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

Area of Science:

• Medical Imaging & Diagnostics
• Fluid Dynamics & Hemodynamics
• Biomedical Engineering

Background:

• High-fidelity computational fluid dynamics (CFD) reveals flow instabilities linked to clinical observations like bruits and murmurs.
• These instabilities are speculated to play a role in aneurysm growth and rupture.
• Existing hemodynamic metrics have shown associations with aneurysm rupture status.

Purpose of the Study:

• To hypothesize that harmonic flow instabilities (spectral bandedness) in CFD data correlate with aneurysm rupture status.
• To introduce a novel method for quantifying and visualizing spectral bandedness using musical audio-processing tools.
• To compare the novel metric with existing rupture-associated metrics.

Main Methods:

• Development of a spectral bandedness index (SBI) based on audio-processing techniques.
• Application of high-fidelity CFD to a dataset of 50 bifurcation aneurysm geometries.
• Calculation of SBI and existing hemodynamic metrics for each aneurysm model.
• Statistical analysis to assess the association of metrics with rupture status (AUC, p-value, sensitivity, specificity).
• 3D flow visualization to identify regions of high SBI.

Main Results:

• The novel spectral bandedness index (SBI) was the only metric significantly associated with aneurysm rupture status (AUC=0.76, p=0.002).
• SBI demonstrated 79% specificity and 65% sensitivity in predicting rupture status.
• High SBI regions correlated with near-wall inflow jets and vortex-shedding/flutter phenomena within the aneurysm sac.

Conclusions:

• Harmonic flow instabilities, quantified by SBI, are significantly associated with aneurysm rupture.
• The novel SBI metric shows promise for identifying intracranial aneurysms at lower risk of rupture.
• Flow-induced vibrational mechanisms driven by coherent flow instabilities may contribute to aneurysm wall degradation.