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Electrophysiological Assessment of Murine Atria with High-Resolution Optical Mapping
Published on: February 22, 2018
Probing Atrial Substrate With the Triple Extrastimulus Protocol: Impact of Variability on Electrophysiological
IEEE Transactions on Bio-Medical Engineering
|June 17, 2026
Summary
Personalized computational models of the left atrium can capture global conduction patterns but struggle to replicate complex beat-to-beat changes seen in persistent atrial fibrillation, indicating a need for improved modeling strategies.
Area of Science:
- Computational electrophysiology
- Cardiac modeling
- Atrial fibrillation research
Background:
- Pulmonary vein isolation alone is insufficient for persistent atrial fibrillation.
- Non-pulmonary vein substrates and hidden slow-regions are critical for reentry.
- Premature stimulation can unmask arrhythmogenic substrates.
Purpose of the Study:
- To assess if personalized in silico left atrial models can reproduce clinical conduction changes during premature stimulation.
- To evaluate the impact of fibrosis and conductivity variations on model accuracy.
- To determine the reliability of computational models in identifying arrhythmogenic substrates.
Main Methods:
- Constructed 10 personalized left atrial models from CT and CARTO data.
- Incorporated fibrosis distributions from bipolar voltage mapping.
- Systematically varied fibrosis density and conductivity to create model variants.
- Compared simulated and clinical activation patterns (LAT, Vmax, fractionation) during triple-extrastimulus (TE) protocol.
Main Results:
- Simulations moderately agreed with clinical local activation times (LAT), with low-to-mild fibrosis improving correlation (up to 0.75).
- Global activation patterns showed limited sensitivity to fibrosis density variations.
- Bipolar amplitude (Vmax) and fractionation agreement were poor (correlation coefficients < 0.4 and 0.25, respectively).
- Models did not consistently reproduce TE-induced conduction changes, suggesting limitations in restitution modeling.
Conclusions:
- Personalized left atrial models capture global conduction but are weakly constrained by clinical data.
- Improved restitution modeling is needed to accurately simulate beat-dependent dynamics.
- Future personalization strategies should integrate functional markers (e.g., restitution) with structural information to better identify arrhythmogenic substrates.
