Highly efficient fluid-solid coupled incompressible SPH simulation method for atherosclerotic plaque generation

doi:10.3785/j.issn.1008-9497.2023.06.006

Journal of Zhejiang University (Science Edition)

2023, Vol. 50

Issue (6): 711-721 DOI: 10.3785/j.issn.1008-9497.2023.06.006

CCF CAD/CG 2023

Highly efficient fluid-solid coupled incompressible SPH simulation method for atherosclerotic plaque generation

Fei WANG¹,Weihong LI¹,Yu YANG²,Dazhi JIANG¹,Baoquan ZHAO³(

),Xiaonan LUO⁴

^1.Department of Computer Science，Shantou University，Shantou 515063，Guangdong Province，China
^2.Shenzhen Securities Information Co. ，Ltd. ，Shenzhen 518000，Guangdong Province，China
^3.School of Artificial Intelligence，Sun Yat-Sen Universit，Zhuhai 519000，Guangdong Province，China
^4.School of Computer Science and Information Security，Guilin University of Electronic Technology，Guilin 541004，Guangxi Zhuang Autonomous Region，China

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Abstract

Atherosclerosis is a critical cause of cardiovascular disease and stroke. Simulating and visualizing this process is crucial to relevant medical research. To tackle the problems of existing methods regarding the difficulties on realistic simulation and low efficiency, we propose a novel and highly efficient atherosclerotic plaque simulation solution based on a fluid-solid coupled incompressible smoothed particle hydrodynamics (SPH) method. Firstly, we discretize the blood into incompressible fluid particles using fluid-solid coupled in compressible SPH to control the stability of blood. Then, we adopt the plaque generation model to model blood, monocytes and other particles to control plaque generation based on pathological analysis of blood composition. Finally, we compute the physical properties of blood and plaque by coupling fluid-solid particles to simulate the plaque clogging effect. To make the simulation as in real-time as possible, parallel accelerated computation is implemented in CUDA architecture. Several realistic renderings of plaque simulations are provided.The results show that our method can achieves fast simulation of plaque generation in blood while avoiding the high computational cost associated with the partial differential equation model for plaque generation.

Key words： smoothed particle hydrodynamics (SPH) atherosclerosis simulation plaque generation blood simulation fluid-solid coupled

Received: 12 June 2023 Published: 30 November 2023

CLC:

TP 391

Corresponding Authors: Baoquan ZHAO E-mail: zhaobaoquan@mail.sysu.edu.cn

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Cite this article:

Fei WANG,Weihong LI,Yu YANG,Dazhi JIANG,Baoquan ZHAO,Xiaonan LUO. Highly efficient fluid-solid coupled incompressible SPH simulation method for atherosclerotic plaque generation. Journal of Zhejiang University (Science Edition), 2023, 50(6): 711-721.

URL:

https://www.zjujournals.com/sci/EN/Y2023/V50/I6/711

动脉粥样硬化斑块生成的高效流固耦合不可压缩SPH模拟方法

动脉粥样硬化是导致心血管疾病和中风的关键诱因，对该病变过程进行模拟与可视化有助于开展医学研究。为解决现有模拟方法不能可视化动脉粥样硬化斑块生成过程以及模拟速度过慢问题，提出了一种基于高效流固耦合不可压缩光滑粒子流体动力学（smoothed particle hydrodynamics，SPH）的斑块生成模拟方法。首先，基于流固耦合不可压缩SPH方法，将血液离散为不可压缩流体粒子，以控制血液流动的稳定性；然后，使用斑块生成模型对血液、单核细胞等粒子建模，对血液成分进行病理性分析，控制斑块生成；最后，通过流固耦合作用计算血液与斑块的物理特性，模拟斑块堵塞血流过程。为使模拟结果能够实时呈现，用统一计算设备架构（compute unified device architecture，CUDA）实现并行加速计算。方法实现了对血液中斑块生成的快速模拟，避免了用偏微分方程模型模拟带来的高计算量；同时能较真实地模拟斑块生成过程并体现血液与斑块的流固耦合作用；最后逼真展现了斑块模拟的渲染结果。

关键词： 光滑粒子流体动力学, 动脉粥样硬化, 斑块生成模拟, 血液模拟, 流固耦合

Fig.1 Transition of monocytes to macrophages in atherosclerosis^［26］

Fig.2 Thrombin stimulates ICAM-1 expression

Fig.3 Attractive force analysis of monocyte recruitment in atherosclerosis

Fig.4 Conversion processing of particles

参数	取值	单位	描述
$h$	0.025	m	光滑核半径
$ρ$	1 050.0	kg·m^-3	血液密度
$m$	0.000 2	kg	血液粒子质量
$V 0$	10^-16	m3	斑块形成临界体积
$V m$	10^-17	m3	单核细胞体积
$V M$	10^-14	m3	巨噬细胞体积
$V F$	10^-13	m3	泡沫细胞体积
$P 0$	120	mmHg	血管初始血压
$E 0$	24.5	kPa	内皮层初始杨氏模量
$α$	3.5	N·m^-3	流体粒子黏性常数
$σ$	2	N·m^-3	流固粒子黏滞系数

Table 1 Experimental parameters of atherosclerotic plaque formation

Fig.5 Effects of blood simulation

Fig.6 Visualization of plaque growth processes

Fig.7 Rendering of the generated plaque

Fig.8 Effect of different

V 0

on the rate of plaque formation

Fig.9 Plaque generation in planar blood flow

Fig.10 Blood flow rate and blood flow changes from frame 3 000 to frame 15 000

Table 2 Simulation efficiency

Table 3 Simulation efficiency of four groups of test conditions


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