Computational Fluid Dynamics Simulations of Blood Flow in a Cerebral Aneurysm

Source: Joseph C. Muskat, Vitaliy L. Rayz, and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana

The objective of this video is to describe recent advancements of computational fluid dynamic (CFD) simulations based on patient- or animal-specific vasculature. Here, subject-based vessel segmentations were created, and, using a combination of open-source and commercial tools, a high-resolution numerical solution was determined within a flow model. Numerous studies have demonstrated that the hemodynamic conditions within the vasculature affect the development and progression of atherosclerosis, aneurysms, and other peripheral artery diseases; concomitantly, direct measurements of intraluminal pressure, wall shear stress (WSS), and particle residence time (PRT) are difficult to acquire in vivo.

CFD allow such variables to be assessed non-invasively. In addition, CFD is used to simulate surgical techniques, which provides physicians better foresight regarding post-operative flow conditions. Two methods in magnetic resonance imaging (MRI), magnetic resonance angiography (MRA) with either time of flight (TOF-MRA) or contrast-enhanced MRA (CE-MRA) and phase-contrast (PC-MRI), allow us to obtain vessel geometries and time-resolved 3D velocity fields, respectively. TOF-MRA is based on the suppression of the signal from static tissue by repeated RF pulses that are applied to the imaged volume. A signal is obtained from unsaturated spins moving into the volume with the flowing blood. CE-MRA is a better technique for imaging vessels with complex recirculating flows, as it uses a contrast agent, such as gadolinium, to increase the signal.

Separately, PC-MRI utilizes bipolar gradients to generate phase shifts that are proportional to a fluid's velocity, thus providing time-resolved velocity distributions. While PC-MRI is capable of providing blood flow velocities, the accuracy of this method is affected by limited spatiotemporal resolution and velocity dynamic range. CFD provides superior resolution and can assess the range of velocities from high-speed jets to slow recirculating vortices observed in diseased blood vessels. Thus, even though the reliability of CFD depends on the modeling assumptions, it opens up the possibility for high quality, comprehensive depiction of patient-specific flow fields, which can guide diagnosis and treatment.