A theoretical model of the high-frequency arrhythmogenic depolarization signal following myocardial infarction

IEEE Trans Biomed Eng. 2004 Nov;51(11):1915-22. doi: 10.1109/TBME.2004.834277.

Abstract

Theoretical body-surface potentials were computed from single, branching and tortuous strands of Luo-Rudy dynamic model cells, representing different areas of an infarct scar. When action potential (AP) propagation either in longitudinal or transverse direction was slow (3-12 cm/s), the depolarization signals contained high-frequency (100-300 Hz) oscillations. The frequencies were related to macroscopic propagation velocity and strand architecture by simple formulas. Next, we extended a mathematical model of the QRS-complex presented in our earlier work to simulate unstable activation wavefront. It combines signals from different strands with small timing fluctuations relative to a large repetitive QRS-like waveform and can account for dynamic changes of real arrhythmogenic micropotentials. Variance spectrum of wavelet coefficients calculated from the composite QRS-complex contained the high frequencies of the individual abnormal signals. We conclude that slow AP propagation through fibrotic regions after myocardial infarction is a source of high-frequency arrhythmogenic components that increase beat-to-beat variability of the QRS, and wavelet variance parameters can be used for ventricular tachycardia risk assessment.

Publication types

  • Clinical Trial
  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Arrhythmias, Cardiac / diagnosis*
  • Arrhythmias, Cardiac / etiology
  • Arrhythmias, Cardiac / physiopathology*
  • Body Surface Potential Mapping / methods*
  • Diagnosis, Computer-Assisted / methods*
  • Heart Conduction System / physiopathology
  • Humans
  • Models, Cardiovascular*
  • Models, Neurological
  • Myocardial Infarction / complications
  • Myocardial Infarction / diagnosis*
  • Myocardial Infarction / physiopathology*
  • Reproducibility of Results
  • Sensitivity and Specificity