Initial evaluation of 2D and 3D simulated high-speed 1000 fps vascular contrast-flow image sequences using computational fluid dynamics (CFD)

Digital subtraction angiography (DSA) remains the clinical standard for detailed visualization of the neurovasculature due to its high-spatial resolution; however, detailed blood-flow quantification is impaired by its low-temporal resolution. Advances in photon-counting detector technology have led us to develop High-Speed Angiography (HSA), where x-ray images are acquired at 1000 fps for more accurate visualization and quantification of blood flow. We have implemented a physics-based optical flow method to extract such information from HSA, but validation of the angiography-derived velocity distributions is not straightforward. Computational fluid dynamics (CFD) is widely regarded as the benchmark for hemodynamic analysis, as it provides a multitude of quantitative flow parameters throughout the volume of interest. However, there are several limitations with this method related to over-simplification of boundary conditions and suboptimal meshing (spatial resolution), that make CFD simulation results an inexact criterion for validation. To overcome this issue for HSA validation, CFD was used to generate both simulated high-speed angiograms and the corresponding ground-truth 3D flow fields to better understand the relationship between the 3D volumetric-flow distribution and the 2D projected-flow distribution as is obtained with angiography, and the subsequent 2D approximation of flow velocity. Several geometries were investigated, ranging from simple pipe models to complex patient-specific aneurysms. Simulated datasets were analyzed with the optical flow algorithm, and the effects of flow divergence, quantum mottle, and intensity gradient on the calculation were evaluated. From these simulations, we can evaluate whether flow fields reconstructed from HSA are representative of significant flow patterns in the 3D vasculature.