Quantitative angiography (QAngio) may provide hemodynamic information during neurointerventional procedures through imaging biomarkers related to contrast flow. The standard clinical implementation of QAngio is limited by projection imaging: analysis of contrast motion within complex 3D geometries is restricted to 1-2 projection views, truncating the potential wealth of imaging biomarkers related to disease progression or efficacy of treatment. To understand the limitations of 2D biomarkers, we propose the use of in-silico contrast distributions to investigate the potential benefits of 3D-QAngio within the context of neurovascular hemodynamics. Ground-truth in-silico contrast distributions were generated in two patient-specific intracranial aneurysm models, accounting for the physical interactions of contrast media and blood. A short bolus of contrast was utilized to obtain full a wash-in/ wash-out cycle within the aneurysm ROI. Simulated angiograms mimicking clinical cone-beam CT (CBCT) acquisitions were then generated, and volumetric contrast distributions were reconstructed to analyze bulk contrast flow. The ground-truth 3D-CFD, reconstructed 3D-CBCT-DSA, and 2D-DSA projections were used to extract QAngio parameters related to contrast time dilution curves, such as area under the curve (AUC), peak height (PH), mean-transit-time (MTT), time-to-peak (TTP), and time to arrival (TTA). An initial comparison of quantitative flow parameters in both 2D and 3D, in a smaller and larger aneurysm, indicated that 3D-QAngio can provide a good description of bulk flow characteristics (TTA, TTP, MTT), but recovery of integral parameters (PH, AUC) aneurysms is limited. Nonetheless, incorporation of 3D-QAngio methods may provide additional insight into our understanding of abnormal vascular flow patterns.
Keywords: Aneurysm; Angiographic Parametric Imaging (API); Computational Fluid Dynamics (CFD); Quantitative Angiography.