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Virtual Electrophysiologic Study in a Three-dimensional Cardiac MRI Model of Porcine Myocardial Infarction

Authors :
Ng, Jason
Jacobson, Jason T
Ng, Justin K
Gordon, David
Lee, Daniel C
Carr, James C.
Goldberger, Jeffrey J
Publication Year :
2012

Abstract

This study sought to test the hypothesis that "virtual" electrophysiological studies (EPS) on an anatomic platform generated by 3-dimensional magnetic resonance imaging reconstruction of the left ventricle can reproduce the reentrant circuits of induced ventricular tachycardia (VT) in a porcine model of myocardial infarction.Delayed-enhancement magnetic resonance imaging has been used to characterize myocardial infarction and "gray zones," which are thought to reflect heterogeneous regions of viable and nonviable myocytes.Myocardial infarction by coronary artery occlusion was induced in 8 pigs. After a recovery period, 3-dimensional cardiac magnetic resonance images were obtained from each pig in vivo. Normal areas, gray zones, and infarct cores were classified based on voxel intensity. In the computer model, gray zones were assigned slower conduction and longer action potential durations than those for normal myocardium. Virtual EPS was performed and compared with results of actual in vivo programmed stimulation and noncontact mapping.The left ventricular volumes ranged from 97.8 to 166.2 cm(3), with 4.9% to 17.5% of voxels classified as infarct zones. Six of the 7 pigs in which VT developed during actual EPS were also inducible with virtual EPS. Four of the 6 pigs that had simulated VT had reentrant circuits that approximated the circuits seen with noncontact mapping, whereas the remaining 2 had similar circuits but propagating in opposite directions.This initial study demonstrates the feasibility of applying a mathematical model to magnetic resonance imaging reconstructions of the left ventricle to predict VT circuits. Virtual EPS may be helpful to plan catheter ablation strategies or to identify patients who are at risk of future episodes of VT.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.pmid..........178610459f3caf013e40f2f588f1711d