Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102372
Title: Directed graph mapping exceeds phase mapping in discriminating true and false rotors detected with a basket catheter in a complex in-silico excitation pattern
Authors: Van, Nieuwenhuyse, E.
Martinez-Mateu, L.
Saiz, J.
Panfilov, A. V.
Vandersickel, N.
Issue Date: 2021
Publisher: Elsevier Ltd
Citation: Directed graph mapping exceeds phase mapping in discriminating true and false rotors detected with a basket catheter in a complex in-silico excitation pattern / E. Van Nieuwenhuyse, L. Martinez-Mateu, J. Saiz, et al. — DOI 10.1016/j.compbiomed.2021.104381 // Computers in Biology and Medicine. — 2021. — Vol. 133. — 104381.
Abstract: Atrial fibrillation (AF) is the most frequently encountered arrhythmia in clinical practise. One of the major problems in the management of AF is the difficulty in identifying the arrhythmia sources from clinical recordings. That difficulty occurs because it is currently impossible to verify algorithms which determine these sources in clinical data, as high resolution true excitation patterns cannot be recorded in patients. Therefore, alternative approaches, like computer modelling are of great interest. In a recent published study such an approach was applied for the verification of one of the most commonly used algorithms, phase mapping (PM). A meandering rotor was simulated in the right atrium and a basket catheter was placed at 3 different locations: at the Superior Vena Cava (SVC), the Crista Terminalis (CT) and at the Coronary Sinus (CS). It was shown that although PM can identify the true source, it also finds several false sources due to the far-field effects and interpolation errors in all three positions. In addition, the detection efficiency strongly depended on the basket location. Recently, a novel tool was developed to analyse any arrhythmia called Directed Graph Mapping (DGM). DGM is based on network theory and creates a directed graph of the excitation pattern, from which the location and the source of the arrhythmia can be detected. Therefore, the objective of the current study was to compare the efficiency of DGM with PM on the basket dataset of this meandering rotor. The DGM-tool was applied for a wide variety of conduction velocities (minimal and maximal), which are input parameters of DGM. Overall we found that DGM was able to distinguish between the true rotor and false rotors for both the SVC and CT basket positions. For example, for the SVC position with a [Formula presented], DGM detected the true core with a prevalence of 82% versus 94% for PM. Three false rotors where detected for 39.16% (DGM) versus 100% (PM); 22.64% (DGM) versus 100% (PM); and 0% (DGM) versus 57% (PM). Increasing CVmin to [Formula presented] had a stronger effect on the false rotors than on the true rotor. This led to a detection rate of 56.6% for the true rotor, while all the other false rotors disappeared. A similar trend was observed for the CT position. For the CS position, DGM already had a low performance for the true rotor for [Formula presented] (14.7%). For [Formula presented] the false and the true rotors could therefore not be distinguished. We can conclude that DGM can overcome some of the limitations of PM by varying one of its input parameters (CVmin). The true rotor is less dependent on this parameter than the false rotors, which disappear at a [Formula presented]. In order to increase to detection rate of the true rotor, one can decrease CVmin and discard the new rotors which also appear at lower values of CVmin. © 2021 The Author(s)
Keywords: ATRIAL ARRHYTHMIA
COMPLEX EXCITATION PATTERN
DGM
DIRECTED GRAPH MAPPING
GUIDED ABLATION
IN-SILICO STUDY
NETWORK THEORY
CATHETERS
CIRCUIT THEORY
COMPLEX NETWORKS
DIRECTED GRAPHS
EFFICIENCY
LOCATION
MAPPING
NETWORK THEORY (GRAPHS)
ATRIAL ARRHYTHMIA
ATRIAL FIBRILLATION
COMPLEX EXCITATION PATTERN
DIRECTED GRAPH MAPPING
EXCITATION PATTERN
GUIDED ABLATION
IN-SILICO STUDY
PHASE MAPPINGS
SUPERIOR VENA CAVA
DISEASES
URI: http://hdl.handle.net/10995/102372
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85104675694
PURE ID: 21866674
5a5757b7-90de-4688-96ed-e6a67089191e
ISSN: 104825
DOI: 10.1016/j.compbiomed.2021.104381
metadata.dc.description.sponsorship: Supported in part by Dirección General de Política Científica de la Generalitat Valenciana (grant ID PROMETEU 2020/043), Valencia, Spain. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 900008), Brussels, Belgium. 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 personalized healthcare” (grant ID 075-15-2020-926), Russia.
CORDIS project card: 900008
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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