A Computational Fluid Dynamics-Based Model for Assessing Rupture Risk in Cerebral Arteries with Varying Aneurysm Sizes

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Rohan Singla, Shubham Gupta, A. Chanda
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Abstract

A cerebral aneurysm is a medical condition where a cerebral artery can burst under adverse pressure conditions. A 20% mortality rate and additional 30 to 40% morbidity rate have been reported for patients suffering from the rupture of aneurysms. In addition to wall shear stress, input jets, induced pressure, and complicated and unstable flow patterns are other important parameters associated with a clinical history of aneurysm ruptures. In this study, the anterior cerebral artery (ACA) was modeled using image segmentation and then rebuilt with aneurysms at locations vulnerable to aneurysm growth. To simulate various aneurysm growth stages, five aneurysm sizes and two wall thicknesses were taken into consideration. In order to simulate realistic pressure loading conditions for the anterior cerebral arteries, inlet velocity and outlet pressure were used. The pressure, wall shear stress, and flow velocity distributions were then evaluated in order to predict the risk of rupture. A low-wall shear stress-based rupture scenario was created using a smaller aneurysm and thinner walls, which enhanced pressure, shear stress, and flow velocity. Additionally, aneurysms with a 4 mm diameter and a thin wall had increased rupture risks, particularly at specific boundary conditions. It is believed that the findings of this study will help physicians predict rupture risk according to aneurysm diameters and make early treatment decisions.
基于计算流体动力学的脑动脉动脉瘤破裂风险评估模型
脑动脉瘤是一种医学疾病,在不利的压力条件下,脑动脉可能会破裂。据报道,动脉瘤破裂患者的死亡率为20%,发病率为30%至40%。除了壁剪切应力外,输入射流、诱导压力以及复杂和不稳定的流动模式也是与动脉瘤破裂临床史相关的其他重要参数。在这项研究中,使用图像分割对大脑前动脉(ACA)进行建模,然后在易发生动脉瘤生长的位置重建动脉瘤。为了模拟不同的动脉瘤生长阶段,考虑了五种动脉瘤大小和两种壁厚。为了模拟大脑前动脉的真实压力负荷条件,使用了入口速度和出口压力。然后评估压力、壁剪切应力和流速分布,以预测破裂风险。使用较小的动脉瘤和较薄的壁创建了基于低壁剪切应力的破裂场景,这增强了压力、剪切应力和流速。此外,直径4毫米、壁薄的动脉瘤破裂风险增加,特别是在特定的边界条件下。相信这项研究的发现将有助于医生根据动脉瘤直径预测破裂风险,并做出早期治疗决定。
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来源期刊
Mathematical & Computational Applications
Mathematical & Computational Applications MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
自引率
10.50%
发文量
86
审稿时长
12 weeks
期刊介绍: Mathematical and Computational Applications (MCA) is devoted to original research in the field of engineering, natural sciences or social sciences where mathematical and/or computational techniques are necessary for solving specific problems. The aim of the journal is to provide a medium by which a wide range of experience can be exchanged among researchers from diverse fields such as engineering (electrical, mechanical, civil, industrial, aeronautical, nuclear etc.), natural sciences (physics, mathematics, chemistry, biology etc.) or social sciences (administrative sciences, economics, political sciences etc.). The papers may be theoretical where mathematics is used in a nontrivial way or computational or combination of both. Each paper submitted will be reviewed and only papers of highest quality that contain original ideas and research will be published. Papers containing only experimental techniques and abstract mathematics without any sign of application are discouraged.
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