Fully resolved simulation and ultrasound flow studies in stented carotid aneurysm model

Abstract

Introduction. Treatment choice for extracranial carotid artery widening, also called aneurysm, is difficult. Blood flow simulation and experimental visualization can be supportive in clinical decision making and patient-specific treatment prediction. This study aims to simulate and validate the effect of flow-diverting stent placement on blood flow characteristics using numerical and in vitro simulation techniques in simplified carotid artery and aneurysm models. Methods. We have developed a workflow from geometry design to flow simulations and in vitro measurements in a carotid aneurysm model. To show feasibility of the numerical simulation part of the workflow that uses an immersed boundary method, we study a model geometry of an extracranial carotid artery aneurysm and put a flow-diverting stent in the aneurysm. We use ultrasound particle image velocimetry (PIV) to visualize experimentally the flow inside the aneurysm model. Results. Feasibility of ultrasound visualization of the flow, virtual flow-diverting stent placement and numerical flow simulation are presented. Flow is resolved to scales much smaller than the cross section of individual wires of the flow-diverting stent. Numerical analysis in stented model introduced 25% reduction of the blood flow inside the aneurysm sac. Quantitative comparison of experimental and numerical results showed agreement in 1D velocity profiles. Discussion/conclusion. We find good numerical convergence of the simulations at appropriate spatial resolutions using the immersed boundary method. This allows us to quantify the changes in the flow in model geometries after deploying a flow-diverting stent. We visualized the physiological blood flow in a 1-to-1 aneurysm model, using PIV, showing a good correspondence to the numerical simulations. The novel workflow enables numerical as well as experimental flow simulations in patient-specific cases before and after flow-diverting stent placement. This may contribute to endovascular treatment prediction.