- Open Access
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.
- Hemodynamic shear stress
- Computational fluid dynamics
- Ultrasonic particle imaging velocimetry
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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- Naghavi M, Libby P, Falk E, Casscells SW, Litovsky S, Rumberger J, Badimon JJ, Stefanadis C, Moreno P, Pasterkamp G, et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: part I. Circulation. 2003;108(14):1664–72.View ArticleGoogle Scholar
- Naghavi M, Libby P, Falk E, Casscells SW, Litovsky S, Rumberger J, Badimon JJ, Stefanadis C, Moreno P, Pasterkamp G, et al. From vulnerable plaque to vulnerable patient: a call for new definitions and risk assessment strategies: part II. Circulation. 2003;108(15):1772–8.View ArticleGoogle Scholar
- Dweck MR, Chow MW, Joshi NV, Williams MC, Jones C, Fletcher AM, Richardson H, White A, McKillop G, van Beek EJ. Coronary arterial 18F-sodium fluoride uptake: a novel marker of plaque biology. J Am Coll Cardiol. 2012;59(17):1539–48.View ArticleGoogle Scholar
- Maurovich-Horvat P, Ferencik M, Voros S, Merkely B, Hoffmann U. Comprehensive plaque assessment by coronary CT angiography. Nat Rev Cardiol. 2014;11(7):390.View ArticleGoogle Scholar
- Schroeder S, Kuettner A, Leitritz M, Janzen J, Kopp AF, Herdeg C, Heuschmid M, Burgstahler C, Baumbach A, Wehrmann M. Reliability of differentiating human coronary plaque morphology using contrast-enhanced multislice spiral computed tomography: a comparison with histology. J Comput Assist Tomogr. 2004;28(4):449–54.View ArticleGoogle Scholar
- De Korte CL, Pasterkamp G, Van Der Steen AF, Woutman HA, Bom N. Characterization of plaque components with intravascular ultrasound elastography in human femoral and coronary arteries in vitro. Circulation. 2000;102(6):617–23.View ArticleGoogle Scholar
- Tearney GJ, Yabushita H, Houser SL, Aretz HT, Jang I-K, Schlendorf KH, Kauffman CR, Shishkov M, Halpern EF, Bouma BE. Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography. Circulation. 2003;107(1):113–9.View ArticleGoogle Scholar
- Wasserman BA, Smith WI, Trout HH, Cannon RO, Balaban RS, Arai AE. Carotid artery atherosclerosis. In vivo morphologic characterization with gadolinium-enhanced double-oblique mr imaging—initial results 1. Radiology. 2002;223(2):566–73.View ArticleGoogle Scholar
- Cheng C, Tempel D, van Haperen R, van der Baan A, Grosveld F, Daemen MJ, Krams R, de Crom R. Atherosclerotic lesion size and vulnerability are determined by patterns of fluid shear stress. Circulation. 2006;113(23):2744–53.View ArticleGoogle Scholar
- Wong KKL, Thavornpattanapong P, Cheung SCP, Tu JY. Biomechanical investigation of pulsatile flow in a three-dimensional atherosclerotic carotid bifurcation model. J Mech Med Biol. 2013;13(01):1350001.View ArticleGoogle Scholar
- Rikhtegar F, Knight JA, Olgac U, Saur SC, Poulikakos D, Marshall W, Cattin PC, Alkadhi H, Kurtcuoglu V. Choosing the optimal wall shear parameter for the prediction of plaque location—a patient-specific computational study in human left coronary arteries. Atherosclerosis. 2012;221(2):432–7.View ArticleGoogle Scholar
- Torii R, Wood NB, Hadjiloizou N, Dowsey AW, Wright AR, Hughes AD, Davies J, Francis DP, Mayet J, Yang G-Z. Stress phase angle depicts differences in coronary artery hemodynamics due to changes in flow and geometry after percutaneous coronary intervention. Am J Physiol-Heart Circ Physiol. 2009;296(3):H765–76.View ArticleGoogle Scholar
- Schaar JA, de Korte CL, Mastik F, Strijder C, Pasterkamp G, Boersma E, Serruys PW, van der Steen AF. Characterizing vulnerable plaque features with intravascular elastography. Circulation. 2003;108(21):2636–41.View ArticleGoogle Scholar
- Caro C, Fitz-Gerald J, Schroter R. Arterial wall shear and distribution of early atheroma in man. Nature. 1969;223:1159–61.View ArticleGoogle Scholar
- Samady H, Eshtehardi P, McDaniel MC, Suo J, Dhawan SS, Maynard C, Timmins LH, Quyyumi AA, Giddens DP. Coronary artery wall shear stress is associated with progression and transformation of atherosclerotic plaque and arterial remodeling in patients with coronary artery disease. Circulation. 2011;124(7):779–88.View ArticleGoogle Scholar
- Jin Z-G, Ueba H, Tanimoto T, Lungu AO, Frame MD, Berk BC. Ligand-independent activation of vascular endothelial growth factor receptor 2 by fluid shear stress regulates activation of endothelial nitric oxide synthase. Circ Res. 2003;93(4):354–63.View ArticleGoogle Scholar
- Papadaki M, Ruef J, Nguyen KT, Li F, Patterson C, Eskin SG, McIntire LV, Runge MS. Differential regulation of protease activated receptor-1 and tissue plasminogen activator expression by shear stress in vascular smooth muscle cells. Circ Res. 1998;83(10):1027–34.View ArticleGoogle Scholar
- Gongol B, Marin T, Peng IC, Woo B, Martin M, King S, Sun W, Johnson DA, Chien S, Shyy JYJ. AMPKα2 exerts its anti-inflammatory effects through PARP-1 and Bcl-6. Proc Natl Acad Sci. 2013;110(8):3161–6.View ArticleGoogle Scholar
- Fang Y, Shi C, Manduchi E, Civelek M, Davies PF. MicroRNA-10a regulation of proinflammatory phenotype in athero-susceptible endothelium in vivo and in vitro. Proc Natl Acad Sci. 2010;107(30):13450–5.View ArticleGoogle Scholar
- Burke AP, Kolodgie FD, Farb A, Weber D, Virmani R. Morphological predictors of arterial remodeling in coronary atherosclerosis. Circulation. 2002;105(3):297–303.View ArticleGoogle Scholar
- Wu W, Xiao H, Laguna-Fernandez A, Villarreal G, Wang KC, Geary GG, Zhang Y, Wang WC, Huang HD, Zhou J. Flow-dependent regulation of Krüppel-like factor 2 is mediated by microRNA-92a. Circulation. 2011;124(5):633–41.View ArticleGoogle Scholar
- Zhou J, Wang K-C, Wu W, Subramaniam S, Shyy JYJ, Chiu JJ, Li JYS, Chien S. MicroRNA-21 targets peroxisome proliferators-activated receptor-α in an autoregulatory loop to modulate flow-induced endothelial inflammation. Proc Natl Acad Sci. 2011;108(25):10355–60.View ArticleGoogle Scholar
- Conklin BS, Zhong DS, Zhao W, Lin PH, Chen C. Shear stress regulates occludin and VEGF expression in porcine arterial endothelial cells. J Surg Res. 2002;102(1):13–21.View ArticleGoogle Scholar
- Zheng H, Liu L, Williams L, Hertzberg JR, Lanning C, Shandas R. Real time multicomponent echo particle image velocimetry technique for opaque flow imaging. Appl Phys Lett. 2006;88(26):261915.View ArticleGoogle Scholar
- Niu L, Qian M, Wan K, Yu W, Jin Q, Ling T, Gao S, Zheng H. Ultrasonic particle image velocimetry for improved flow gradient imaging: algorithms, methodology and validation. Phys Med Biol. 2010;55(7):2103–20.View ArticleGoogle Scholar
- Johnston BM, Johnston PR, Corney S, Kilpatrick D. Non-Newtonian blood flow in human right coronary arteries: steady state simulations. J Biomech. 2004;37(5):709–20.View ArticleGoogle Scholar
- Martin D, Zaman A, Hacker J, Mendelow D, Birchall D. Analysis of haemodynamic factors involved in carotid atherosclerosis using computational fluid dynamics. Br J Radiol. 2014.Google Scholar
- Steinman DA, Milner JS, Norley CJ, Lownie SP, Holdsworth DW. Image-based computational simulation of flow dynamics in a giant intracranial aneurysm. Am J Neuroradiol. 2003;24(4):559–66.Google Scholar
- Qiu Y, Tarbell JM. Numerical simulation of pulsatile flow in a compliant curved tube model of a coronary artery. J Biomech Eng. 2000;122(1):77–85.View ArticleGoogle Scholar
- Bavo AM, Pouch AM, Degroote J, Vierendeels J, Gorman JH, Gorman RC, Segers P. Patient-specific CFD simulation of intraventricular haemodynamics based on 3D ultrasound imaging. Biomed Eng Online. 2016;15(1):107.View ArticleGoogle Scholar
- Wu J, Liu G, Huang W, Ghista DN, Wong KK. Transient blood flow in elastic coronary arteries with varying degrees of stenosis and dilatations: CFD modelling and parametric study. Comput Methods Biomech Biomed Eng. 2015;18(16):1835–45.View ArticleGoogle Scholar
- Wong KK, Ghista DN, Wu J, Liu G. Simulation of blood flow in idealized and patient-specific coronary arteries with curvatures, stenoses, dilatations, and side-branches. Cardiol Sci Technol. 2016;333.Google Scholar
- Wong KKL, Sun Z, Tu J. Medical imaging and computer-aided flow analysis of a heart with atrial septal defect. J Mech Med Biol. 2012;12(05):1250024.View ArticleGoogle Scholar
- Wong KK, Wang D, Ko JK, Mazumdar J, Le TT, Ghista D. Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures. Biomed Eng Online. 2017;16(1):35.View ArticleGoogle Scholar
- Chu KC, Rutt BK. Polyvinyl alcohol cryogel: an ideal phantom material for MR studies of arterial flow and elasticity. Magn Reson Med. 1997;37(2):314–9.View ArticleGoogle Scholar
- Surry K, Austin H, Fenster A, Peters T. Poly (vinyl alcohol) cryogel phantoms for use in ultrasound and MR imaging. Phys Med Biol. 2004;49(24):5529.View ArticleGoogle Scholar
- Pazos V, Mongrain R, Tardif J. Polyvinyl alcohol cryogel: optimizing the parameters of cryogenic treatment using hyperelastic models. J Mech Behav Biomed Mater. 2009;2(5):542–9.View ArticleGoogle Scholar
- McDonald DA. Blood flow in arteries. 1974.Google Scholar
- Niu L, Qian M, Yan L, Yu W, Jiang B, Jin Q, Wang Y, Shandas R, Liu X, Zheng H. Real-time texture analysis for identifying optimum microbubble concentration in 2-D ultrasonic particle image velocimetry. Ultrasound Med Biol. 2011;37(8):1280–91.View ArticleGoogle Scholar
- Morandi C, Piazza F, Capancioni R. Digital image registration by phase correlation between boundary maps. IEE Proc E-Comput Digit Tech. 1987;2(134):101–4.View ArticleGoogle Scholar
- Zhu LH. Study and improvement of robust performance of Gaussian filtering. Chinese J Sci Instrum. 2004;5:018.Google Scholar
- Malek AM, Alper SL, Izumo S. Hemodynamic shear stress and its role in atherosclerosis. JAMA. 1999;282(21):2035–42.View ArticleGoogle Scholar
- Richardson PD, Davies M, Born G. Influence of plaque configuration and stress distribution on fissuring of coronary atherosclerotic plaques. Lancet. 1989;334(8669):941–4.View ArticleGoogle Scholar
- Cheng GC, Loree HM, Kamm RD, Fishbein MC, Lee RT. Distribution of circumferential stress in ruptured and stable atherosclerotic lesions. A structural analysis with histopathological correlation. Circulation. 1993;87(4):1179–87.View ArticleGoogle Scholar
- Papathanasopoulou P, Zhao S, Köhler U, Robertson MB, Long Q, Hoskins P, Yun XuX, Marshall I. MRI measurement of time-resolved wall shear stress vectors in a carotid bifurcation model, and comparison with CFD predictions. J Magn Reson Imaging. 2003;17(2):153–62.View ArticleGoogle Scholar
- Vuong B, Genis H, Wong R, Ramjist J, Jivraj J, Farooq H, Sun C, Yang VX. Evaluation of flow velocities after carotid artery stenting through split spectrum Doppler optical coherence tomography and computational fluid dynamics modeling. Biomed Opt Express. 2014;5(12):4405–16.View ArticleGoogle Scholar
- Torii R, Oshima M, Kobayashi T, Takagi K, Tezduyar TE. Influence of wall elasticity in patient-specific hemodynamic simulations. Comput Fluids. 2007;36(1):160–8.View ArticleMATHGoogle Scholar
- Ford MD, Nikolov HN, Milner JS, Lownie SP, DeMont EM, Kalata W, Loth F, Holdsworth DW, Steinman DA. PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models. J Biomech Eng. 2008;130(2):021015.View ArticleGoogle Scholar
- Niu L, Meng L, Xu L, Liu J, Wang Q, Xiao Y, Qian M, Zheng H. Stress phase angle depicts differences in arterial stiffness: phantom and in vivo study. Phys Med Biol. 2015;60(11):4281.View ArticleGoogle Scholar
- Bodnár T, Sequeira A, Prosi M. On the shear-thinning and viscoelastic effects of blood flow under various flow rates. Appl Math Comput. 2011;217(11):5055–67.MathSciNetMATHGoogle Scholar
- Gijsen FJ, van de Vosse FN, Janssen J. The influence of the non-Newtonian properties of blood on the flow in large arteries: steady flow in a carotid bifurcation model. J Biomech. 1999;32(6):601–8.View ArticleGoogle Scholar