Optimization of Computer Assisted Arrhythmia Intervention

The normal rhythmic beating of the heart is controlled by a set of electrical signals. When these signals are scrambled and the heart is no longer beating regularly, it produces a medical condition known as cardiac arrhythmia. There are several types of cardiac arrhythmias, the most common one being atrial fibrillation (AF) that affects more than 350,000 Canadians, which has far reaching impacts on the healthcare system and broader economy in the order of $3.6 billion/year. Currently clinical management of AF patients involves the use of catheter ablation, which is a procedure that applies energy to destroy heart tissue. In cases where patients have permanent AF, catheter ablation is not sufficient to correct the problem owing to the existence of other, unidentified sources. In this proposal, we are applying to develop a computational simulation technique so that we might better understand AF and develop patient specific strategies for treatment. We have assembled an interdisciplinary team of researchers to achieve this research objective, and have collaborated with Abbott Canada, the manufacturer of such ablation systems, to extend the value of our research findings, and to offer specific and unique training opportunities to our highly qualified personnel.

Faculty Supervisor:

Damian Redfearn

Student:

Benjamin Cecchetto

Partner:

Abbott Canada

Discipline:

Medicine

Sector:

Manufacturing

University:

Queen's University