用蒙特卡罗概率方法研究正电子与人体某些器官的相互作用

Zaheer S. Mohammad, J. Abda
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引用次数: 1

摘要

在本研究中,对氢(H)、碳(C)、氮(N)、氧(O)、磷(P)、硫(S)、氯(Cl)、钾(K)和碘(I)等元素的平均自由程和正电子弹性-非弹性散射进行了建模。尽管需要大量的数据,但应用了蒙特卡罗(MC)方法,可以非常精确地模拟活细胞中正电子相互作用碰撞。本文报道了正电子与乳腺、肝脏和甲状腺在正常入射角下相互作用的MC模拟,能量范围从45 eV到0.2 MeV。该模型为正电子散射的随机抽样提供了一个直观的解析公式。采用ICRU44进行元素组成数据的编制。本文研究了人体组织中正电子相互作用的弹性截面(ECS)和非弹性截面(ICS)。弹性散射由卢瑟福微分截面得到。Gryzinski的激发函数在第一生近似中用于确定ICS的核心和价态。结果用图形表示。当散射能量接近零时,ECS迅速增加,并与器官中元素的原子序数有关。ICS已达到100 eV左右的最大值。正电子能量的增加导致弹性和非弹性平均自由程的增加。模拟结果与许多其他研究结果一致,这些研究处理了相同的参数和条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Positron Interactions with Some Human Body Organs Using Monte Carlo Probability Method
In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this work, elastic cross sections (ECS) and inelastic cross-sections (ICS) for positron interaction in human tissues were studied. The elastic scattering is obtained from the Rutherford differential cross-section. Gryzinski's excitation function is used within the first-born approximation to determine the core and valence of ICS. The results are presented graphically. The ECS increases rapidly as the scattering energy approaches zero and becomes dependent on the atomic number of elements in organs. The ICS has reached a maximum value of around 100 eV. Increasing positron energy leads to an increase in the elastic and inelastic mean free paths. The simulations agree with many other studies dealing with the same parameters and conditions.
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