Ventricular fibrillation (VF) is a fatal cardiac arrhythmia in which the orchestrated contraction of the ventricular myocardium becomes chaotic due to disorganized excitation, causing a failure in the efficiency of the cardiac pump. Dynamic heterogeneity arising from electrical restitution properties unravels activation-repolarization and refractoriness instability. Previous studies on non-linear dynamics during frequency restitution under induction protocols have shown that steep electrical restitution slopes promote wavelength oscillations and wave-breaks contributing to electrical instability and arrhythmogenesis. It is of great interest to validate robust methods that allows for early identification of myocardial vulnerability and susceptibility to such events.
Comprehensive analyses of the ventricular activation-repolarization dynamics may help to identify the intrinsic and dynamic vulnerability of cardiac electrical stability as well as susceptibility for developing VF. Steepness analysis of restitution slopes in dynamic restitution curves as well as automated quantification of dynamic activation-repolarization morphological changes has shown to provide valuable information on the process of ventricular arrhythmogenesis.
We’ve developed and validated an application that allows carrying out the reconstruction and automated analysis of the restoration of cardiac electrical activity using advanced signal-processing techniques during dynamic VF induction protocols. Throughout induction, ventricular complexes undergo complex progressive adaptations leading to continuous morphological changes, which are dynamically determined using wavelet transformations. Steepness slope analysis as well as arrhythmia initiation are automatically determined. Furthermore, we combine multimodal data from simultaneous global electrical and regional multisite optical recordings, which are integrated to provide additional value. A comparison between healthy controls and subjects who have undergone myocardial remodeling due to metabolic syndrome is analyzed for validation purposes.