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Directed Graph Mapping exceeds Phase Mapping for the detection of simulated 2D meandering rotors in fibrotic tissue
Sebastiaan Lootens1, Iris Janssens1, Robin Van Den Abeele1
1Department of Physics and Astronomy, Ghent University, Ghent, Belgium.
Insights
Directed Graph Mapping (DGM) offers superior accuracy over Phase Mapping (PM) for detecting cardiac rotors, especially in complex conditions like high meandering, fibrosis, and noise. DGM provides a more robust solution for guiding arrhythmia ablation strategies.
Area of Science:
- Cardiology
- Computational Biology
- Biomedical Engineering
Background:
- Cardiac arrhythmias, including atrial fibrillation (AF), are often linked to re-entrant wave phenomena known as rotors.
- Accurate detection of rotor centers is critical for effective ablation strategies in treating cardiac arrhythmias.
- Traditional Phase Mapping (PM) methods for rotor detection are susceptible to errors, particularly in fibrotic cardiac tissue and noisy signal environments.
Purpose of the Study:
- To compare the performance of advanced Phase Mapping (PM) techniques against a novel Directed Graph Mapping (DGM) method for detecting cardiac rotors.
- To evaluate the robustness of both PM and DGM in simulated scenarios with varying degrees of tissue meandering, fibrosis, and temporal noise.
- To determine which mapping technique provides more reliable rotor center identification for guiding arrhythmia ablation.
Main Methods:
- Simulated 64 instances of 2D meandering rotors under diverse conditions of fibrosis and temporal noise.
- Employed four comparative strategies: visual analysis, F2-score and distance distribution comparison, and mid-p McNemar statistical testing.
- Assessed the precision and recall of rotor detection by both PM and DGM techniques across all simulations.
Main Results:
- Both PM and DGM performed comparably well in simulations with low meandering, fibrosis, and noise.
- In scenarios with high meandering, fibrosis, and noise, PM exhibited significant errors, primarily false positives, leading to low precision.
- DGM demonstrated superior robustness, maintaining high F2-scores (≥0.931) compared to the best PM performance (≥0.635) across all simulations.
Conclusions:
- Directed Graph Mapping (DGM) is a more reliable and robust technique for detecting cardiac rotors than advanced Phase Mapping (PM) methods.
- DGM's improved performance is particularly evident in complex cardiac conditions characterized by high meandering, fibrosis, and noise.
- DGM shows significant potential to enhance the accuracy and effectiveness of ablation strategies for treating cardiac arrhythmias like AF.
Abstract:
Cardiac arrhythmias such as atrial fibrillation (AF) are recognised to be associated with re-entry or rotors. A rotor is a wave of excitation in the cardiac tissue that wraps around its refractory tail, causing faster-than-normal periodic excitation. The detection of rotor centres is of crucial importance in guiding ablation strategies for the treatment of arrhythmia. The most popular technique for detecting rotor centres is Phase Mapping (PM), which detects phase singularities derived from the phase of a signal. This method has been proven to be prone to errors, especially in regimes of fibrotic tissue and temporal noise. Recently, a novel technique called Directed Graph Mapping (DGM) was developed to detect rotational activity such as rotors by creating a network of excitation. This research aims to compare the performance of advanced PM techniques versus DGM for the detection of rotors using 64 simulated 2D meandering rotors in the presence of various levels of fibrotic tissue and temporal noise. Four strategies were employed to compare the performances of PM and DGM. These included a visual analysis, a comparison of F2-scores and distance distributions, and calculating p-values using the mid-p McNemar test. Results indicate that in the case of low meandering, fibrosis and noise, PM and DGM yield excellent results and are comparable. However, in the case of high meandering, fibrosis and noise, PM is undeniably prone to errors, mainly in the form of an excess of false positives, resulting in low precision. In contrast, DGM is more robust against these factors as F2-scores remain high, yielding F2≥0.931 as opposed to the best PM F2≥0.635 across all 64 simulations.
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