Analysis of Velocity and Pressure Gradients to Predict Stroke Using Carotid Artery Simulations

The purpose of this poster is to demonstrate the combination of computational fluid dynamics (CFD) and medicine to better characterize the early signs of stroke and aid in medical decisions. Stroke is one of the leading causes of death in the world. In the US alone, strokes account for one in twenty deaths, out of which 87% are identified as ischemic strokes. Reliable prediction of stroke is inherently challenging but is important to prevent long-term adverse effects in patients who require surgery and to avoid unnecessary surgeries in other patients. This project aims to correctly predict which patients will benefit from surgery by using CFD to analyze flow patterns in patients’ carotid arteries, with the ultimate goal of creating a predictive tool that helps physicians make informed decisions regarding stroke patients. CFD is a computational technique that uses finite element analysis (FEA) to discretize a fluid domain and determine the flow characteristics and pressure gradients. The combination of CFD and a patient’s specific carotid artery geometry can provide greater insight into the flow patterns of stroke and non-stroke patients. Therefore, the goal of the project is to create a patient specific CFD model to predict stroke. Computerized tomography angiography (CTA) scans from a patient’s left and right carotid artery are used to generate a 3D geometry to import into a commercial CFD simulation software. In collaboration with the University of Rochester, Department of Neurosurgery, the analysis of 48 different pairs of carotid arteries (26 stroke and 22 non-stroke) has been completed. A laminar viscous flow model was utilized to model blood flow in the patient’s carotid and each patient’s specific peak systolic velocities (PSV) were used as boundary conditions. Results showed that stroke patients have irregular velocity gradients and high velocity values in the ICA’s sinus. Recent work has shown that stroke patients have small regions of high-pressure gradients around the walls of the carotid which could be an indicator of potential stroke.