Influences of Blood Flow Waveform Uncertainties on Computational Hemodynamic Evaluation for Intracranial Aneurysms*

Boundary condition (BC) is one of the most critical factors in the accuracy of hemodynamic evaluations of intracranial aneurysms (IAs) using computational fluid dynamics (CFD) modeling. Most previous investigations used a uniform rather than the patient-specific physiological blood flow waveform as BCs for numerical modeling of IAs, which could induce significant errors in risk evaluations and lead to wrong diagnoses for patients with IA symptoms. To secure the prime BC for hemodynamic modeling for IAs and quantify the hemodynamic differences under various BC strategies, this study conducted a comprehensive investigation based on Doppler ultrasound measurements and the discrete Fourier transform (DFT) simulation. First, the periodically pulsatile blood velocity at the internal carotid artery (ICA) was measured by the ultrasound flowmeter for the IA patient with a heart rate of 57 Hz, which was plotted and then phase-averaged as the baseline physiological BC for CFD modeling. Subsequently, the number of discrete points, i.e., N = 8, 16, 22, 36, and 106 on the phase-averaged waveform, were employed to generate five simulated waveforms as BCs for CFD modeling by comparing agreements in hemodynamics with the phase-averaged scenario. In addition, hemodynamic performances under the patient-specific physiological BC and a previously employed uniform BC were compared to check the errors induced by the uniform waveform assumption. The preliminary results showed that more discrete points are selected for a DFT waveform, better agreements in hemodynamics (i.e., maximum wall shear stress (WSS), surface-averaged (SA-WSS), oscillatory shear index (OSI)) on the IA sac wall can be obtained. It results in the correlation coefficients of ~ 0.94, ~0.98, ~ 0.993, ~0.996, and ~0.998 under scenarios of N = 8, 16, 22, 36, and 106, respectively. It suggests that N = 22 are acceptable prime DFT points to generate a BC for hemodynamic modeling by considering the balance of modeling accuracy and DFT complexity. Additionally, significant differences in hemodynamics resulting from uniform and patient-specific BCs suggest the latter is essential to ensure the accuracy of hemodynamic predictions for IAs.