Leveraging Patient-Specific Simulated Angiograms to Characterize Cerebral Aneurysm Hemodynamics using Computational Fluid Dynamics.

Abstract

Cerebral aneurysms (CA) affect nearly 6% of the US population and its rupture is one of the major causes of hemorrhagic stroke. Neurointerventionalists performing endovascular therapy (ET) to treat CA rely on qualitative image sequences obtained under fluoroscopy guidance alone, and do not have access to crucial quantitative information regarding blood flow before, during and after treatment - partially contributing to a failure rate of up to 30%. Computational fluid dynamics (CFD) is a powerful tool that can provide a wealth of quantitative data; however, CFD has found limited utility in the clinic due to the challenges in obtaining hemodynamic boundary conditions for each patient. In this work, we present a novel CFD-based simulated angiogram approach (SAA) that resolves the blood flow physics and interaction between blood and injected contrast agent to extract quantitative hemodynamic parameters which can be used to design real-time parametric imaging analysis. The SAA enables correlating contrast agent transport to the underlying hemodynamic conditions via time-density curves (TDC) obtained at several points in the region of interest. The ability of the TDC and the SAA to provide critical hemodynamic parameters in and around CA anatomies, such as washout and local flow changes is explored and presented. This provides invaluable quantitative data to the clinician at the time of intervention, since it incorporates the physics of blood flow and correlates the contrast transport to hemodynamic parameters quantitatively - thereby enabling the clinician to take informed decisions that improve treatment outcomes.