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使用光滑粒子流体动力学对左心室血流进行建模。

Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics.

作者信息

Caballero Andrés, Mao Wenbin, Liang Liang, Oshinski John, Primiano Charles, McKay Raymond, Kodali Susheel, Sun Wei

机构信息

The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.

Department of Radiology & Imaging Science, Emory University, Atlanta, GA, USA.

出版信息

Cardiovasc Eng Technol. 2017 Dec;8(4):465-479. doi: 10.1007/s13239-017-0324-z. Epub 2017 Jul 25.

Abstract

This study aims to investigate the capability of smoothed particle hydrodynamics (SPH), a fully Lagrangian mesh-free method, to simulate the bulk blood flow dynamics in two realistic left ventricular (LV) models. Three dimensional geometries and motion of the LV, proximal left atrium and aortic root are extracted from cardiac magnetic resonance imaging and multi-slice computed tomography imaging data. SPH simulation results are analyzed and compared with those obtained using a traditional finite volume-based numerical method, and to in vivo phase contrast magnetic resonance imaging and echocardiography data, in terms of the large-scale blood flow phenomena usually clinically measured. A quantitative comparison of the velocity fields and global flow parameters between the in silico models and the in vivo data shows a reasonable agreement, given the inherent uncertainties and limitations in the modeling and imaging techniques. The results indicate the capability of SPH as a promising tool for predicting clinically relevant large-scale LV flow information.

摘要

本研究旨在探究光滑粒子流体动力学(SPH)这一完全拉格朗日无网格方法模拟两个真实左心室(LV)模型中整体血流动力学的能力。左心室、左心房近端和主动脉根部的三维几何形状及运动是从心脏磁共振成像和多层计算机断层扫描成像数据中提取的。根据通常临床测量的大规模血流现象,对SPH模拟结果进行分析,并与使用传统基于有限体积的数值方法获得的结果以及体内相位对比磁共振成像和超声心动图数据进行比较。鉴于建模和成像技术中存在的固有不确定性和局限性,计算机模拟模型与体内数据之间速度场和整体流动参数的定量比较显示出合理的一致性。结果表明,SPH有能力成为预测临床相关大规模左心室血流信息的一种有前景的工具。

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Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics.使用光滑粒子流体动力学对左心室血流进行建模。
Cardiovasc Eng Technol. 2017 Dec;8(4):465-479. doi: 10.1007/s13239-017-0324-z. Epub 2017 Jul 25.

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