Detect Hemodynamic Instabilities in Brain Aneurysms using Dynamic Mode Decomposition

Investigating aneurysmal hemodynamics using in vivo imaging is challenging due to limited spatial and temporal resolutions. This study explores modal analysis at various resolutions to analyze blood flows in brain aneurysms. We employ two Dynamic Mode Decomposition (DMD) variants: Hankel-DMD and Optimized-DMD, to extract time-dependent blood flow dynamics during one cardiac cycle. High-resolution hemodynamic data from patient-specific aneurysms are obtained using Computational Fluid Dynamics. DMD analysis is then applied to calculate dynamics modes, spatial amplitudes, and temporal magnitudes. We examine DMD analyses across various resolutions to validate its applicability for low-resolution data, mimicking clinical scenarios. Results demonstrate DMD's ability to characterize inflow jet dynamics by separating large-scale structures and flow instabilities, even at low resolutions. The method's robustness in quantifying flow dynamics via energy spectrum is shown across different resolutions in all studied aneurysms. This work indicates DMD's potential as a promising tool for analyzing brain aneurysm blood flow patterns in vivo.