Correlation Between Angiographic and Particle Image Velocimetry Quantifications of Flow Diverters in an In Vitro Model of Elastase-Induced Rabbit Aneurysms

Author:

Trager Asher L.1,Sadasivan Chander1,Seong Jaehoon2,Lieber Baruch B.3

Affiliation:

1. Department of Biomedical Engineering, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146

2. Department of Engineering and Physics, University of Central Oklahoma, 100 North University Drive, Edmond, OK 73034

3. Department of Biomedical Engineering and Department of Radiology, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146

Abstract

The rupture of a cerebral aneurysm can result in a hemorrhagic stroke. A flow diverter, which is a porous tubular mesh, can be placed across the neck of a cerebral aneurysm to induce the cessation of flow and initiate the formation of an intra-aneurysmal thrombus. By finding a correlation between particle image velocimetry (PIV) and digital subtraction angiography, a better assessment of how well an aneurysm is excluded from the parent artery can be made in the clinical setting. A model of a rabbit elastase-induced aneurysm was connected to a mock circulation loop. The model was then placed under angiography. Recorded angiograms were analyzed so that a contrast concentration-time curve based on the average grayscale intensity inside the aneurysm could be determined. That curve was then fitted to a mathematical model that quantifies the influence of convection and diffusion on contrast transport. Optimized parameters were correlated with the intraneurysmal mean kinetic energy measured by PIV in the same aneurysm model. A strong correlation was observed between the convection and diffusion time constants and the mean kinetic energy inside the aneurysm. Analyzing the flow of angiographic contrast into and out of the aneurysm after implantation of a flow diverter allows for prediction of the efficacy of the device in excluding the aneurysm. Correlating hydrodynamic measures obtained by angiography to those obtained by detailed techniques such as PIV increases confidence in such predictions.

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

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