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利用蒙特卡罗模拟研究细胞群体中的能量沉积。

Investigating energy deposition within cell populations using Monte Carlo simulations.

机构信息

Carleton Laboratory for Radiotherapy Physics, Physics Dept, Carleton University, Ottawa, K1S 5B6, Canada.

出版信息

Phys Med Biol. 2018 Aug 1;63(15):155018. doi: 10.1088/1361-6560/aacf7b.

DOI:10.1088/1361-6560/aacf7b
PMID:29947613
Abstract

In this work, we develop multicellular models of healthy and cancerous human soft tissues, which are used to investigate energy deposition in subcellular targets, quantify the microdosimetric spread in a population of cells, and determine how these results depend on model details. Monte Carlo (MC) tissue models combining varying levels of detail on different length scales are developed: microscopically-detailed regions of interest (>1500 explicitly-modelled cells) are embedded in bulk tissue phantoms irradiated by photons (20 keV-1.25 MeV). Specific energy (z; energy imparted per unit mass) is scored in nuclei and cytoplasm compartments using the EGSnrc user-code egs_chamber; specific energy mean, [Formula: see text], standard deviation, [Formula: see text], and distribution, [Formula: see text], are calculated for a variety of macroscopic doses, D. MC-calculated [Formula: see text] are compared with normal distributions having the same mean and standard deviation. For  ∼mGy doses, there is considerable variation in energy deposition (microdosimetric spread) throughout a cell population: e.g. for 30 keV photons irradiating melanoma with 7.5 μm cell radius and 3 μm nuclear radius, [Formula: see text] for nuclear targets is [Formula: see text], and the fraction of nuclei receiving no energy deposition, f , is 0.31 for a dose of 10 mGy. If cobalt-60 photons are considered instead, then [Formula: see text] decreases to [Formula: see text], and f decreases to 0.036. These results correspond to randomly arranged cells with cell/nucleus sizes randomly sampled from a normal distribution with a standard deviation of 1 μm. If cells are arranged in a hexagonal lattice and cell/nucleus sizes are uniform throughout the population, then [Formula: see text] decreases to [Formula: see text] and [Formula: see text] for 30 keV and cobalt-60, respectively; f decreases to 0.25 and 0.000 94 for 30 keV and cobalt-60, respectively. Thus, specific energy distributions are sensitive to cell/nucleus sizes and their distributions: variations in specific energy deposited over a cell population are underestimated if targets are assumed to be uniform in size compared with more realistic variation in target size. Bulk tissue dose differs from [Formula: see text] for nuclei (cytoplasms) by up to [Formula: see text] ([Formula: see text]) across all cell/nucleus sizes, bulk tissues, and incident photon energies, considering a 50 mGy dose level. Overall, results demonstrate the importance of microdosimetric considerations at low doses, and indicate the sensitivity of energy deposition within subcellular targets to incident photon energy, dose level, elemental compositions, and microscopic tissue model.

摘要

在这项工作中,我们开发了健康和癌变人体软组织的多细胞模型,用于研究亚细胞靶区的能量沉积,量化细胞群体中的微剂量分布,并确定这些结果如何取决于模型细节。我们开发了结合不同长度尺度上不同细节水平的蒙特卡罗(MC)组织模型:用光子(20 keV-1.25 MeV)辐照的体模中嵌入了具有微观细节的感兴趣区域(>1500 个明确建模的细胞)。使用 EGSnrc 用户代码 egs_chamber 在核和细胞质隔室中记录特定能量(z;单位质量所赋予的能量);对于各种宏观剂量 D,计算特定能量均值[Formula: see text]、标准差[Formula: see text]和分布[Formula: see text]。MC 计算的[Formula: see text]与具有相同均值和标准差的正态分布进行比较。对于约为 mGy 的剂量,细胞群体中的能量沉积(微剂量分布)存在很大差异:例如,对于 30 keV 光子辐照具有 7.5 μm 细胞半径和 3 μm 核半径的黑色素瘤,核靶区的[Formula: see text]为[Formula: see text],并且没有接受任何能量沉积的核的分数 f 为 10 mGy 时为 0.31。如果考虑钴-60 光子,则[Formula: see text]降低到[Formula: see text],f 降低到 0.036。这些结果对应于随机排列的细胞,如果细胞/核尺寸从具有 1 μm 标准差的正态分布中随机抽样,则随机排列的细胞。如果细胞以六方晶格排列并且整个群体中的细胞/核尺寸均匀,则对于 30 keV 和钴-60,[Formula: see text]分别降低到[Formula: see text]和[Formula: see text];对于 30 keV 和钴-60,f 分别降低到 0.25 和 0.000 94。因此,特定能量分布对细胞/核尺寸及其分布敏感:与目标尺寸的实际变化相比,如果假设目标尺寸均匀,则细胞群体中沉积的特定能量分布会被低估。对于所有细胞/核尺寸、体模和入射光子能量,考虑 50 mGy 的剂量水平,体模剂量与核(细胞质)的[Formula: see text]差异最大可达[Formula: see text]。总体而言,结果表明在低剂量下微剂量考虑的重要性,并表明亚细胞靶区内能量沉积对入射光子能量、剂量水平、元素组成和微观组织模型的敏感性。

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