Investigation of Carotid Atherosclerosis Ultrasound Image Using Computational Hemodynamics

Abstract

Brain stroke is a major cause of mortality and disability in recent decades. Carotid atherosclerosis is considered an important contributor to the growing problem of brain stroke. Carotid atherosclerosis resulted from an accumulation of fat, cholesterol, Calcium, and other materials in arterial walls that create complex hemodynamics. Furthermore, elevated blood viscosity is associated with atherosclerosis and its growth. Hence, increased blood viscosity is also an independent risk factor for atherosclerotic diseases. Though conventional ultrasound techniques used for flow estimation due to the real time scanning capability, still there are scopes to enhance the image quality. Moreover, atherosclerosis related viscosity changes effects are not considered in conventional techniques. The knowledge of the carotid artery hemodynamics resulted due to atherosclerosis with different level of blood viscosity can provide more information on artery stenosis and symptoms, and the risk of stroke. Therefore, improvement in flow imaging has great clinical importance to understand the origin and evolution of disease. Investigation and detection of viscosity change and its effect might be helpful for better diagnosis of carotid atherosclerosis, which is a major emphasis of this thesis. In this simulation work, hemo-disturbances have been investigated in realistic normal and atherosclerotic carotid using finite element method (FEM) based computational fluid dynamics (CFD) under different viscosities consideration. The computed data has been used to simulate color flow image of blood velocities using ultrasound radio frequency (RF) signals to considering ultrasound potentiality in atherosclerosis diagnosis. The ultrasound simulated flow characteristics have been compared with FEM computed flow behavior and found a good agreement between them. It has been observed that the blood velocities increase noticeably in carotid atherosclerotic growths whereas velocities are almost uniform in the normal carotid. The severity stages of the models have been examined quantitatively. It is also found that viscosity induced contrast is not negligible and importantly, it is detectable from multiple steps ultrasound flow images. The findings of this study suggest that ultrasound based blood flow image can detect the viscosity change effect related to atherosclerosis growth. So, incorporation of the viscosity changes contrast can enhance the quality of ultrasound flow image. It is expected that the outcomes of this thesis work might be useful to diagnosis the present conditions and predict the future progressions of carotid atherosclerosis to minimize the risk of stroke.