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MODELING OF BLOOD FLOW IN THE HUMAN BRAIN

机译:人脑中血流的建模

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摘要

The non-Newtonian properties of blood, i.e., shear thinning and viscoelasticity, can have a significant influence on the distribution of Cerebral Blood Flow (CBF) in the human brain. The aim of this work is to quantify the role played by the non-Newtonian nature of blood. Under normal conditions, CBF is autoregulated to maintain baseline levels of flow and oxygen to the brain. However, in patients suffering from heart failure (HF), Stroke, or Arteriovenous malformation (AVM), the pressure in afferent vessels varies from the normal range within which the regulatory mechanisms can ensure a constant cerebral flow rate, leading to impaired cerebration in patients. It has been reported that the change in the flow rate is more significant in certain regions of the brain than others, and that this might be relevant to the pathophysiological symptoms exhibited in these patients. We have developed mathematical models of CBF under normal and the above disease conditions 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 relatively more severely under these conditions.
机译:血液的非牛顿特性,即剪切稀化和粘弹性,会对人脑中脑血流(CBF)的分布产生重大影响。这项工作的目的是量化血液的非牛顿性所起的作用。在正常情况下,CBF会自动调节以维持进入大脑的血流量和氧气的基线水平。但是,在患有心力衰竭(HF),中风或动静脉畸形(AVM)的患者中,传入血管的压力与正常范围有所不同,在正常范围内调节机制可确保恒定的脑血流量,从而导致患者的脑波受损。据报道,在大脑的某些区域,流速的变化比其他区域更显着,这可能与这些患者表现出的病理生理症状有关。我们已经开发了在正常和以上疾病条件下的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个区域会受到相对更严重的影响。

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