Subclinical atherosclerosis is an important area of research to evaluate stroke risk and predict localization of plaque. The current methods for detecting atherosclerosis risk are insufficient because it is based on The Framingham Risk Score and carotid intima media thickness, therefore an engineering detection model based on quantifiable data is needed. Laminar and turbulent flow, dictated by Reynolds number and relative roughness, was modeled through the carotid artery bifurcation to compare shear stress and shear rate. Computer-aided design and fluid flow software were used to model hemodynamics through the carotid artery. Data from the model was derived from governing equations programmed in COMSOL for both laminar and turbulent flow. A carotid artery model is accurate enough to describe how relative roughness, flow profiles, and shear rate can be a good prediction of subclinical atherosclerosis.

With the high mortality rate of cardiovascular disease, it is important to study the early signs. The early detection of cardiovascular disease can lead to saved lives. Currently the most prevalent detection methods are the Framingham Risk Score and the carotid intima media thickness, both of which are insufficient. The necessary tool for early detection requires a uniform quantification system. The stimulus leading to endothelial dysfunction, the most significant predictor of a major adverse cardiovascular event (MACE)—and subsequently subclinical atherosclerosis—is reduced shear stress. Increased surface relative roughness affects the flow profile transition from laminar to turbulent resulting in reduced shear rate. The relationship between the shear stress and the relative roughness was studied using a computer model for fluid flow. A model of the brachial artery was generated to study its hemodynamics. Roughness values for both laminar and turbulent flow were calculated to use with the governing equations programmed in COMSOL Multiphysics. With all other factors remaining constant in the model, the roughness values were changed. From the model profile plots, line graphs, and numeral data are generated. This data provides information about how the shear stress and the shear rate change with respect to the relative roughness value. The models with different wall boundary conditions—slip versus Navier slip—were unable to be directly compared due to the differences in value magnitude. When the flow profile transitions from laminar to turbulent, there is a corresponding drop in both the shear stress and the shear rate values. Additional testing is required to determine a critical relative roughness value for this change in cumulative shear.

Cardiovascular disease is the leading cause of death globally and is responsible for taking 17.9 million lives per year. Despite the use of clinical treatments and detection methods, there remains a large population of individuals that suffer from CVD whose symptoms are left undetected and untreated prior to a life-threatening cardiac event. This highlights a need for an early detection method that can prevent the manifestation and worsening of the disease as well as address limitations of current early detection methods. An area of interest for early detection of CVD is subclinical atherosclerosis, which is the long, early, asymptomatic stage of plaque formation. Subclinical atherosclerosis has been namely associated with endothelial dysfunction and is the result of the pathological state of the endothelium due to its impact on vascular homeostasis, thrombosis, and vascular tone. Endothelial dysfunction is a result of several factors contributing to and promoting inflammation and results in changes in biological pathways that can alter the surface of the endothelium. This surface modification or added roughness changes the flow profile from laminar to turbulent flow due to the decreased shear stress on the vascular wall. Current detection methods such as carotid intima media thickness (CIMT) and flow-mediated dilation (FMD) targeted at identifying the early stages of atherosclerosis present limitations such as identifying late-stage effects of plaque formation and subjective readings highlight the need for a different approach to early detection. This experimental study aims to present a possible method of detecting the morphological changes of the endothelium due to inflammation through acoustic analysis of flow. Three silicone artery phantom groups were created with different degrees of inner diameter surface roughness to explore the relationship between relative roughness and sound associated with fluid flow. The results of this study are power spectral density graphs (PSD) which show frequency peaks associated with each of the phantoms at a theoretical laminar and turbulent Reynolds number. The PSD graphs show that there is a difference in frequency response between a smooth and rough artery phantom at the same flow rate providing preliminary support that sound analysis of fluid flow could provide information regarding early-stage cardiovascular disease.