Literature DB >> 29704490

Mathematical modeling of atherosclerotic plaque destabilization: Role of neovascularization and intraplaque hemorrhage.

Muyi Guo1, Yan Cai1, Xinke Yao1, Zhiyong Li2.   

Abstract

Observational studies have identified angiogenesis from the adventitial vasa vasorum and intraplaque hemorrhage (IPH) as critical factors in atherosclerotic plaque progression and destabilization. Here we propose a mathematical model incorporating intraplaque neovascularization and hemodynamic calculation with plaque destabilization for the quantitative evaluation of the role of neoangiogenesis and IPH in the vulnerable atherosclerotic plaque formation. An angiogenic microvasculature is generated by two-dimensional nine-point discretization of endothelial cell proliferation and migration from the vasa vasorum. Three key cells (endothelial cells, smooth muscle cells and macrophages) and three key chemicals (vascular endothelial growth factors, extracellular matrix and matrix metalloproteinase) are involved in the plaque progression model, and described by the reaction-diffusion partial differential equations. The hemodynamic calculation of the microcirculation on the generated microvessel network is carried out by coupling the intravascular, interstitial and transvascular flow. The plasma concentration in the interstitial domain is defined as the description of IPH area according to the diffusion and convection with the interstitial fluid flow, as well as the extravascular movement across the leaky vessel wall. The simulation results demonstrate a series of pathophysiological phenomena during the vulnerable progression of an atherosclerotic plaque, including the expanding necrotic core, the exacerbated inflammation, the high microvessel density (MVD) region at the shoulder areas, the transvascular flow through the capillary wall and the IPH. The important role of IPH in the plaque destabilization is evidenced by simulations with varied model parameters. It is found that the IPH can significantly speed up the plaque vulnerability by increasing necrotic core and thinning fibrous cap. In addition, the decreased MVD and vessel permeability may slow down the process of plaque destabilization by reducing the IPH dramatically. We envision that the present model and its future advances can serve as a valuable theoretical platform for studying the dynamic changes in the microenvironment during the plaque destabilization.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Intraplaque angiogenesis and hemorrhage; Microcirculation inside the plaque lesion; Numerical model of vulnerable atherosclerosis; Plaque microenvironmental dynamics

Mesh:

Year:  2018        PMID: 29704490     DOI: 10.1016/j.jtbi.2018.04.031

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

1.  Studying the Factors of Human Carotid Atherosclerotic Plaque Rupture, by Calculating Stress/Strain in the Plaque, Based on CEUS Images: A Numerical Study.

Authors:  Zhenzhou Li; Yongfeng Wang; Xinyin Wu; Xin Liu; Shanshan Huang; Yi He; Shuyu Liu; Lijie Ren
Journal:  Front Neuroinform       Date:  2020-11-24       Impact factor: 4.081

2.  Dilated microvessel with endothelial cell proliferation involves intraplaque hemorrhage in unstable carotid plaque.

Authors:  Daina Kashiwazaki; Shusuke Yamamoto; Naoki Akioka; Emiko Hori; Takashi Shibata; Naoya Kuwayama; Kyo Noguchi; Satoshi Kuroda
Journal:  Acta Neurochir (Wien)       Date:  2020-09-30       Impact factor: 2.216

3.  Assessment of carotid atherosclerotic plaque using 3D motion-sensitized driven-equilibrium prepared rapid gradient echo: a comparative study.

Authors:  Xin Cao; Ye Tang; Lei Pan; Jinming Yang; Yifan Wu; Daoying Geng; Jun Zhang
Journal:  Quant Imaging Med Surg       Date:  2021-06

4.  Simulation of atherosclerotic plaque growth using computational biomechanics and patient-specific data.

Authors:  Dimitrios S Pleouras; Antonis I Sakellarios; Panagiota Tsompou; Vassiliki Kigka; Savvas Kyriakidis; Silvia Rocchiccioli; Danilo Neglia; Juhani Knuuti; Gualtiero Pelosi; Lampros K Michalis; Dimitrios I Fotiadis
Journal:  Sci Rep       Date:  2020-10-15       Impact factor: 4.379

5.  A prediction tool for plaque progression based on patient-specific multi-physical modeling.

Authors:  Jichao Pan; Yan Cai; Liang Wang; Akiko Maehara; Gary S Mintz; Dalin Tang; Zhiyong Li
Journal:  PLoS Comput Biol       Date:  2021-03-29       Impact factor: 4.475

Review 6.  Different Approaches in Therapy Aiming to Stabilize an Unstable Atherosclerotic Plaque.

Authors:  Michal Kowara; Agnieszka Cudnoch-Jedrzejewska
Journal:  Int J Mol Sci       Date:  2021-04-21       Impact factor: 5.923

7.  Macrophage polarization as a potential therapeutic target for atherosclerosis: a dynamic stochastic modelling study.

Authors:  Mengchen Liu; Yan Cai; Jichao Pan; Karlheinz Peter; Zhiyong Li
Journal:  R Soc Open Sci       Date:  2022-08-03       Impact factor: 3.653

  7 in total

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