CBC Talk on Development of a Virtual Electrophysiology Lab that Can Predict Arrhythmia Susceptibility and Identify Optimal Ablation Site - June 17, 2015

On Wednesday June 17 at 12:00 Dr. Hermenegild Arevalo (Johns Hopkins University) will give a talk on the Development of a Virtual Electrophysiology Lab that Can Predict Arrhythmia Susceptibility and Identify Optimal Ablation Site. The talk will be presented in Bakrommet at Simula.

Total number of participants: 19
Total number of guests outside of CBC: 11
Number of different nationalities represented: 6
Total number of speakers: 1
Total number of talks: 1

Abstract

Patients with myocardial infarction experience frequent ventricular arrhythmias and are at a higher risk for sudden cardiac death. For these patients, therapeutic interventions such as insertion of implantable cardioverter defibrillators or catheter ablation rely on invasive measurements obtained in the electrophysiology (EP) lab. In the EP lab, programmed stimulation via catheters are used to determine inducibility of arrhythmias which has been shown to be a predictor of sudden cardiac death. During catheter ablation, point-by-point mapping performed in the EP lab is used to locate the arrhythmogenic substrate and ablation target. The invasive nature of the EP test coupled with the long duration of the procedure exposes the patients to increased risk of complications. The goal of this project is to develop MRI-based, personalized models of patient hearts that can be used in a Virtual EP lab that allows for a non-invasive, safe, and effective way to investigate the arrhythmic propensity of individual patient hearts. This talk will summarize the pipeline developed by our group to develop personalized, image-based computational models of ventricles. I will then illustrate the effectiveness of the Virtual EP lab in predicting sudden cardiac death risk and ablation guidance via retrospective animal and patient studies. 

17/ Jun 2015 12.0013.00

 

 

Center for Biomedical Computing (CBC) aims to develop and apply novel simulation technologies to reach new understanding of complex physical processes affecting human health. We target selected medical problems where insight from mathematical modeling can contribute to changing clinical practice.