A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations

Area of Science:

• Computational modeling
• Cardiac electrophysiology
• Medical imaging analysis

Background:

• Atypical atrial flutter (AAF) frequently occurs after atrial fibrillation ablation.
• Patient-specific computational models can predict AAF circuits but face input uncertainty.
• Uncertainty quantification (UQ) assesses input variability's impact on model outputs.

Purpose of the Study:

• To investigate the sensitivity of simulated AAF reentry to fibrosis threshold selection.
• To explore the impact of fibrosis threshold variability on AAF models.
• To establish a foundation for future UQ studies in AAF modeling.

Main Methods:

• Utilized patient-specific computational simulations for AAF reentry.
• Employed the image intensity ratio (IIR) method to set fibrosis thresholds from LGE-MRI.
• Analyzed the effect of varying fibrosis thresholds on simulated arrhythmia duration.

Main Results:

• The majority of changes in reentry duration occurred within an IIR range of 1.01 to 1.39.
• Significant variability in the resulting arrhythmia was observed.
• Identified a sensitive range for fibrosis threshold in AAF models.

Conclusions:

• Fibrosis threshold selection critically influences simulated AAF reentry.
• This study highlights the need for UQ in patient-specific AAF models.
• Provides a basis for understanding the nonlinear relationship between fibrosis and arrhythmia.