Visualizing the Substrate for Sudden Cardiac Death

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DESCRIPTION (provided by applicant): Sudden cardiac death is a significant health care problem in the United States, with estimates of annual incidence ranging from 200,000 to 400,000 deaths. Malignant ventricular tachyarrhythmias (VTNF) account for at least 50% of death in patients with a history of myocardial infarction (MI). These arrhythmias result from re-entrant circuits residing predominantly at the border zone between healthy and scarred tissue. Indeed, histopathological studies have revealed that the most arrhythmogenic scars are those containing the greatest degree of interdigitation between normal and abnormal tissue. In this study, we propose to test the hypothesis that structural characteristics of arrhythmogenic ventricular tissue can be identified by magnetic resonance imaging (MRI). Experiments will be performed using a combination of ex vivo and in vivo animal studies, as well as in vivo clinical corroboration. We hypothesize that these protocols will provide direct experimental evidence that MR imaging can precisely identify the presence and location of arrhythmogenic "hotspots" in a myocardial scar. This would have a direct impact on two important aspects of the management and prevention of malignant ventricular arrhythmias. First, catheter ablation procedures to eliminate VT could be precisely targeted by pre-procedural MR imaging and 3D reconstruction to identify and localize the arrhythmogenic "hot spots". Second, by determining whether the myocardial scar in a particular post-MI patient contains any of these arrhythmogenic zones by MR imaging, one may be able to clearly identify those patients at highest risk for sudden cardiac death requiring treatment. This project represents a unique confluence of disciplines (Cardiac Electrophysiology, MR Imaging, and Image Processing)and novel techniques (substrate-based electroanatomical mapping of VT, percutaneous catheter-based epicardial mapping, and 3D MR imaging reconstruction and registration with electrophysiological data) to address the leading cause of death in the United States.