Abstract

Cardiovascular diseases such as heart attack and stroke are often caused by rupture of a vulnerable atherosclerotic plaque. The mechanisms governing plaque progression and causing plaque rupture are not fully understood. 3D multi-component FSI models for atherosclerotic plaques based on in vivo/ex vivo MRI images were introduced to investigate plaque progression and rupture. MRI images of human carotid atherosclerotic plaques were acquired using multi-contrast techniques. Both artery wall and plaque components were assumed to be hyperelastic, isotropic, incompressible and homogeneous. The modified Mooney-Rivlin model was used for all the materials with parameters selected to fit experimental data. Blood flow was assumed to be laminar, Newtonian, viscous and incompressible. The incompressible Navier-Stokes equations were used as the governing equations. The fully coupled 3D multicomponent FSI models were solved using ADINA (ADINA R&D, Watertown, MA, USA) to perform flow and stress/strain analysis and seek critical information which may be related to plaque progression and rupture. It is wellknown that low and oscillating flow wall shear stresses play an important role in atherosclerotic plaque initiation and progression. For advanced atherosclerotic plaques, our results indicate that flow wall shear stress is considerably higher in the stenotic region because of lumen narrowing. While the low and oscillating flow shear stress hypothesis correctly identifies locations of intimal thickening, it cannot explain why advanced plaques continue to grow under high flow shear stress conditions. Positive and negative correlations of flow shear stress and wall maximum principal stress with respect to wall thickness were found from our investigations which lead to a possible new hypothesis for intermediate and advanced plaque progression: Low structure stress has positive correlation with plaque wall thickness, and may create favorable mechanical conditions in the plaque for intermediate and advanced plaque progression. Acknowledgement: This research was supported by NIH grant R01 EB004759.

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