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

Ben Orkild1, Jake Bergquist1, Eric Paccione1, Matthias Lange2, Eugene Kwan1, Bram Hunt1, Rob MacLeod1, Akil Narayan1, Ravi Ranjan1
1University of Utah, 2Universtiy of Utah


Abstract

Atypical Atrial Flutter (AAF) is the most common cardiac arrhythmia to develop following catheter ablation for atrial fibrillation. Patient-specific computational simulations of propagation have shown promise in prospectively predicting AAF reentrant circuits and providing useful insight to guide successful ablation procedures. These patient-specific models require a large number of inputs, each with an unknown amount of uncertainty. Uncertainty quantification (UQ) is a technique to assess how variability in a set of input parameters can affect the output of a model. However, modern UQ techniques, such as polynomial chaos expansion, require a well-defined output to map to the inputs. In this study, we aimed to identify simulation output metrics that could be used to create an interpretable and comprehensive understanding of model behavior in subsequent UQ analyses based on realistic ranges of fibrosis values. We found that the majority of changes to the duration of reentry occurred within an IIR range of $1.01$ to $1.39$, and that there was a large amount of variability in the resulting arrhythmia. This study serves as a starting point for future UQ studies to investigate the nonlinear relationship between fibrosis threshold and the resulting arrhythmia in AAF models.