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Modeling of Blood Flow in the Human Brain

机译:人脑中的血流建模

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摘要

Under normal conditions, Cerebral Blood Flow (CBF) is related to the metabolism of the cerebral tissue. Three factors that contribute significantly to the regulation of CBF include the carbon dioxide and hydrogen ion concentration, oxygen deficiency and the level of cerebral activity. These regulatory mechanisms ensure a constant CBF of 50 to 55 ml per lOOg of brain per minute for mean arterial blood pressure between 60 -180 mm Hg. Under severe conditions when the autoregulatory mechanism fails to compensate, sympathetic nervous system constricts the large and intermediate sized arteries and prevents very high pressure from ever reaching the smaller blood vessels, preventing the occurrence of vascular hemorrhage. Several invasive and non-invasive techniques such as pressure and thermoelectric effect sensors to Positron Emission Tomography (PET) and magnetic resonance imaging (MRI) based profusion techniques have been used to quantify CBF. However, the effects of the non-Newtonian properties of blood, i.e., shear thinning and viscoelasticity, can have a significant influence on the distribution of CBF in the human brain and are poorly understood. The aim of this work is to quantify the role played by the non-Newtonian nature of blood on CBF. We have developed mathematical models of CBF that use direct numerical simulations (DNS) for the individual capillaries along with the experimental data in a one-dimensional model to determine the flow rate and the methods for regulating CBF. The model also allows us to determine which regions of the brain would be affected more severely under these conditions.
机译:在正常情况下,脑血流量(CBF)与脑组织的代谢有关。对CBF的调节起重要作用的三个因素包括二氧化碳和氢离子浓度,氧缺乏和大脑活动水平。这些调节机制可确保平均动脉血压在60 -180 mm Hg之间,每分钟每100克大脑50到55毫升的恒定CBF。在严重情况下,当自动调节机制无法补偿时,交感神经系统会收缩大中型动脉,并阻止非常高的压力到达较小的血管,从而防止血管出血的发生。几种侵入式和非侵入式技术,例如基于正电子发射断层扫描(PET)和基于磁共振成像(MRI)的灌注技术的压力和热电效应传感器,已被用于量化CBF。但是,血液的非牛顿特性的影响,即剪切稀化和粘弹性,会对人脑中CBF的分布产生重大影响,人们对此知之甚少。这项工作的目的是量化血液的非牛顿性在脑血流中的作用。我们已经开发出了CBF的数学模型,该模型使用单个毛细管的直接数值模拟(DNS)以及一维模型中的实验数据来确定流速和调节CBF的方法。该模型还使我们能够确定在这些情况下大脑的哪些区域会受到更严重的影响。

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