On the evolution of stresses in a stratified atherosclerotic arterial tissue

Arthesh Basak1, Shramika Annreddy1, Surya Teja Chinnala1

  • 1Department of Civil Engineering, GITAM School of Technology, Visakhapatnam, India.

Insights

This study compares stress in healthy and diseased coronary arteries. Atherosclerosis significantly alters stress distribution, potentially leading to plaque rupture and heart attack.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Research
  • Computational Mechanics

Background:

  • Cardiovascular diseases are the leading global cause of death.
  • Coronary artery disease, characterized by atherosclerosis, involves plaque buildup, narrowing the artery lumen.
  • This narrowing alters stress distribution, increasing risks of plaque rupture, myocardial infarction, and angina.

Purpose of the Study:

  • To analyze and compare the stress evolution in a sclerotic coronary artery versus a healthy artery.
  • To model the mechanical response of arterial tissue under simulated physiological conditions.

Main Methods:

  • A three-layered arterial tissue model was created using finite element software.
  • Contact modeling was implemented to simulate layer adhesion.
  • A 50% lumen reduction plaque was modeled using incompressible hydrostatic fluid elements.
  • Axisymmetric finite element analysis was performed under radial pressure.

Main Results:

  • The study analyzed the evolution of Von Mises stress, shear stresses, and contact stresses.
  • Significant differences in stress distribution were observed between the diseased and healthy coronary artery models.
  • Contact stresses on the interface between arterial layers were particularly highlighted.

Conclusions:

  • The finite element model effectively simulated stress changes in atherosclerotic coronary arteries.
  • Atherosclerosis induces critical alterations in arterial tissue stress, providing insights into disease progression.
  • Further research can utilize these findings to explore therapeutic interventions and predict cardiovascular events.

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