Spectral Bandedness in High-Fidelity Computational Fluid Dynamics Predicts Rupture Status in Intracranial Aneurysms

Abstract

Recent studies using high-fidelity computational fluid dynamics (CFD) have revealed high-frequency flow instabilities consistent with clinical reports of bruits and “musical murmurs”, which have been speculated to contribute to aneurysm growth and rupture. We hypothesized that harmonic flow instabilities (“spectral bandedness”) in aneurysm CFD data may be associated with rupture status. Before testing this hypothesis, we first present a novel method for quantifying and visualizing spectral bandedness in cardiovascular CFD datasets based on musical audio-processing tools. Motivated by previous studies of aneurysm hemodynamics, we also computed a selection of existing metrics that have demonstrated association with rupture in large studies. In a dataset of 50 bifurcation aneurysm geometries modeled using high-fidelity CFD, our spectral bandedness index (SBI) was the only metric significantly associated with rupture status (AUC = 0.76, p = 0.002), with a specificity of 79% (correctly predicting 19/24 unruptured cases) and sensitivity of 65% (correctly predicting 17/26 ruptured cases). Three-dimensional flow visualizations revealed coherent regions of high SBI to be associated with strong near-wall inflow jets and vortex-shedding/flutter phenomena in the aneurysm sac. We speculate that these intracycle, coherent flow instabilities may preferentially contribute to the progressive degradation of the aneurysm wall through flow-induced vibrational mechanisms, and that their absence in high-fidelity CFD may be useful for identifying intracranial aneurysms at lower risk of rupture.