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脑脊液与完整头部模型在快速加速和减速情况下的流固耦合分析。

Fluid-structure interaction analysis of cerebrospinal fluid with a comprehensive head model subject to a rapid acceleration and deceleration.

作者信息

Toma Milan, Nguyen Paul D H

机构信息

a Computational Bio-FSI Laboratory, Department of Mechanical Engineering, School of Engineering & Computing Sciences , New York Institute of Technology , Old Westbury, NY , USA.

b Penn State College of Medicine , Hershey , PA , USA.

出版信息

Brain Inj. 2018;32(12):1576-1584. doi: 10.1080/02699052.2018.1502470. Epub 2018 Jul 30.

Abstract

PRIMARY OBJECTIVE

Closed brain injuries are a common danger in contact sports and motorized vehicular collisions. Mild closed brain injuries, such as concussions, are not easily visualized by computed imaging or scans. Having a comprehensive head/brain model and using fluid-structure interaction (FSI) simulations enable us to see the exact movement of the cerebrospinal fluid (CSF) under such conditions and to identify the areas of brain most affected.

RESEARCH DESIGN

The presented work is based on the first FSI model capable of simulating the interaction between the CSF flow and brain.

METHODS AND PROCEDURES

FSI analysis combining smoothed-particle hydrodynamics and high-order finite-element method is used.

MAIN OUTCOMES AND RESULTS

The interaction between the CSF and brain under rapid acceleration and deceleration is demonstrated. The cushioning effect of the fluid and its effect on brain are shown.

CONCLUSIONS

The capability to locate areas (down to the exact gyri and sulci) of the brain the most affected under given loading conditions, and therefore assess the possible damage to the brain and consequently predict the symptoms, is shown.

摘要

主要目标

闭合性脑损伤在接触性运动和机动车碰撞中是常见的危险。轻度闭合性脑损伤,如脑震荡,通过计算机成像或扫描不易观察到。拥有一个全面的头部/大脑模型并使用流固耦合(FSI)模拟,使我们能够看到在这种情况下脑脊液(CSF)的确切运动,并确定受影响最严重的脑区。

研究设计

所展示的工作基于首个能够模拟脑脊液流动与大脑之间相互作用的FSI模型。

方法和步骤

采用结合了光滑粒子流体动力学和高阶有限元方法的FSI分析。

主要结果

展示了快速加速和减速下脑脊液与大脑之间的相互作用。显示了流体的缓冲作用及其对大脑的影响。

结论

展示了在给定负荷条件下定位受影响最严重的脑区(精确到脑回和脑沟)的能力,从而评估对大脑可能造成的损伤并预测症状。

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