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使用流固耦合方法对脑动脉栓塞进行计算机模拟分析。

In silico analysis of embolism in cerebral arteries using fluid-structure interaction method.

作者信息

Talebibarmi Pouria, Vahidi Bahman, Ebad Mahtab

机构信息

Division of Biomedical Engineering, Department of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.

出版信息

Heliyon. 2024 Apr 27;10(9):e30443. doi: 10.1016/j.heliyon.2024.e30443. eCollection 2024 May 15.

DOI:10.1016/j.heliyon.2024.e30443
PMID:38720729
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11077041/
Abstract

Ischemic stroke, particularly embolic stroke, stands as a significant global contributor to mortality and long-term disabilities. This paper presents a comprehensive simulation of emboli motion through the middle cerebral artery (MCA), a prevalent site for embolic stroke. Our patient-specific computational model integrates major branches of the middle cerebral artery reconstructed from magnetic resonance angiography images, pulsatile flow dynamics, and emboli of varying geometries, sizes, and material properties. The fluid-structure interactions method is employed to simulate deformable emboli motion through the middle cerebral artery, allowing observation of hemodynamic changes in artery branches upon embolus entry. We investigated the impact of embolus presence on shear stress magnitude on artery walls, analyzed the effects of embolus material properties and geometries on embolus trajectory and motion dynamics within the middle cerebral artery. Additionally, we evaluated the non-Newtonian behavior of blood, comparing it with Newtonian blood behavior. Our findings highlight that embolus geometry significantly influences trajectory, motion patterns, and hemodynamics within middle cerebral artery branches. Emboli with visco-hyperelastic material properties experienced higher stresses upon collision with artery walls compared to those with hyperelastic properties. Furthermore, considering blood as a non-Newtonian fluid had notable effects on emboli stresses and trajectories within the artery, particularly during collisions. Notably, the maximum von Mises stress experienced in our study was 21.83 kPa, suggesting a very low probability of emboli breaking during movement, impact, and after coming to a stop. However, in certain situations, the magnitude of shear stress on them exceeded 1 kPa, increasing the likelihood of cracking and disintegration. These results serve as an initial step in anticipating critical clinical conditions arising from arterial embolism in the middle cerebral artery. They provide insights into the biomechanical parameters influencing embolism, contributing to improved clinical decision-making for stroke management.

摘要

缺血性中风,尤其是栓塞性中风,是全球死亡率和长期残疾的重要原因。本文对栓子通过大脑中动脉(MCA)的运动进行了全面模拟,大脑中动脉是栓塞性中风的常见部位。我们的患者特异性计算模型整合了从磁共振血管造影图像重建的大脑中动脉主要分支、脉动血流动力学以及不同几何形状、大小和材料特性的栓子。采用流固相互作用方法模拟可变形栓子在大脑中动脉中的运动,从而观察栓子进入后动脉分支中的血流动力学变化。我们研究了栓子的存在对动脉壁剪切应力大小的影响,分析了栓子材料特性和几何形状对大脑中动脉内栓子轨迹和运动动力学的影响。此外,我们评估了血液的非牛顿行为,并将其与牛顿血液行为进行了比较。我们的研究结果表明,栓子几何形状对大脑中动脉分支内的轨迹、运动模式和血流动力学有显著影响。与具有超弹性特性的栓子相比,具有粘弹性超弹性材料特性的栓子在与动脉壁碰撞时承受更高的应力。此外,将血液视为非牛顿流体对动脉内栓子的应力和轨迹有显著影响,尤其是在碰撞期间。值得注意的是,我们研究中经历的最大冯·米塞斯应力为21.83kPa,这表明栓子在运动、撞击和停止后破裂的可能性非常低。然而,在某些情况下,作用在它们上的剪切应力大小超过1kPa,增加了破裂和崩解的可能性。这些结果是预测大脑中动脉动脉栓塞引起的关键临床情况的第一步。它们提供了对影响栓塞的生物力学参数的见解,有助于改善中风管理的临床决策。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/643d1929566e/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/021f309c9989/gr4.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/6d7c612f09be/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/e6301ff2d3e5/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/d62273a3a67d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/253546236196/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/ee50af1681ba/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/1fb3f31efa8e/gr11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/b51a33a585f6/gr12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8733/11077041/d1e2fb4086a8/gr13.jpg

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Front Cardiovasc Med. 2023 Aug 15;10:1219021. doi: 10.3389/fcvm.2023.1219021. eCollection 2023.
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Animal Models of Ischemic Stroke with Different Forms of Middle Cerebral Artery Occlusion.
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Sci Rep. 2023 Feb 21;13(1):3021. doi: 10.1038/s41598-023-29974-2.
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In Silico Prediction of the Toxicity of Nitroaromatic Compounds: Application of Ensemble Learning QSAR Approach.硝基芳香族化合物毒性的计算机模拟预测:集成学习QSAR方法的应用
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