Characterization of fibrillatory rhythms by ensemble vector directional analysis

Area of Science:

• Cardiology
• Biomedical Engineering
• Computational Biology

Background:

• Fibrillatory rhythms, though appearing random, exhibit definable patterns.
• Standard mapping techniques face limitations in identifying fibrillation organization.
• Characterizing spatiotemporal organization is crucial for understanding fibrillatory rhythms.

Purpose of the Study:

• Develop and apply a novel method, "ensemble vector mapping," for characterizing fibrillation's spatiotemporal organization.
• Objectively assess the consistency of myocardial activation during fibrillatory rhythms.
• Distinguish between different types of fibrillatory rhythms.

Main Methods:

• Induced ventricular fibrillation (VF) and atrial fibrillation (AF) in canine models.
• Recorded epicardial electrograms using a 112-electrode plaque array.
• Created "ensemble vector" index by summing orthogonal bipolar electrograms, transforming magnitude, integrating, and normalizing for activation consistency.

Main Results:

• Ensemble vector index was significantly lower during VF (39 ± 23 mV/s) than ventricular pacing (137 ± 36 mV/s).
• Index was lower during AF (60 ± 54 mV/s) than atrial pacing (115 ± 27 mV/s).
• Activation consistency was higher in AF than VF and the index distinguished atrial tachycardia from AF.

Conclusions:

• Ensemble vector mapping provides an objective assessment of myocardial activation consistency during fibrillation.
• Activation consistency differs between atrial and ventricular fibrillation models.
• This technique can rapidly characterize repetitive activation patterns and differentiate fibrillatory rhythms.