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用于脉动血液、大脑和脑脊液动态相互作用的数学框架。

A mathematical framework for the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid.

机构信息

Department of Neurological Surgery, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA.

Department of Mathematics, Vels Institute of Science, Technology and Advanced Studies, Chennai, Tamilnadu, India.

出版信息

Comput Methods Programs Biomed. 2023 Apr;231:107209. doi: 10.1016/j.cmpb.2022.107209. Epub 2022 Oct 29.

Abstract

BACKGROUND

Shedding light on less-known aspects of intracranial fluid dynamics may be helpful to understand the hydrocephalus mechanism. The present study suggests a mathematical framework based on in vivo inputs to compare the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid (CSF) between the healthy subject and the hydrocephalus patient.

METHOD

The input data for the mathematical formulations was pulsatile blood velocity, which was measured using cine PC-MRI. Tube law was used to transfer the created deformation by blood pulsation in the vessel circumference to the brain domain. The pulsatile deformation of brain tissue with respect to time was calculated and considered to be inlet velocity in the CSF domain. The governing equations in all three domains were continuity, Navier-Stokes, and concentration. We used Darcy law with defined permeability and diffusivity values to define the material properties in the brain.

RESULTS

We validated the preciseness of the CSF velocity and pressure through the mathematical formulations with cine PC-MRI velocity, experimental ICP, and FSI simulated velocity and pressure. We used the analysis of dimensionless numbers including Reynolds, Womersley, Hartmann, and Peclet to evaluate the characteristics of the intracranial fluid flow. In the mid-systole phase of a cardiac cycle, CSF velocity had the maximum value and CSF pressure had the minimum value. The maximum and amplitude of CSF pressure, as well as CSF stroke volume, were calculated and compared between the healthy subject and the hydrocephalus patient.

CONCLUSION

The present in vivo-based mathematical framework has the potential to gain insight into the less-known points in the physiological function of intracranial fluid dynamics and the hydrocephalus mechanism.

摘要

背景

揭示颅内流体动力学中不太为人知的方面可能有助于理解脑积水机制。本研究提出了一个基于体内输入的数学框架,以比较健康受试者和脑积水患者之间搏动性血液、大脑和脑脊液(CSF)之间的动态相互作用。

方法

数学公式的输入数据是脉动血流速度,使用电影 PC-MRI 测量。管律用于将血管周长内血液搏动引起的变形传递到大脑区域。计算脑组织相对于时间的脉动变形,并将其视为 CSF 域中的入口速度。所有三个域的控制方程均为连续性、纳维-斯托克斯和浓度方程。我们使用定义了渗透性和扩散率值的达西定律来定义大脑中的材料特性。

结果

我们通过电影 PC-MRI 速度、实验 ICP 和 FSI 模拟速度和压力的数学公式验证了 CSF 速度和压力的精确性。我们使用无量纲数分析,包括雷诺数、沃默斯利数、哈特曼数和佩克莱特数,来评估颅内流体流动的特征。在心动周期的中期,CSF 速度达到最大值,CSF 压力达到最小值。计算并比较了健康受试者和脑积水患者之间的 CSF 压力最大值和振幅以及 CSF 冲程量。

结论

本基于体内的数学框架有可能深入了解颅内流体动力学和脑积水机制中不太为人知的生理功能方面。

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