TY - JOUR
T1 - A theoretical model of the high-frequency arrhythmogenic depolarization signal following myocardial infarction
AU - Kapela, Adam
AU - Bezerianos, Anastasios
N1 - Funding Information:
Manuscript received July 7, 2003; revised March 21, 2004. The work of A. Kapela was supported by the State Scholarship Foundation (S.S.F.) of Athens-Greece. Asterisk indicates corresponding author.
PY - 2004/11
Y1 - 2004/11
N2 - 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.
AB - 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.
KW - Myocardial infarction
KW - QRS variability
KW - Theoretical ECG
KW - Wavelet analysis
UR - http://www.scopus.com/inward/record.url?scp=6344219737&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=6344219737&partnerID=8YFLogxK
U2 - 10.1109/TBME.2004.834277
DO - 10.1109/TBME.2004.834277
M3 - Article
C2 - 15536893
AN - SCOPUS:6344219737
SN - 0018-9294
VL - 51
SP - 1915
EP - 1922
JO - IRE transactions on medical electronics
JF - IRE transactions on medical electronics
IS - 11
ER -