UC San Diego

Cardiac resynchronization therapy (CRT) is an effective intervention for patients with heart failure but has a 30% non-responder rate due to a lack of predictive, mechanism- based objective criteria for patient selection. In order to fully optimize treatment outcomes, computational models can be used to predict molecular, biomechanical, and electrophysiological mechanisms of cardiac function. The methods presented in this thesis provide an efficient technique to estimate epicardial activation time parameters and thus will prove useful as the electrophysiological input for predictive patient-specific computational model development. By developing three- dimensional isochronal maps, the sequence of ventricular activation in normal hearts, hearts with heart failure, hearts with myocardial infarcts, and hearts with ventricular dyssynchrony, such as left bundle branch block (LBBB), can be visualized. Through the use of a 128- electrode sock array, it is confirmed that the local activation time is most efficiently calculated using the time of the maximum negative derivative averaged over multiple beats. Automatic determination of the activation times proved to be comparable to manual determination (the standard). It is also seen that filtering signals causes data loss and should be avoided if possible. The calculated activation times are then input into an anatomical fit geometry of the heart to create an epicardial isochronal activation map in Continuity. Inspection of these maps reveals that endocardial pacing does not always restore more ventricular synchrony when compared to epicardial pacing, specifically in the presence of tachycardia-induced heart failure and a myocardial infarct