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.
Results are consistent with previous work, but our methods yield more detailed insights into the complex flow dynamics. However, routine applications of CFD to anatomically realistic cases still depend upon further development of dedicated algorithms, most crucially to handle geometry definition and mesh generation for complicated stent deployments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.