Spatial Changes in the Atrial Fibrillation Wave-Dynamics After Using Antiarrhythmic Drugs: A Computational Modeling...

Area of Science:

• Computational electrophysiology
• Cardiac electrophysiology
• Pharmacology

Background:

• Previous work demonstrated the feasibility of computational modeling-guided antiarrhythmic drug (AAD) testing in atrial fibrillation (AF) patients.
• This study further explores the anti-AF mechanisms of AADs and their impact on AF wave dynamics using realistic computational models.

Purpose of the Study:

• To characterize the effects of five AADs on atrial fibrillation (AF) wave dynamics using realistic computational models.
• To investigate the spatial changes in AF wave dynamics, including dominant frequency (DF) and its coefficient of variation (DF-COV), in response to AADs.

Main Methods:

• Utilized realistic computational modeling of 25 AF patients, incorporating individual anatomy, histology, and electrophysiology of the left atrium (LA).
• Assessed the effects of five AADs (amiodarone, sotalol, dronedarone, flecainide, propafenone) on LA segments.
• Measured mean dominant frequency (DF) and its coefficient of variation (DF-COV) across 10 LA segments to evaluate spatial AF wave dynamics.

Main Results:

• AAD administration resulted in a dose-dependent decrease in mean DF (p < 0.001).
• Under AADs, DF was significantly lower in pulmonary vein (PV) regions compared to extra-PV regions (p < 0.001), with a higher DF-COV (p = 0.003).
• Mean DF was lower under high Smax (≥1.4) conditions (p < 0.001) and during AF defragmentation episodes, which also showed higher DF-COV (p < 0.001).

Conclusions:

• AAD-induced DF reduction is most prominent in PVs and during high Smax conditions.
• These DF changes contribute to AF termination or defragmentation by creating lower DF and spatially unstable conditions (higher DF-COV).