Non-invasive Mechanism Location of Atrial Arrythmias with Optical Flow from Electrocardiographic Imaging

The location of driver mechanisms in supra-ventricular tachyarrhythmias can be difficult to perform by human observers or in an automated manner, mainly when it comes to non-invasive methods. In this study, we investigated an automated methodology to locate two of the most common: Atrial Fibrillation (AF), driven by functional rotors; and atrial tachycardia (AT), driven by ectopic foci. In the proposed study, we used Farnebäck optical flow and calculated the divergence and curl of the generated vector field. First we validated the algorithm with signals from mathematical phantoms and then applied the method to AF and AT realistic in-silico models, comparing the results from the original simulated signals and the respective electrocardiographic imaging (ECGi), that is, after the originals went through forward solution followed by inverse solution. Results show that the present method is robust to noise, and outcomes are dependent of the predefined spatial resolution. In addition, the approach was able to locate both AT and AF mechanisms on the original atrial epicardial maps, and AF mechanism on the estimated atrial maps through the ECGi. However, AT mechanism location accuracy seems to be partially degraded by the ECGi.