• Matlab
  • Simulink
  • NS3
  • OMNET++
  • NS2

Noninvasive Imaging of 3D Myocardial Infarction 

We propose a new approach to noninvasively image the 3-D myocardial infarction (MI) substrates based on equivalent current density (ECD) distribution that is estimated from the body surface potential maps (BSPMs) during S-T segment. The MI substrates were identified using a predefined threshold of ECD. Computer simulations were performed to assess the performance with respect to: 1) MI locations; 2) MI sizes; 3) measurement noise; 4) numbers of BSPM electrodes; and 5) volume conductor modeling errors. A total of 114 sites of transmural infarctions, 91 sites of epicardial infarctions, and 36 sites of endocardial infarctions were simulated.

The simulation results show that: 1) Under 205 electrodes and 10-μV noise, the averaged accuracies of imagingtransmural MI are 83.4% for sensitivity, 82.2% for specificity, 65.0% for Dice’s coefficient, and 6.5 mm for distances between the centers of gravity (DCG). 2) For epicardial infarction, the averaged imagingaccuracies are 81.6% for sensitivity, 75.8% for specificity, 45.3% for Dice’s coefficient, and 7.5 mm for DCG; while for endocardial infarction, the imaging accuracies are 80.0% for sensitivity, 77.0% for specificity, 39.2% for Dice’s coefficient, and 10.4 mm for DCG. 3) A reasonably goodimaging performance was obtained under higher noise levels, fewer BSPM electrodes, and mild volume conductor modeling errors. The present results suggest that this method has the potential to aid in the clinical identification of the MI substrates.

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