Predicting the onset of consequent stenotic regions in carotid arteries using computational fluid dynamics

Carotid arteries are the major blood vessels that carry oxygenated blood to the brain and face. Carotid artery disease is characterized by the narrowing of the carotid arteries due to plaque buildup at the arterial walls, leading to major consequences such as brain stroke and death. Hemodynamics such as wall shear stress (WSS) and velocity distribution can be employed to investigate the severity and location of stenosis in the carotid arteries. Furthermore, the potential of stenosis in other regions along the carotid arteries is affected by local variations in hemodynamics. To investigate other potential high-risk regions, a comprehensive blood flow model was utilized through a reconstructed three-dimensional patient-specific geometry with realistic boundary conditions. The developed model was numerically simulated and validated. The results indicated that hemodynamics can be successfully used to investigate the degree of stenosis severity and location. Two different locations along the carotid artery were examined. At location 1 (near the artery bifurcation) of the common carotid artery, the WSS increased from 11 Pa in the case of 42% stenosis to 27 Pa in the case of 61% stenosis and 263 Pa for 84% stenosis. Such values significantly decreased at location 2 (far from the artery bifurcation) because of the increasing distance from the artery bifurcation. In addition, the maximum value of the oscillatory shear index (OSI) downstream of the stenosis throat reached 0.5, and the outlet mass flow rate changed significantly with varying stenosis location. Carotid artery stenosis affects the artery bifurcation, which appears to be at high risk because of thrombus and arterial wall rupture, which are clearly indicated by the WSS and OSI values in this region. The current findings support the efficient use of a computational fluid dynamics approach for the diagnosis and prediction of carotid artery stenosis.

Automated summary

Carotid artery disease, characterized by narrowed arteries due to plaque buildup, can be investigated using hemodynamic parameters. A computational fluid dynamics approach based on patient-specific models can be effectively used to diagnose and predict carotid artery stenosis, indicating potential high-risk regions.