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A simulation to tissue homogeneity model for capillary of brain by statistical method

机译:用统计方法模拟脑毛细血管组织均匀性模型

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Analytical methods for solving adiabatic equations with non-uniform permeability and real arterial input function (AIF) are complicated. We consider crossing of contrast agent through the capillary and BBB as intrinsically statistical processes. Therefore, it is simulated by a stochastic method (Monte Carlo method). In our model, capillary is divided into multiple sections as in Patlak model and contrast agent moves from one section to other sections. For capillary input, AIF is made by Monte Carlo method from real data. Without solving an equation, we derive the concentration of contrast agent as a function of time and distance in the capillary for normal (not permeable due to BBB) and abnormal capillary with uniform and non-uniform permeability.
机译:求解具有非均匀渗透率和实际动脉输入函数(AIF)的绝热方程的解析方法很复杂。我们认为造影剂通过毛细管和血脑屏障的交叉是本质上的统计过程。因此,它是通过随机方法(蒙特卡罗方法)进行模拟的。在我们的模型中,与Patlak模型一样,毛细管被分为多个部分,而造影剂则从一个部分移动到另一部分。对于毛细管输入,AIF是通过蒙特卡罗方法从实际数据中得出的。在不求解方程的情况下,我们得出造影剂的浓度随时间的变化而变化,该时间是正常毛细管(由于BBB不能渗透)和具有均匀和非均匀渗透率的异常毛细管在毛细管中的时间和距离的函数。

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