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Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement between PIV and CFD suggests that CFD can reliably predict the details of the intra-aneurysmal flow dynamics observed in anatomically realistic in vitro models. Nevertheless, given the various modeling assumptions, this does not prove that they are mimicking the actual in vivo hemodynamics, and so validations against in vivo data are encouraged whenever possible.

It has recently become possible to simulate aneurysmal blood flow dynamics in a patient-specific manner via the coupling of three-dimensional (3-D) X-ray angiography and cmputational fluid dynamics (CFD). Before such image-based CFD models can be used in a predictive capacity, however, it must be shown that they indeed reproduce the in vivo hemodynamic environment. Motivated by the fact that there are currently no techniques for adequately measuring complex blood velocity fields in vivo, in this paper we describe how cine X-ray angiograms may be simulated for the purpose of indirectly validating patient-sperific CFD models. Mimicking the radiological procedure, a virtual angiogram is constructed by first simulating the time-varying injection of contrast agent into a precomputed, patient-specific CFD model. A time-series of images is then constructed by simulating the attenuation of X-rays through the computed 3-D contrast-agent flow dynamics. Virtual angiographic images and residence time maps, here derived from an image-based CFD model of a giant aneurysm, are shown to be in excellent agreement wiith the corresponding clinical images and residence time maps, but only when the interaction between the quasisteady contrast agent injection and the pulsatile flow are properly accounted for. These virtual angiographic techniques pave the way for validating image-based CFD models against routinely available clinical data, and provide a means of visualizing complex, 3-D blood flow dynamics in a clinically relevant manner. They also clearly show how the contrast agent injection perturbs the noraml blood flow patterns, further highlighting the potential utility of image-based CFD as a window into the true aneurysmal hemodynamics.