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基于等效均匀剂量的放射治疗计划评估:纳入物理和蒙特卡罗统计剂量不确定性。

EUD-based radiotherapy treatment plan evaluation: incorporating physical and Monte Carlo statistical dose uncertainties.

作者信息

Cranmer-Sargison G, Zavgorodni S

机构信息

Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada.

出版信息

Phys Med Biol. 2005 Sep 7;50(17):4097-109. doi: 10.1088/0031-9155/50/17/013. Epub 2005 Aug 24.

Abstract

The purpose of this work is to quantify the impact of dose uncertainty on radiobiologically based treatment plan evaluation. Dose uncertainties are divided into two categories: physical and statistical. Physical dose uncertainty is associated with the systematic and/or random errors incurred during treatment planning and/or delivery. The dose uncertainty associated with Monte Carlo calculated dose distributions is deemed statistical and noted as artificial with respect to the actual delivered dose. We will refer to all dose uncertainties that arise from either calculation or delivery as stochastic. Both physical and statistical dose uncertainties are considered at the intra- and inter-voxel levels. To account for voxel dose uncertainty, we calculate the mean survival fraction (SF) for the random dose deposition. Mathematically, the expression for the mean survival fraction is identical to that used by Niemierko (1997 Med. Phys. 24 103-10) in defining equivalent uniform dose (EUD). To distinguish between spatial and probabilistic dose variations, we define equivalent stochastic dose (ESD) as a voxel dose that gives the mean expected survival fraction for the randomly deposited dose. For a probability density function f(D), that represents the probabilistic voxel dose, SF(ESD) can be calculated by convolving SF(D) with f(D). In the case where the probability density function follows a Gaussian distribution, an analytic expression is derived for SF(ESD). The derived expression is verified using the Monte Carlo method and ESD values calculated with varied radiosensitivities for cases of 60 and 70 Gy at 2 Gy per fraction. The analytic expression is also extended to account for a multi-voxel dose distribution that incorporates a spatial dose heterogeneity. The results show that survival fraction increases with an increased dose uncertainty. This reduction depends on radiobiological parameters attributed to tissue and tumour. For tissue, ESD drops to 55% of the mean physical dose when the dose has a 10% intra- and inter-voxel dose uncertainty and inhomogeneity.

摘要

这项工作的目的是量化剂量不确定性对基于放射生物学的治疗计划评估的影响。剂量不确定性分为两类:物理性和统计性。物理剂量不确定性与治疗计划和/或实施过程中产生的系统误差和/或随机误差相关。与蒙特卡罗计算的剂量分布相关的剂量不确定性被视为统计性的,相对于实际给予的剂量被视为人为的。我们将计算或实施过程中产生的所有剂量不确定性称为随机性的。物理和统计剂量不确定性在体素内和体素间水平都予以考虑。为了考虑体素剂量不确定性,我们计算随机剂量沉积的平均存活分数(SF)。从数学上讲,平均存活分数的表达式与Niemierko(1997年,《医学物理》24卷,103 - 10页)定义等效均匀剂量(EUD)时使用的表达式相同。为了区分空间和概率性剂量变化,我们将等效随机剂量(ESD)定义为能给出随机沉积剂量的平均预期存活分数的体素剂量。对于表示概率性体素剂量的概率密度函数f(D),SF(ESD)可通过将SF(D)与f(D)卷积来计算。在概率密度函数遵循高斯分布的情况下,推导了SF(ESD)的解析表达式。使用蒙特卡罗方法以及针对每次分割2 Gy、60 Gy和70 Gy的情况,用不同放射敏感性计算得到的ESD值对推导的表达式进行了验证。该解析表达式还被扩展以考虑包含空间剂量异质性的多体素剂量分布。结果表明,存活分数随剂量不确定性增加而增加。这种降低取决于归因于组织和肿瘤的放射生物学参数。对于组织,当剂量在体素内和体素间有10%的剂量不确定性和不均匀性时,ESD降至平均物理剂量的55%。

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