Using Contrast Motion to Generate Patient-Specific Blood Flow Simulations During Invasive Coronary Angiography

Abstract

Virtual fractional flow reserve (vFFR) is an emerging technology employing patient-specific computational fluid dynamics (CFD) simulations to infer the hemodynamic significance of a coronary stenosis. Patient-specific boundary conditions are an important aspect of this approach and while most efforts make use of lumped parameter models to capture key phenomena, they lack the ability to specify the associated parameters on a patient-specific basis. When applying vFFR in a catheter laboratory setting using X-ray angiograms as the basis for creating the simulations, there is some indirect functional information available through the observation of the radio-opaque contrast agent motion. In this work, we present a novel method for tuning the lumped parameter arterial resistances (commonly incorporated in such simulations), based on simulating the physics of the contrast motion and comparing the observed and simulated arrival times of the contrast front at key points within a coronary tree. We present proof of principle results on a synthetically generated coronary tree comprised of multiple segments, demonstrating that the method can successfully optimize the arterial resistances to reconstruct the underlying velocity and pressure fields, providing a potential new means to improve the patient specificity of simulation-based technologies in this area.