Une approche de modélisation pour guider la caractérisation du substrat de la fibrillation auriculaire

 

Vincent Jacquemet

Centre de recherche de l'Hôpital du Sacré-Coeur de Montréal

 

Domaine : santé circulatoire et respiratoire

Programme Chercheurs-boursiers - Junior 2

Concours 2016-2017

Atrial fibrillation (AF) is the most common arrhythmia and a major cause of stroke. Pulmonary vein isolation by catheter ablation is a therapy of choice for drug-resistant paroxysmal AF. Nevertheless, AF recurrences are frequent and sometimes asymptomatic, requiring new interventions by catheter. Novel techniques are needed for early detection of the changes in the arrhythmogenic substrate in order to avoid an aggravation caused by the remodeling induced by successive self-terminating AF episodes.

In this research program, we are looking for electrophysiological markers based on electrocardiograms (ECG) to predict AF recurrence. Our work is based on the assumption that these recurrences are due to electrical reconnection of the pulmonary veins after ablation and that these reconnections cause detectable changes in the morphology of the bioelectric signals on the ECG.

For this purpose, we will create computer models of patients' atria to reproduce normal ECG, simulate catheter ablations and reconnections of the pulmonary veins, and identify at each step the changes in the resulting ECG characteristics. In parallel, a group of patients will be followed up for a year after catheter ablation using an implanted heart monitor to detect AF recurrence and measure changes in the ECG. Signal processing tools will be developed to analyze ECG morphology in light of the results of the simulations and investigate their correlation with the occurrence of arrhythmias detected by the implanted heart monitor.