TY - JOUR

T1 - Directed Graph Mapping exceeds Phase Mapping for the detection of simulated 2D meandering rotors in fibrotic tissue with added noise

AU - Lootens, Sebastiaan

AU - Janssens, Iris

AU - Van den Abeele, Robin

AU - Wülfers, Eike

AU - Bezerra, Arthur Santos

AU - Verstraeten, Bjorn

AU - Hendrickx, Sander

AU - Okenov, Arstanbek

AU - Nezlobinsky, Timur

AU - Panfilov, Alexander

AU - Vandersickel, Nele

N1 - Текст о финансировании #1 This research was supported by a ‘Starting Grant’ from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (Grant No. 900008), awarded to Nele Vandersickel. A.V. Panfilov's research at Sechenov University was financed by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers “Digital Biodesign and personalised healthcare” (Grant No 075-15-2022-304). Текст о финансировании #2 A.V. Panfilov’s research at Sechenov University was financed by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers “Digital Biodesign and personalised healthcare” (Grant No 075-15-2022-304 ). Текст о финансировании #3 This research was supported by a ‘Starting Grant’ from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant No. 900008 ), awarded to Nele Vandersickel.

PY - 2024/3/1

Y1 - 2024/3/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85185561015

UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=001198186700001

U2 - 10.1016/j.compbiomed.2024.108138

DO - 10.1016/j.compbiomed.2024.108138

M3 - Article

VL - 171

JO - Computers in Biology and Medicine

JF - Computers in Biology and Medicine

SN - 0010-4825

M1 - 108138

ER -