AI Article Synopsis
- A study explored how adjusting conduction velocity (ϴ) in computational models of persistent atrial fibrillation (AF) can enhance the accuracy of simulations compared to actual patient outcomes post-ablation.
- Researchers analyzed data from 37 patients who underwent ablation, finding that adjusting ϴ improved the model's agreement with clinical results, increasing accuracy from 46% to 65%.
- The results suggest that personalized adjustments of ϴ, especially in patients with significant left atrial fibrosis and higher BMI, could make simulations more relevant for predicting arrhythmia recurrence after treatment.
Article Abstract
Background: Computational models of fibrosis-mediated, re-entrant left atrial (LA) arrhythmia can identify possible substrate for persistent atrial fibrillation (AF) ablation. Contemporary models use a 1-size-fits-all approach to represent electrophysiological properties, limiting agreement between simulations and patient outcomes.
Objectives: The goal of this study was to test the hypothesis that conduction velocity (ϴ) modulation in persistent AF models can improve simulation agreement with clinical arrhythmias.
Methods: Patients with persistent AF (n = 37) underwent ablation and were followed up for ≥2 years to determine post-ablation outcomes: AF, atrial flutter (AFL), or no recurrence. Patient-specific LA models (n = 74) were constructed using pre-ablation and ≥90 days' post-ablation magnetic resonance imaging data. Simulated pacing gauged in silico arrhythmia inducibility due to AF-like rotors or AFL-like macro re-entrant tachycardias. A physiologically plausible range of ϴ values (±10 or 20% vs. baseline) was tested, and model/clinical agreement was assessed.
Results: Fifteen (41%) patients had a recurrence with AF and 6 (16%) with AFL. Arrhythmia was induced in 1,078 of 5,550 simulations. Using baseline ϴ, model/clinical agreement was 46% (34 of 74 models), improving to 65% (48 of 74) when any possible ϴ value was used (McNemar's test, P = 0.014). ϴ modulation improved model/clinical agreement in both pre-ablation and post-ablation models. Pre-ablation model/clinical agreement was significantly greater for patients with extensive LA fibrosis (>17.2%) and an elevated body mass index (>32.0 kg/m).
Conclusions: Simulations in persistent AF models show a 41% relative improvement in model/clinical agreement when ϴ is modulated. Patient-specific calibration of ϴ values could improve model/clinical agreement and model usefulness, especially in patients with higher body mass index or LA fibrosis burden. This could ultimately facilitate better personalized modeling, with immediate clinical implications.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10909381 | PMC |
| http://dx.doi.org/10.1016/j.jacep.2023.06.015 | DOI Listing |
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Article Synopsis
- A study explored how adjusting conduction velocity (ϴ) in computational models of persistent atrial fibrillation (AF) can enhance the accuracy of simulations compared to actual patient outcomes post-ablation.
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