Advertisement

CMBEBIH 2017 pp 269-274 | Cite as

Computational modeling of plaque development in the coronary arteries

  • Nenad Filipovic
  • Velibor Isailovic
  • Zarko Milosevic
  • Dalibor Nikolic
  • Igor Saveljic
  • Milos Radovic
  • Milica Nikolic
  • Bojana Cirkovic-Andjelkovic
  • Exarchos Themis
  • Dimitris Fotiadis
  • Gualtiero Pelosi
  • Oberdan Parodi
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 62)

Abstract

Computational study for plaque formation and development for the patient specific coronary arteries was performed. Transport of macrophages and oxidized LDL distribution for the initial plaque grow model inside the intimal area was implemented. Mass transport of LDL through the wall and the simplified inflammatory process was firstly solved. The Navier-Stokes equations govern the blood motion in the lumen, the Darcy law is used for model blood filtration, Kedem-Katchalsky equations for the solute and flux exchanges between the lumen and the intima. The system of three additional reaction-diffusion equations that models the inflammatory process and lesion growth model in the intima was used. Some examples of computer simulation for plaque formation and progression for the specific patient for left and right coronary arteries are presented. Determination of plaque location and plaque volume with computer simulation for a specific patient shows a potential benefit for prediction of disease progression.

Keywords

Wall Shear Stress Plaque Formation Shear Stress Distribution Plaque Volume Oscillatory Shear Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Begent N., Born G.V., (1970) Nature, 227: 926–930.Google Scholar
  2. 2.
    Filipovic N, Zhongzhao Teng, Milos Radovic, Igor Saveljic, Dimitris Fotiadis and Oberdan Parodi (2013), Computer simulation of three dimensional plaque formation and progression in the carotid artery, Medical & Biological Engineering & Computing, DOI: 10.1007/s11517-012-1031-4.Google Scholar
  3. 3.
    Filipovic N., Mijailovic S., Tsuda A., Kojic M., (2006). An implicit algorithm within the Arbitrary Lagrangian-Eulerian formulation for solving incompressible fluid flow with large boundary motions, Comp. Meth. Appl. Mech. Eng., 195: 6347-6361.Google Scholar
  4. 4.
    Filipovic N., Rosic M., Tanaskovic I., Milosevic Z., Nikolic D., Zdravkovic N., Peulic A., Fotiadis D., Parodi O., (2012) ARTreat project: Three-dimensional Numerical Simulation of Plaque Formation and Development in the Arteries, IEEE Trans Inf Technol Biomed, Vol. 16(2): 272-278.Google Scholar
  5. 5.
    Himburg, H., Grzybowski, D., Hazel, A., LaMack, J. Li X. and Friedman M., (2004). Spatial comparison between wall shear stress measures and porcine arterial endothelial permeability. Am J Physiol Hear Circ Pysiol 286: 1916-1922.Google Scholar
  6. 6.
    Kedem, O., Katchalsky, A., (1958) Thermodynamic analysis of the permeability of biological membranes to non-electrolytes. Biochim. Biophys. 27: 229–246.Google Scholar
  7. 7.
    Kedem, O., Katchalsky, A., (1961) A physical interpretation of the phenomenological coefficients of membrane permeability. The Journal of General Physiology, 45, 143–179.Google Scholar
  8. 8.
    Kojic M., Filipovic N., Stojanovic B., Kojic N., (2008). Computer Modeling in Bioengineering: Theoretical Background, Examples and Software. John Wiley and Sons, Chichester, England.Google Scholar
  9. 9.
    Loscalzo J., Schafer A. I., (2003) Thrombosis and Hemorrhage. Third edition. Lippincott Williams & Wilkins, Philadelphia.Google Scholar
  10. 10.
    Meyer G., Merval R., Tedgui A., (1996). Effects of pressure-induced stretch and convection on low-Density Lipoprotein and Albumin uptake in the rabbit aortic wall. Circulation Research, 79: 532-540.Google Scholar
  11. 11.
    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 luminal flow. J. Biomech., 38: 903–917.Google Scholar
  12. 12.
    Quarteroni A., Valli A., (1999). Domain Decomposition Methods for Partial Differential Equations. Oxford University Press.Google Scholar
  13. 13.
    Quarteroni A., Veneziani A., Zunino P., (2002). Mathematical and numerical modeling of the solute dynamics in blood flow and arterial walls. SIAM Journal of Numerical Analysis, 39: 1488–1511.Google Scholar
  14. 14.
    Ross R., (1993). Atherosclerosis: a defense mechanism gone awry. Am J Pathol., 143: 987–1002.Google Scholar
  15. 15.
    Tarbell, J. M., (2003). Mass transport in arteries and the localization of atherosclerosis. Annual Review of Biomedical Engineering, 5: 79–118.Google Scholar
  16. 16.
    Taylor CA, Hughes T.J.R., Zarins C.K. (1998), Finite element modeling of blood flow in arteries, Comp Meth Appl Mech Eng, 158: 155-196.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Nenad Filipovic
    • 1
    • 2
  • Velibor Isailovic
    • 1
    • 2
  • Zarko Milosevic
    • 1
    • 2
  • Dalibor Nikolic
    • 1
    • 2
  • Igor Saveljic
    • 1
    • 2
  • Milos Radovic
    • 1
    • 2
  • Milica Nikolic
    • 1
    • 2
  • Bojana Cirkovic-Andjelkovic
    • 1
    • 2
  • Exarchos Themis
    • 3
  • Dimitris Fotiadis
    • 3
  • Gualtiero Pelosi
    • 4
  • Oberdan Parodi
    • 4
  1. 1.Faculty of EngineeringUniversity of KragujevacKragujevacSerbia
  2. 2.BioIRC Bioengineering Research and Development CenterKragujevacSerbia
  3. 3.University of IoanninaIoanninaGreece
  4. 4.National Research Council PisaPisaItaly

Personalised recommendations