Skip to main content
SpringerLink
Log in

Haemodynamic Effects on the Development and Stability of Atherosclerotic Plaques in Arterial Blood Vessel

  • Original research article
  • Published:
Interdisciplinary Sciences: Computational Life Sciences Aims and scope Submit manuscript

Abstract

Studying the formation and stability of atherosclerotic plaques in the hemodynamic field is essential for understanding the growth mechanism and preventive treatment of atherosclerotic plaques. In this paper, based on a multiplayer porous wall model, we established a two-way fluid–solid interaction with time-varying inlet flow. The lipid-rich necrotic core (LRNC) and stress in atherosclerotic plaque were described for analyzing the stability of atherosclerotic plaques during the plaque growth by solving advection–diffusion–reaction equations with finite-element method. It was found that LRNC appeared when the lipid levels of apoptotic materials (such as macrophages, foam cells) in the plaque reached a specified lower concentration, and increased with the plaque growth. LRNC was positively correlated with the blood pressure and was negatively correlated with the blood flow velocity. The maximum stress was mainly located at the necrotic core and gradually moved toward the left shoulder of the plaque with the plaque growth, which increases the plaque instability and the risk of the plaque shedding. The computational model may contribute to understanding the mechanisms of early atherosclerotic plaque growth and the risk of instability in the plaque growth.

Graphic abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Data availability

All data generated or used during the study appear in the submitted article.

Abbreviations

C :

Concentration

D :

Diffusion coefficient

ρ:

Blood density

u w :

Convection coefficient of the conserved flux

P :

Blood pressure

μ :

Dynamic viscosity

U :

Velocity of the blood

t :

Time

WSS:

Shear stress

V :

Volume

R :

The height of the necrotic core

L :

Length of damage

Kr:

Correction factor

υ:

Poisson’s ratio

\(\Omega\) :

Two-dimensional domain

\(J\) :

Boundary flux

\(\varepsilon_{p}\) :

porosity

k :

Permeability

References

  1. Zhou D, Li J, Liu D, Ji LY, Wang NQ, Jie D, Wang JC, Ye M, Zhao XH (2019) Irregular surface of carotid atherosclerotic plaque is associated with ischemic stroke: a magnetic resonance imaging study. J Geriatr Cardiol 16(12):872–879. https://doi.org/10.11909/j.issn.1671-5411.2019.12.002

    Article  PubMed  PubMed Central  Google Scholar 

  2. Li J, Li D, Yang D, Hang HL, Wu YW, Yao R, Chen XY, Xu YL, Dai W, Zhou D, Zhao XH (2020) Irregularity of carotid plaque surface predicts subsequent vascular event: a MRI study. J Magn Reson Imaging 52(1):185–194. https://doi.org/10.1002/jmri.27038

    Article  PubMed  Google Scholar 

  3. Lei W, Hu J, Xie Y et al (2023) Mathematical modelling of the effects of statins on the growth of necrotic core in atherosclerotic plaque. Math Model Nat Phenom 18:11–28. https://doi.org/10.1051/mmnp/2023005

    Article  Google Scholar 

  4. Thon MP, Hemmler A, Glinzer A, Mayr M, Widgruber M, Zernecke-Madsen A, Gee MW (2018) A multiphysics approach for modeling early atherosclerosis. Biomech Model Mechanobiol 17:617–644. https://doi.org/10.1007/s10237-017-0982-7

    Article  CAS  PubMed  Google Scholar 

  5. Basak S, Khare HA, Kempen PJ, Kamaly N, Almdal K (2022) Nanoconfined anti-oxidizing RAFT nitroxide radical polymer for reduction of low-density lipoprotein oxidation and foam cell formation. Nanoscale Adv. 4(3):742–753. https://doi.org/10.1039/D1NA00631B

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Victoria-Montesinos D, Abellán Ruiz MS, Luque Rubia AJ, Martinez DG, Pérez-Piñero S, Sánchez Macarro M, García-Muñoz AM, García FC, Sánchez JC, López-Román FJ (2021) Effectiveness of consumption of a combination of citrus fruit flavonoids and olive leaf polyphenols to reduce oxidation of low-density lipoprotein in treatment-naive cardiovascular risk subjects: a randomized double-blind controlled study. Antioxidants 10(4):589–599. https://doi.org/10.3390/antiox10040589

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fok PW (2012) Growth of necrotic cores in atherosclerotic plaque. Math Med Biol A J Ima 29(4):301–327. https://doi.org/10.1093/imammb/dqr012

    Article  Google Scholar 

  8. Newby AC, George SJ, Ismail Y, Johnson JL, Sala-Newby GB, Thomas AC (2009) Vulnerable atherosclerotic plaque metalloproteinases and foam cell phenotypes. Thromb Haemost 2009(101):1006–1011. https://doi.org/10.1160/TH08-07-0469

    Article  CAS  Google Scholar 

  9. Kedem O, Katchalsky A (1958) Thermodynamic analysis of the permeability of biological membranes to non-electrolytes. Acta Biochim Biophys Sin 27:229–246. https://doi.org/10.1016/0006-3002(58)90330-5

    Article  CAS  Google Scholar 

  10. Prosi M, Zunino P, Perktold K, Quarteroni A (2005) Mathematical and numerical models for transfer of low-density lipoproteins through the arterial walls: a new methodology for the model set up with applications to the study of disturbed lumenal flow. J Biomech 38(4):903–917. https://doi.org/10.1016/j.jbiomech.2004.04.024

    Article  CAS  PubMed  Google Scholar 

  11. Knight J, Olgac U, Saur SC, Poulikakos D, Marshall W Jr, Cattin PC, Alkadhi H, Kurtcuoglu V (2010) Choosing the optimal wall shear parameter for the prediction of plaque location—a patient-specific computational study in human right coronary arteries. Atherosclerosis 211(2):445–450. https://doi.org/10.1016/j.atherosclerosis.2010.03.001

    Article  CAS  PubMed  Google Scholar 

  12. Roustaei M, Nikmaneshi MR, Firoozabadi B (2018) Simulation of Low Density Lipoprotein (LDL) permeation into multilayer coronary arterial wall: Interactive effects of wall shear stress and fluid-structure interaction in hypertension. J Biomech 67:114–122. https://doi.org/10.1016/j.jbiomech.2017.11.029

    Article  PubMed  Google Scholar 

  13. Calvez V, Ebde A, Meunier N, Raoult A (2009) Mathematical modelling of the atherosclerotic plaque formation//Esaim: proceedings. EDP Sciences 28:1–12. https://doi.org/10.1051/proc/2009036

    Article  Google Scholar 

  14. Wong KKL, Thavornpattanapong P, Cheung SCP, Sun ZH, Tu JY (2012) Effect of calcification on the mechanical stability of plaque based on a three-dimensional carotid bifurcation model. BMC Cardiovasc Disord 12:1–18. https://doi.org/10.1186/1471-2261-12-7

    Article  CAS  Google Scholar 

  15. Pasqualino G (2019) Pattern formation in atherosclerotic plaques. http://hdl.handle.net/10222/76250. Accessed 26 Feb 2023

  16. Mirzaei NM, Weintraub WS, Fok PW (2020) An integrated approach to simulating the vulnerable atherosclerotic plaque. Am J Physiol Heart Circ Physiol 319(4):H835–H846. https://doi.org/10.1152/ajpheart.00174.2020

    Article  CAS  Google Scholar 

  17. Seneviratne AN, Edsfeldt A, Cole JE, Kassiteridi C, Swart M, Park I, Green P, Khoyratty T, Saliba D, Goddard ME, Sansom SN, Goncalves I, Krams R, Udalova IA, Monaco C (2017) Interferon regulatory factor 5 controls necrotic core formation in atherosclerotic lesions by impairing efferocytosis. Circulation 136(12):1140–1154. https://doi.org/10.1161/CIRCULATIONAHA.117.027844

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hao W, Friedman A (2014) The LDL-HDL profile determines the risk of atherosclerosis: a mathematical model. PLoS ONE 9(3):e90497. https://doi.org/10.1371/journal.pone.0090497

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Rostam-Alilou AA, Jarrah HR, Zolfagharian A, Bodaghi M (2022) Fluid–structure interaction (FSI) simulation for studying the impact of atherosclerosis on hemodynamics, arterial tissue remodeling, and initiation risk of intracranial aneurysms. Biomech Model Mechanobiol 21:1393–1406. https://doi.org/10.1007/s10237-022-01597-y

    Article  PubMed  PubMed Central  Google Scholar 

  20. Dirksen MT, van der Wal AC, van den Berg FM, van der Loos CM, Becker AE (1998) Distribution of inflammatory cells in atherosclerotic plaques relates to the direction of flow. Circulation 98(19):2000–2003. https://doi.org/10.1161/01.CIR.98.19.2000

    Article  CAS  PubMed  Google Scholar 

  21. Pedrigi RM, Mehta VV, Bovens SM, Mohri Z, Poulsen CB, Gsell W, Tremoleda JL, Towhidi L, Silva RD, Petretto E, Krams R (2016) Influence of shear stress magnitude and direction on atherosclerotic plaque composition. R Soc Open Sci. 3(10):160588. https://doi.org/10.1098/rsos.160588

    Article  PubMed  PubMed Central  Google Scholar 

  22. Jager NA, de WallisVries BM, Hillebrands JL, Harlaar NJ, Tio RA, Slart RHJA, van Dam GM, Boersma HH, Zeebregts CJ, Westra J (2016) Distribution of matrix metalloproteinase in human atherosclerotic carotid plaques and their production by smooth muscle cells and macrophage subsets. Mol Imaging Biol 18:283Y291. https://doi.org/10.1007/s11307-015-0882-0

    Article  CAS  Google Scholar 

  23. Morbiducci U, Kok AM, Kwak B, Stone PH, Steinman DA, Wentzel JJ (2016) Atherosclerosis at arterial bifurcations: evidence for the role of haemodynamics and geometry. Thromb Haemost 115(3):484–492. https://doi.org/10.1160/th15-07-0597

    Article  PubMed  Google Scholar 

  24. Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP (2020) Heart disease and stroke statistics-2020 update: a report from the American Heart Association. Circulation 141:e139-596. https://doi.org/10.1161/CIR.0000000000000757

    Article  PubMed  Google Scholar 

  25. Liu Y, Luo X, Jia H and Yu B. The Effect of Blood Pressure Variability on Coronary Atherosclerosis Plaques. Front Cardiovasc Med. 2022; 9:803810. https://doi.org/10.3389/fcvm.2022.803810

  26. Jarrah HR, Zolfagharian A, Bodaghi M (2022) Finite element modeling of shape memory polyurethane foams for treatment of cerebral aneurysms. Biomech Model Mechanobiol 21:383–399. https://doi.org/10.1007/s10237-021-01540-7

    Article  CAS  PubMed  Google Scholar 

  27. Sugiyama S, Niizuma K, Nakayama T, Shimizu H, Endo H, Inoue T, Fujimura M, Ohta M, Takahashi A, Tominaga T (2013) Relative residence time prolongation in intracranial aneurysms: a possible association with atherosclerosis. Neurosurgery 73(5):767–776. https://doi.org/10.1227/NEU.0000000000000096

    Article  PubMed  Google Scholar 

  28. He F, Hua L, Gao L (2017) Computational analysis of blood flow and wall mechanics in a model of early atherosclerotic artery. J Mech Sci Technol 31:1015–1020. https://doi.org/10.1007/s12206-017-0154-9

    Article  Google Scholar 

  29. Ahmadpour-B M, Nooraeen A, Tafazzoli-Shadpour M, Taghizadeh H (2021) Contribution of atherosclerotic plaque location and severity to the near-wall hemodynamics of the carotid bifurcation: an experimental study and FSI modeling. Biomech Model Mechanobiol 20:1069–1085. https://doi.org/10.1007/s10237-021-01431-x

    Article  PubMed  Google Scholar 

  30. Wang H, Uhlmann K, Vedula V, Balzani D, Varnik F (2022) Fluid-structure interaction simulation of tissue degradation and its effects on intra-aneurysm hemodynamics. Biomech Model Mechanobiol 21(2):671–683. https://doi.org/10.1007/s10237-022-01556-7

    Article  PubMed  PubMed Central  Google Scholar 

  31. Ebrahimi S, Fallah F (2022) Investigation of coronary artery tortuosity with atherosclerosis: a study on predicting plaque rupture and progression. Int J Mech Sci 223:107295. https://doi.org/10.1016/j.ijmecsci.2022.107295

    Article  Google Scholar 

  32. Dhawan SS, Avati Nanjundappa RP, Branch JR, Taylor WR, Quyyumi AA, Jo H, McDaniel MC, Suo J, Giddens D, Samady H (2010) Shear stress and plaque development. Expert Rev Cardiovasc Ther 8(4):545–556. https://doi.org/10.1586/erc.10.28

    Article  PubMed  PubMed Central  Google Scholar 

  33. Chalmers AD, Bursill CA, Myerscough MR (2017) Nonlinear dynamics of early atherosclerotic plaque formation may determine the efficacy of high-density lipoproteins (HDL) in plaque regression. PLoS ONE 12(11):e0187674. https://doi.org/10.1371/journal.pone.0187674

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Linsel-Nitschke P, Tall AR (2005) HDL as a target in the treatment of atherosclerotic cardio vascular disease. Nat Rev Drug Discovery 4(3):193–205. https://doi.org/10.1038/nrd1658

    Article  CAS  PubMed  Google Scholar 

  35. Chalmers AD, Cohen A, Bursill CA, Myerscough MR (2015) Bifurcation and dynamics in a mathematical model of early atherosclerosis. J Math Biol 71:1451–1480. https://doi.org/10.1007/s00285-015-0864-5

    Article  PubMed  Google Scholar 

  36. Bulelzai MAK, Dubbeldam JLA (2012) Long time evolution of atherosclerotic plaques. J Theor Biol 297:1–10. https://doi.org/10.1016/j.jtbi.2011.11.023

    Article  CAS  PubMed  Google Scholar 

  37. Carvalho V, Carneiro F, Ferreira AC, Gama V, Teixeira JC, Teixeira S (2021) Numerical study of the unsteady flow in simplified and realistic iliac bifurcation models. Fluids 6(8):284–302. https://doi.org/10.3390/fluids6080284

    Article  CAS  Google Scholar 

  38. Cilla M, Pena E, Martinez MA (2014) Mathematical modelling of atheroma plaque formation and development in coronary arteries. J R Soc Interface 11(90):20130866. https://doi.org/10.1098/rsif.2013.0866

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hariharan P, Nabili M, Guan A, Zderic V, Myers M (2017) Model for porosity changes occurring during ultrasound-enhanced transcorneal drug delivery. Ultrasound Med Biol 43(6):1223–1236. https://doi.org/10.1016/j.ultrasmedbio.2017.01.013

    Article  PubMed  PubMed Central  Google Scholar 

  40. Cheema TA, Kim GM, Lee CY, Hong JG, Kwak MK, Park CW (2014) Characteristics of blood vessel wall deformation with porous wall conditions in an aortic arch. Appl Rheol 24(2):17–24. https://doi.org/10.3933/applrheol-24-24590

    Article  Google Scholar 

  41. Palombo C, Kozakova M (2016) Arterial stiffness, atherosclerosis and cardiovascular risk: pathophysiologic mechanisms and emerging clinical indications. Vascul Pharmacol 77:1–7. https://doi.org/10.1016/j.vph.2015.11.083

    Article  CAS  PubMed  Google Scholar 

  42. Tang D, Yang C, Kobayashi S, Zheng J, Woodard PK, Teng ZZ, Billiar K, Bach R, Ku DN (2019) 3D MRI-based anisotropic FSI models with cyclic bending for human coronary atherosclerotic plaque mechanical analysis. J Biomech Eng 131(6):061010. https://doi.org/10.1115/1.3127253

    Article  Google Scholar 

  43. Silva T, Jäger W, Neuss-Radu M, Sequeira A (2020) Modeling of the early stage of atherosclerosis with emphasis on the regulation of the endothelial permeability. J Theor Biol 496:496–515. https://doi.org/10.1016/j.jtbi.2020.110229

    Article  CAS  Google Scholar 

  44. Chen C, Gu Y, Tu J, Guo X, Zhang D (2016) Microbubble oscillating in a microvessel filled with viscous fluid: a finite element modeling study. Ultrasonics 66:54–64. https://doi.org/10.1016/j.ultras.2015.11.010

    Article  CAS  PubMed  Google Scholar 

  45. Kirillova IV, Kossovich EL, Safonov RA, Chelnokova NO, Golyadkina AA; Shevtsova MS (2016) Finite Element Modeling of Atherosclerotic Plaque Evolution vol 3. 2016 3rd International Conference on Information Science and Control Engineering (ICISCE) IEEE. pp 973–977. https://doi.org/10.1109/ICISCE.2016.211

  46. Ball RY, Stowers EC, Burton JH, Cary NRB, Skepper JN, Mitchinson MJ (1995) Evidence that the death of macrophage foam cells contributes to the necrotic core of atheroma. Atherosclerosis 114(1):45–54. https://doi.org/10.1016/0021-9150(94)05463-

    Article  CAS  PubMed  Google Scholar 

  47. Yuan Y, Li P, Ye J (2012) Lipid homeostasis and the formation of macrophage-derived foam cells in atherosclerosis. Protein Cell 3(3):173–181. https://doi.org/10.1007/s13238-012-2025-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lei W, Hu J, Liu Y, Liu W, Chen XK (2021) Numerical evaluation of high-intensity focused ultrasound-induced thermal lesions in atherosclerotic plaques. Math Biosci Eng 18:1154–1168. https://doi.org/10.3934/mbe.2021062

    Article  PubMed  Google Scholar 

  49. Esterbauer H, Striegl G, Puhl H, Rotheneder M (1989) Continuous monitoring of in vitro oxidation of human low density lipoprotein. Free Radical Res 6(1):67–75. https://doi.org/10.3109/10715768909073429

    Article  CAS  Google Scholar 

  50. Schiesser WE (2018) PDE models for atherosclerosis computer implementation in R. J. synthesis lectures on biomedical engineering. Biomed Eng Lett 11:1–141. https://doi.org/10.2200/S00877ED1V01Y201810MAS022

    Article  Google Scholar 

  51. Kruth HS, Huang W, Ishii I, Zhang WY (2002) Macrophage foam cell formation with native low-density lipoprotein. J Biol Chem 77(37):34573–34580. https://doi.org/10.1074/jbc.M205059200

    Article  Google Scholar 

  52. Taylor BA, Panza G, Pescatello LS, Chipkin S, Gipe D, Shao WP, White CM, Thompson PD (2014) Serum PCSK9 levels distinguish individuals who do not respond to high-dose statin therapy with the expected reduction in LDL-C. J Lipids. 2014:140723. https://doi.org/10.1155/2014/140723

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Akyildiz AC, Speelman L, Brummelen VH, Gutiérrez MA, Virmani R, Lugt AV, van der Steen FWA, Wentzel JJ, Gijsen F (2011) Effects of intima stiffness and plaque morphology on peak cap stress. Biomed Eng Online 10:1–13. https://doi.org/10.1186/1475-925X-10-25

    Article  Google Scholar 

  54. Xie J, Zhou J, Fung YC (1995) Bending of blood vessel wall: stress-strain laws of the intima-media and adventitial layers. J Biomech Sci Eng 1(136):136–145. https://doi.org/10.1115/1.2792261

    Article  Google Scholar 

  55. Khanafer K, Berguer R (2009) Fluid–structure interaction analysis of turbulent pulsatile flow within a layered aortic wall as related to aortic dissection. J biomech 42(16):2642–2648. https://doi.org/10.1016/j.jbiomech.2009.08.010

    Article  PubMed  Google Scholar 

  56. Chen XK, Hu XY, Jia P, Xie ZX, Liu J (2021) Tunable anisotropic thermal transport in porous carbon foams: The role of phonon coupling. Int J Mech Sci 306:106576. https://doi.org/10.1016/j.ijmecsci.2021.106576

    Article  Google Scholar 

  57. Sun J, Balu N, Hippe DS, Xue YJ, Dong L, Zhao XH, Li FY, Xu DX, Hatsukami TS, Yuan C (2013) Subclinical carotid atherosclerosis: short-term natural history of lipid-rich necrotic core—a multicenter study with MR imaging. Radiology 268(1):61–68. https://doi.org/10.1148/radiol.13121702

    Article  PubMed  Google Scholar 

  58. Chang HJ, Lin FY, Lee SE et al (2018) Coronary atherosclerotic precursors of acute coronary syndromes. J Am Coll Cardiol 71(22):2511–2522. https://doi.org/10.1016/j.jacc.2018.02.079

    Article  PubMed  PubMed Central  Google Scholar 

  59. Getz GS, Reardon CA (2012) Animal models of atherosclerosis. Prog Mol Biol Transl Sci 32(5):1–23. https://doi.org/10.1016/B978-0-12-394596-9.00001-9

    Article  CAS  Google Scholar 

  60. Feuchtner G, Langer C, Barbieri F, Beyer C, Dichtl WG, Friedrich G, Schgoer W, Widmann G, Plank F (2021) The effect of omega-3 fatty acids on coronary atherosclerosis quantified by coronary computed tomography angiography. Clin Nutr 40(3):1123–1129. https://doi.org/10.1016/j.clnu.2020.07.016

    Article  CAS  PubMed  Google Scholar 

  61. Zhao X, Hippe DS, Li R, Canton GM, Sui BB, Song Y, Li FY, Xue YJ, Sun J, Yamada K, Hatsukami TS, Xu DX, Wang MX, Yuan C (2017) Prevalence and characteristics of carotid artery high-risk atherosclerotic plaques in Chinese patients with cerebrovascular symptoms: a Chinese atherosclerosis risk evaluation II study. J Am Heart Assoc 6(8):e005831. https://doi.org/10.1161/JAHA.117.005831

    Article  PubMed  PubMed Central  Google Scholar 

  62. Virmani R, Kolodgie FD, Burke AP, Finn AV, Gold HK, Tulenko TN, Wrenn SP, Narula J (2005) Atherosclerotic plaque progression and vulnerability to rupture: angiogenesis as a source of intraplaque hemorrhage. Arterioscler Thromb Vasc Biol 25(10):2054–2061. https://doi.org/10.1161/01.ATV.0000178991.71605.18

    Article  CAS  PubMed  Google Scholar 

  63. Li AC, Glass CK (2002) The macrophage foam cell as a target for therapeutic intervention. Nat Med 8(11):1235–1242. https://doi.org/10.1038/nm1102-1235

    Article  CAS  PubMed  Google Scholar 

  64. Tash OA, Razavi SE (2012) Numerical investigation of pulsatile blood flow in a bifurcation model with a non-planar branch: the effect of different bifurcation angles and non-planar branch. Bioimpacts 2(4):195–205. https://doi.org/10.5681/bi.2012.023

    Article  Google Scholar 

  65. Velican D, Velican C (1989) Coronary anatomy and microarchitecture as related to coronary atherosclerotic involvement. Med Interne 27(4):257–262. https://doi.org/10.1007/978-0-387-76852-6_4

    Article  CAS  PubMed  Google Scholar 

  66. Nishizawa A, Suemoto CK, Farias-Itao DS, Campos FM, Karen C, Silva S, Bittencourt MS, Grinberg LT, Leite REP, Ferretti-Rebustini REL, Farfel JM, Jacob-Filho W, Pasqualucci CA (2017) Morphometric measurements of systemic atherosclerosis and visceral fat: Evidence from an autopsy study. PLoS ONE 12(10):e0186630. https://doi.org/10.1371/journal.pone.0186630

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Wang X, Ge J (2021) Haemodynamics of atherosclerosis: a matter of higher hydrostatic pressure or lower shear stress? Cardiovasc Res 117(4):e57–e59. https://doi.org/10.1093/cvr/cvab001

    Article  CAS  PubMed  Google Scholar 

  68. Meng H, Tutino VM, Xiang J, Siddiqui A (2014) High WSS or low WSS? Complex interactions of hemodynamics with intracranial aneurysm initiation, growth, and rupture: toward a unifying hypothesis. Am J Neuroradiol 35(7):1254–1262. https://doi.org/10.3174/ajnr.A3558

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Xiong H, Liu X, Tian X, Pu L, Zhang HY, Lu MH, Huang WH, Zhang YT (2014) A numerical study of the effect of varied blood pressure on the stability of carotid atherosclerotic plaque. Biomed Eng Online 13(1):1–13. https://doi.org/10.1186/1475-925X-13-152

    Article  Google Scholar 

  70. Manning-Tobin JJ, Moore KJ, Seimon TA, Bell SA, Sharuk M, Alvarez-Leite JI, Menno P, Winther JD, Tabas I, MasonFreeman W (2009) Loss of SR-A and CD36 activity reduces atherosclerotic lesion complexity without abrogating foam cell formation in hyperlipidemic mice. Arterioscler Thromb Vasc Biol 29(1):19–26. https://doi.org/10.1161/ATVBAHA.108.176644

    Article  CAS  PubMed  Google Scholar 

  71. Yang S, Wang Q, Shi W, Guo WC, Jiang ZI, Gong XB (2019) Numerical study of biomechanical characteristics of plaque rupture at stenosed carotid bifurcation: a stenosis mechanical property-specific guide for blood pressure control in daily activities. Acta Mech Sin 35:1279–1289. https://doi.org/10.1007/s10409-019-00883-w

    Article  CAS  Google Scholar 

  72. Campbell IC, Weiss D, Suever JD, Virmani R, Veneziani A, Vito RP, Oshinski JN, Taylor WR (2013) Biomechanical modeling and morphology analysis indicates plaque rupture due to mechanical failure unlikely in atherosclerosis-prone mice. Am J Physiol Heart Circ Physiol 304(3):H473–H486. https://doi.org/10.1152/ajpheart.00620.2012

    Article  CAS  PubMed  Google Scholar 

  73. Pu L, Xiong H, Liu X (2014) Quantifying effect of blood pressure on stress distribution in atherosclerotic plaque. Int Conf Health Informaticsy 42(1):P216–P219. https://doi.org/10.1007/978-3-319-03005-0_55

  74. Huang Y, Teng ZZ, Sadat U, Graves MJ, Bennett MR, Gillard JH (2014) The influence of computational strategy on prediction of mechanical stress in carotid atherosclerotic plaques: Comparison of 2D structure-only, 3D structure-only, one-way and fully coupled fluid-structure interaction analyses. J Biomech 47(6):1465–1471. https://doi.org/10.1016/j.jbiomech.2014.01.030

    Article  PubMed  PubMed Central  Google Scholar 

  75. Manduteanu I, Simionescu M (2012) Inflammation in atherosclerosis: a cause or a result of vascular disorders? J Cell Mol Med 16(9):1978–1990. https://doi.org/10.1111/j.1582-4934.2012.01552.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Fuchs FD, Whelton PK (2020) High blood pressure and cardiovascular disease. Hypertension 75(2):285–329. https://doi.org/10.1161/HYPERTENSIONAHA.119.14240

    Article  CAS  PubMed  Google Scholar 

  77. Eshtehardi P, Mcdaniel MC, Suo J, Dhawan SS, Timmins LH, Binongo JNG, Golub LJ, Corban MT, Finn AV, Oshinski JN (2012) Association of coronary wall shear stress with atherosclerotic plaque burden, composition, and distribution in patients with coronary artery disease. J Am Heart Assoc 1(4):e002543. https://doi.org/10.1161/JAHA.112.002543

    Article  PubMed  PubMed Central  Google Scholar 

  78. Cecchi E, Giglioli C, Valente S, Lazzeri C, Gensini GF, Gensini R, Gensini L (2011) Role of hemodynamic shear stress in cardiovascular disease. Atherosclerosis 214(2):249–256. https://doi.org/10.1016/j.atherosclerosis.2010.09.008

    Article  CAS  PubMed  Google Scholar 

  79. Kim S, Giddens DP (2015) Thrombosis formation on atherosclerotic lesions and plaque rupture. J Biomech Sci Eng 137(4):0410071–04100711. https://doi.org/10.1111/joim.12296

    Article  CAS  Google Scholar 

  80. Wang LM, Hu JW, Lei WR, Liu WY, Liu YT (2019) Mechanical stress analysis of defects in atherosclerotic plaque. J Anhui Normal Univ. 42(6):538–543. https://doi.org/10.14182/J.cnki.1001-2443.2019.06.006

    Article  Google Scholar 

  81. Li ZY, Howarth S, Tang T, Martin G, Jean Marie UK, Jonathan G (2007) Does calcium deposition play a role in the stability of atheroma? Location may be the key. Cerebrovasc Dis 24(5):452–459. https://doi.org/10.1159/000108436

    Article  PubMed  Google Scholar 

  82. Theofilatos K, Stojkovic S, Hasman M, Baig F, Barallobre-Barreiro J, Schmidt L, Yin S, Yin X, Burnap S, Singh B (2022) A proteomic atlas of atherosclerosis: regional proteomic signatures for plaque inflammation and calcification. Cardiovasc Res. https://doi.org/10.1093/cvr/cvac066.204

    Article  PubMed  PubMed Central  Google Scholar 

  83. Bajaj R, Eggermont J, Grainger SJ, Raber L, Parasa R, Khan AHA, Costa C, Erdogan E, Hendricks MJ, Chandrasekharan KH (2022) Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: validation against histology. Atherosclerosis. https://doi.org/10.1016/j.atherosclerosis.2022.01.021

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Nature Science Foundation of China (No.12274200、11774088) and Hengyang science and technology plan projects (No.202250045335).

Author information

Authors and Affiliations

  1. School of Physics and Electronics, Hunan Normal University, Changsha, 410006, China

    Weirui Lei & Shengyou Qian

  2. Hengyang Medical School, University of South China, Hengyang, 421001, China

    Xin Zhu

  3. School of Mathematics and Physics, University of South China, Hengyang, 421001, China

    Jiwen Hu

Authors
  1. Weirui Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shengyou Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xin Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiwen Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Shengyou Qian or Jiwen Hu.

Ethics declarations

Conflict of Interest

The authors declared that no conflict of interest among all authors.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lei, W., Qian, S., Zhu, X. et al. Haemodynamic Effects on the Development and Stability of Atherosclerotic Plaques in Arterial Blood Vessel. Interdiscip Sci Comput Life Sci 15, 616–632 (2023). https://doi.org/10.1007/s12539-023-00576-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12539-023-00576-w

Keywords

Search

Navigation