Computational and experimental assessment of influences of hemodynamic shear stress on carotid plaque
- Hui Zhou†1, 2,
- Long Meng†1,
- Wei Zhou1,
- Lin Xin3,
- Xiangxiang Xia1,
- Shuai Li1,
- Hairong Zheng1 and
- Lili Niu1Email authorView ORCID ID profile
© The Author(s) 2017
Received: 6 April 2017
Accepted: 22 July 2017
Published: 29 July 2017
Studies have identified hemodynamic shear stress as an important determinant of endothelial function and atherosclerosis. In this study, we assess the influences of hemodynamic shear stress on carotid plaques.
Carotid stenosis phantoms with three severity (30, 50, 70%) were made from 10% polyvinyl alcohol (PVA) cryogel. The phantoms were placed in a pulsatile flow loop with the same systolic/diastolic phase (35/65) and inlet flow rate (16 L/h). Ultrasonic particle imaging velocimetry (Echo PIV) and computational fluid dynamics (CFD) were used to calculate the velocity profile and shear stress distribution in the carotid stenosis phantoms. Inlet/outlet boundary conditions used in CFD were extracted from Echo PIV experiments to make sure that the results were comparable.
Echo PIV and CFD results showed that velocity was largest in 70% than those in 30 and 50% at peak systole. Echo PIV results indicated that shear stress was larger in the upper wall and the surface of plaque than in the center of vessel. CFD results demonstrated that wall shear stress in the upstream was larger than in downstream of plaque. There was no significant difference in average velocity obtained by CFD and Echo PIV in 30% (p = 0.25). Velocities measured by CFD in 50% (93.01 cm/s) and in 70% (115.07 cm/s) were larger than those by Echo PIV in 50% (60.26 ± 5.36 cm/s) and in 70% (89.11 ± 7.21 cm/s).
The results suggested that Echo PIV and CFD could obtain hemodynamic shear stress on carotid plaques. Higher WSS occurred in narrower arteries, and the shoulder of plaque bore higher WSS than in bottom part.
KeywordsHemodynamic shear stress Computational fluid dynamics Ultrasonic particle imaging velocimetry Atherosclerosis Plaque
Vulnerable plaque is considered to be the culprit of vessel thrombosis and acute cardiovascular and cerebrovascular diseases because of its silent progression and sudden rupture. Therefore, finding accurate and early predictor of plaque prone to rupture is essential for prospective and preventative treatment. A large amount of clinical studies have confirmed that vulnerable plaque is made of a thin overlying fibrous cap, large lipid cores and potential inflammation [1, 2]. Imaging technique can detect the existence of atherosclerotic plaque [3–5]. Intravascular ultrasound (IVUS) and optical coherence tomography (OCT) provide intravascular imaging and identify thin fibrous cap which is responsible for high probability rupture plaque [6, 7]. However IVUS and OCT are invasive tools. Magnetic resonance imaging (MRI) is a noninvasive technique which offers important biological characteristics of plaque , but its temporal-spatial resolution is low.
In addition, many studies have indicated that hemodynamic stress, such as wall shear stress (WSS) [9, 10], oscillatory shear index (OSI) , stress phase angle (SPA) , wall shear gradient (WSG)  has potential function in prediction of high-risk plaque. Among all those stress, WSS has been most fully studied. WSS affected the morphology and biochemistry of endothelial cells (ECs) and further influenced arterial remodelling and process of atherosclerosis [14, 15]. When healthy arteries were in high WSS (15–70 dyne/cm2), ECs present elongated arrangement parallel to the direction of flow, and high WSS will cause expression of vasodilators , fibrinolytics , in addition to reduce expression of leukocyte adhesion molecules  and inflammatory mediators , thus leading to expansive remodelling in the vessel to reduce WSS . Whereas low WSS (<10 dyne/cm2) will decrease production of vasodilators , fibrinolytics , and increase expression of cell adhesion molecules , growth factors , thus leading to narrowing remodelling in the vessel to enhance WSS . However, higher WSS may promote plaque rupture in artery stenosis.
Echo PIV, a two-dimensional, non-invasive ultrasonic velocimetry technique, could calculate the displacements of particles in fluid using cross-correlation coefficient, and the displacements of particles reflect fluid flow information. It has been confirmed that Echo PIV used in this research can conduct rotating flow, jet flow, tube flow measurement accurately [24, 25]. CFD, numerical computational method, has been widely used to calculate hemodynamic stress [26–31] in patient-specific images model [32, 33] and anatomically realistic experimental model .
The goal of this work is to conduct Echo PIV in three different severity stenosis PVA-c arterial phantoms, to obtain the hemodynamic shear stress in those phantoms and further analyze the influence of severity on the plaque. Besides, Echo PIV-based phantoms and boundaries were used in CFD to calculate WSS in three phantoms, and further verify the stenosis influence in plaque rupture.
PVA-c arterial phantoms
Ultrasonic particle image velocimetry algorithm
The nodes and elements in three models
Velocity distributions measured by Echo PIV and CFD
Quantitative comparison of velocity distributions using CFD and Echo PIV
WSS distributions measured by Echo PIV and CFD
Largest WSS measured by Echo PIV and CFD in three stenosis
Echo PIV (Pa)
In this study, we conducted Echo PIV and CFD simulation in three different severity stenosis phantoms (30, 50, 70%), and further made comparisons on shear stress among three phantoms. Firstly, SS had functional relationship with velocity, and any changes in velocity would definitely cause corresponding changes in SS, thus we calculated the velocity profile by CFD and Echo PIV under the same condition. Both experiments demonstrated that there was a larger blood velocity changes in magnitude and direction in narrower phantom, which could result in abnormally high and low SS (Fig. 5). Secondly, we quantitatively calculated SS in three phantoms. Previous researches have indicated that SS can be used to understand the progress of atherosclerosis and may help to guide future therapeutic strategies . Echo PIV and CFD results indicated that plaque shoulders generally exhibited high shear stress than other site. Previous studies have also indicated that plaque shoulders are most often the site of plaque rupture [43, 44]. Lastly, SS and velocity obtained from Echo PIV were obviously lower than those from CFD.
Diameter expansion in three stenosis during cardiac cycle
Diameter expansion (mm)
5 ± 0.11
5 ± 0.06
5 ± 0.03
Secondly CFD relies on simplifying fluid conditions and specifies blood as Newtonian fluid (with constant viscosity respect to shear rate). However, blood exhibits non-Newtonian properties and variable shear-dependent viscosity. Previous studies indicated that different blood properties depicted different hemodynamic parameters [50, 51]. Finally, anatomically realistic artery stenosis model and vulnerable plaque model should be employed to further assess the probability of plaque rupture.
In this study, we carried out CFD and Echo PIV analysis of hemodynamic shear stress in plaque phantoms with three severity stenosis phantoms. We observed that the degree of stenosis had a significant influence on the SS distribution, which was an important factor in the rupture of plaque. The results are a first step toward clinical application in prediction of plaque’s rupture. Future relevant work would include assessing the length of plaque influence on hemodynamic shear stress.
LN and LM designed the project. HZ, WZ, SL performed the experiments. HZ discussed the results. LN and HZ wrote the manuscript. All authors reviewed the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
All data generated or analysed during this study are included in this published article.
The work is supported by National Science Foundation Grants (NSFC Grant Nos. 11574341, 11674347, 81527901, 11325420) and Shenzhen Basic Science Research (JCYJ20160429190550139, JCYJ20160429184552717).
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