Atherosclerosis is a disease of the cardiovascular system where a stenosis may develop in an artery which is an abnormal narrowing in the blood vessel that adversely affects the blood flow. Due to the constriction of the blood vessel, the flow is disturbed, forming a jet and recirculation downstream of the stenosis. Dynamic pressure fluctuations on the inner wall of the blood vessel leads to the vibration of the vessel structure and acoustic energy is propagated through the surrounding tissue that can be detected on the skin surface. Acoustic energy radiating from the interaction of blood flow and stenotic blood vessel carries valuable information from a diagnostic perspective. In this study, a constricted blood flow is modeled by using ADINA finite element analysis software together with the blood vessel in the form of a thin cylindrical shell with an idealized blunt constriction. The flow is considered as incompressible and Newtonian. Water properties at indoor temperature are used for the fluid model. The diameter of the modeled vessel is 6.4 mm with 87% area reduction at the throat of the stenosis. The flow is investigated for Reynolds numbers 1000 and 2000. The problem is handled in three parts which are rigid wall Computational Fluid Dynamics (CFD) solution, structural analysis of fluid filled cylindrical shell, and Fluid Structure Interaction (FSI) solutions of fluid flow and vessel structure. The pressure fluctuations and consequential vessel wall vibrations display broadband spectral content over a range of several hundred Hz with strong fluid-structural coupling. Maximum dynamic pressure and vibration amplitudes are observed around the reattachment point of the flow near the exit of the stenosis and this effect gradually decreases along downstream of flow. Results obtained by the numerical simulations are compared with relevant studies in the literature and it is concluded that ADINA can be used to investigate these types of problems involving high frequency pressure fluctuations of the fluid and the resulting vibratory motion of the surrounding blood vessel structure.

Hemodynamic factors play a role in atherogenesis and the localization of atherosclerotic plaques. The human aorta and coronary arteries are susceptible to arterial disease, and there have been many studies of flows in models of these vessels. However, previous work has been limited in that investigations have not modeled both the geometry and flow conditions in specific individuals. The first aim of the research was to develop a methodology that combined computational fluid dynamics (CFD) and magnetic resonance imaging (MRI) to simulate the blood flow patterns found in the human aorta. The methodology included MR image processing, 3D model reconstruction and flow simulation using in vivo velocity boundary conditions obtained from phase contrast (PC)-MRI scanning. The CFD simulations successfully reproduce the unusual right-hand helical flow pattern that has been reported in the ascending aorta, giving confidence in the accuracy of the methodology. The second aim was to investigate the causes of the right-hand helical flow. It was found that the correct flow dynamics could only be produced by including the specific aortic motion caused by the beating heart; and it is concluded that this is a significant factor in producing the observed in vivo helical flow patterns. The entrance flows of coronary arteries are expected to be affected by flow in the aortic root, and the third aim was to explore these effects using models that include aorta and coronary arteries. The simulation results demonstrate that a pair of axial vortexes with different rotating directions exists in the entrance segments of the right and left coronary arteries during systole and early diastole, producing asymmetrical wall shear stress (WSS) distributions. The last aim of the research was to examine possible relationships between WSS distributions induced by the entry flow patterns and the frequency distributions of atherosclerosis in the proximal segments of coronary arteries reported in the clinical literature. A close correspondence between low WSS and higher frequency of plaque occurrence was observed. The tools developed in this study provide a promising avenue for future study of cardiovascular disease because of the ability to investigate phenomena in individual human subjects.

Ce travail a pour objectif de générer des modèles vasculaires et de simuler des écoulements sanguins réalistes à l'intérieur de ces modèles. La première étape consiste à segmenter/reconstruire le volume 3D du réseau vasculaire. Une fois de tels volumes vasculaires segmentés et maillés, il est alors possible de simuler des écoulements sanguins à l'intérieur de ceux-ci. Pour la segmentation, nous utilisons une approche variationnelle. Nous proposons un premier modèle qui inclut un a priori de tubularité dans les modèles de débruitage ROF et TV-L1. Néanmoins, bien que ces modèles permettent de réhausser les vaisseaux, ils ne permettent pas de les segmenter. C'est pourquoi nous proposons un deuxième modèle amélioré qui inclut à la fois un a priori de tubularité et de direction dans le modèle de segmentation de Chan-Vese. Les résultats sont présentés sur des images synthétiques 2D, ainsi que sur des images rétiniennes. En ce qui concerne la simulation, nous nous intéressons d'abord au réseau veineux cérébral, encore peu étudié. Les équations de la dynamique des fluides qui régissent les écoulements sanguins dans notre géométrie sont alors les équations de Navier-Stokes. Pour résoudre ces équations, la méthode classique des caractéristiques est comparée avec un schéma d'ordre plus élevé. Ces deux schémas sont validés sur des solutions analytiques avant d'être appliqués aux cas réalistes du réseau veineux cérébral premièrement, puis du polygone artériel de Willis. / The aim of this work is to generate vascular models and simulate blood flows inside these models. A first step consists of segmenting/reconstructing the 3D volume of the vascular network. Once such volumes are segmented and meshed, it is then possible to simulate blood flows. For segmentation purposes, we use a variational approach. We first propose a model that embeds a vesselness prior in the denoising models ROF and TV-L1. Although these models can enhance vessels, they are not designed for segmentation. Then, we propose a second, improved model that includes both vesselness and direction priors in the Chan-Vese segmentation model. The results are presented on 2D synthetic images, as well as retinal images. In the second part, devoted to simulation, we first focus on the cerebral venous network, that has not been intensively studied. The equations governing blood flows inside our geometry are the Navier-Stokes equations. For their resolution, the classical method of characteristics is compared with a high-order scheme. Both schemes are validated on analytical solutions before their application on the realistic cases of the cerebral venous network, and the arterial polygon of Willis.