Modeling and Analysis in Large Hyperelastic Deformation of the Stress Distribution in an Atherosclerotic Plaque.

Autor: Amor, Bouaricha, Ammar, Haiahem, Benyebka, Bou-Said
Předmět:
Zdroj: International Review of Physics; Jun2009, Vol. 3 Issue 3, p179-185, 7p
Abstrakt: Despite the current extensive development of medical imaging, clinicians are still not able to diagnose the vulnerability of an atherosclerotic plaque and to prevent its rupture with sufficient precision. The rupture of plaque is the main reason for the different presentations of cardiac, cerebral, renal or lower limb ischemia. Cyclical and pulsating properties of blood flow can lead to a rupture of the vessel by fatigue. This rupture is often linked to stress concentration (SC) resulting from the vessel geometry and blood pulse. Amplitude and topography of the concentrated stress are linked to blood pressure, stenosis rate (SR) and to the shape and volume of the plaque. The mechanical properties of the plaque components as well as the thickness of the fibrous cap (FC) and the type of remodeling are also factors which can influence the stability of the atherosclerosis plaque. To provide markers that can help in the diagnosis of vulnerable plaque, the purpose of this study is to model and analyze the artery, using the finite element method with the large deformation assumption, to determine the stress field generated during the cardiac cycle. Amplitude and location of the SC are determined for every parameter considered as a vulnerability factor. The various simulations on a model of atherosclerotic plaque in an eccentric artery case with stenosis demonstrate that thinning of the fibrous cap, the increase of the angle β (a characteristic of a constrictive remodeling) and the lack of rigidity of the lipidic core (LC), as well as increase of its volume, decrease individually the plaque resistance to rupture. The increase of the stenosis rate, coupled with other geometrical factors, increases the magnitude of the stress, which reaches its maximum for SR = 40 %. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index