• Sebastiaan Lootens
  • Iris Janssens
  • Robin Van den Abeele
  • Eike Wülfers
  • Arthur Santos Bezerra
  • Bjorn Verstraeten
  • Sander Hendrickx
  • Arstanbek Okenov
  • Timur Nezlobinsky
  • Alexander Panfilov
  • Nele Vandersickel
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 -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 -scores remain high, yielding as opposed to the best PM across all 64 simulations.
Original languageEnglish
Article number108138
JournalComputers in Biology and Medicine
Volume171
DOIs
Publication statusPublished - 1 Mar 2024

    ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

    WoS ResearchAreas Categories

  • Biology
  • Computer Science, Interdisciplinary Applications
  • Engineering, Biomedical
  • Mathematical & Computational Biology

ID: 53742969