Suppr超能文献

利用个体颅内压和脑几何模型模拟输注过程中的 CSF 循环和脑淋巴系统。

Modeling CSF circulation and the glymphatic system during infusion using subject specific intracranial pressures and brain geometries.

机构信息

Department of Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway.

Department of Mathematics, University of Oslo, Oslo, Norway.

出版信息

Fluids Barriers CNS. 2024 Oct 15;21(1):82. doi: 10.1186/s12987-024-00582-0.

Abstract

BACKGROUND

Infusion testing is an established method for assessing CSF resistance in patients with idiopathic normal pressure hydrocephalus (iNPH). To what extent the increased resistance is related to the glymphatic system is an open question. Here we introduce a computational model that includes the glymphatic system and enables us to determine the importance of (1) brain geometry, (2) intracranial pressure, and (3) physiological parameters on the outcome of and response to an infusion test.

METHODS

We implemented a seven-compartment multiple network porous medium model with subject specific geometries from MR images using the finite element library FEniCS. The model consists of the arterial, capillary and venous blood vessels, their corresponding perivascular spaces, and the extracellular space (ECS). Both subject specific brain geometries and subject specific infusion tests were used in the modeling of both healthy adults and iNPH patients. Furthermore, we performed a systematic study of the effect of variations in model parameters.

RESULTS

Both the iNPH group and the control group reached a similar steady state solution when subject specific geometries under identical boundary conditions was used in simulation. The difference in terms of average fluid pressure and velocity between the iNPH and control groups, was found to be less than 6% during all stages of infusion in all compartments. With subject specific boundary conditions, the largest computed difference was a 75% greater fluid speed in the arterial perivascular space (PVS) in the iNPH group compared to the control group. Changes to material parameters changed fluid speeds by several orders of magnitude in some scenarios. A considerable amount of the CSF pass through the glymphatic pathway in our models during infusion, i.e., 28% and 38% in the healthy and iNPH patients, respectively.

CONCLUSIONS

Using computational models, we have found the relative importance of subject specific geometries to be less important than individual differences in resistance as measured with infusion tests and model parameters such as permeability, in determining the computed pressure and flow during infusion. Model parameters are uncertain, but certain variations have large impact on the simulation results. The computations resulted in a considerable amount of the infused volume passing through the brain either through the perivascular spaces or the extracellular space.

摘要

背景

输注测试是评估特发性正常压力脑积水(iNPH)患者 CSF 阻力的一种既定方法。增加的阻力在多大程度上与糖质系统有关是一个悬而未决的问题。在这里,我们引入了一个计算模型,该模型包括糖质系统,并使我们能够确定(1)脑几何形状、(2)颅内压和(3)生理参数对输注测试结果和反应的重要性。

方法

我们使用有限元库 FEniCS 实现了一个具有从 MRI 获得的特定于主体的几何形状的七腔室多网络多孔介质模型。该模型由动脉、毛细血管和静脉血管及其相应的血管周腔和细胞外空间(ECS)组成。特定于主体的脑几何形状和特定于主体的输注测试均用于健康成年人和 iNPH 患者的建模。此外,我们对模型参数变化的影响进行了系统研究。

结果

当在模拟中使用相同边界条件下的特定于主体的几何形状时,iNPH 组和对照组都达到了相似的稳态解。在所有输注阶段,iNPH 组和对照组在所有隔室中的平均流体压力和速度差异均小于 6%。使用特定于主体的边界条件,在 iNPH 组中,动脉周腔(PVS)中的流体速度比对照组大 75%。在某些情况下,材料参数的变化会使流体速度变化几个数量级。在我们的模型中,大量 CSF 在输注过程中通过糖质途径,即健康患者和 iNPH 患者分别为 28%和 38%。

结论

使用计算模型,我们发现特定于主体的几何形状的相对重要性不如通过输注测试和模型参数(如渗透性)测量的阻力个体差异重要,这些参数确定了输注过程中的计算压力和流量。模型参数是不确定的,但某些变化对模拟结果有很大影响。计算结果导致相当一部分注入的体积通过血管周腔或细胞外空间穿过大脑。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d43f/11481529/64c80bf3ae1a/12987_2024_582_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验