By appropriately weighting the monoenergetic dose ratios obtained, the dose ratio for any arbitrary spectrum can be determined. This allows complex scenarios to be modeled accurately without explicitly simulating each individual GNP.