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Article Abstract

In this work, we present the release of a novel easy to use software package called DGM or Directed-Graph-Mapping. DGM can automatically analyze any type of arrhythmia to find reentry or focal sources if the measurements are synchronized in time. Currently, DGM requires the local activation times (LAT) and the spatial coordinates of the measured electrodes. However, there is no requirement for any spatial organization of the electrodes, allowing to analyze clinical, experimental or computational data. DGM creates directed networks of the activation, which are analyzed with fast algorithms to search for reentry (cycles in the network) and focal sources (nodes with outgoing arrows). DGM has been mainly optimized to analyze atrial tachycardia, but we also discuss other applications of DGM demonstrating its wide applicability. The goal is to release a free software package which can allow researchers to save time in the analysis of cardiac data. An academic license is attached to the software, allowing only non-commercial use of the software. All updates of the software, user and installation guide will be published on a dedicated website www.dgmapping.com . Graphical Abstract Direct-Graph-Mapping is a method to automatically analyze a given arrhythmia by converting measured data of the electrodes in a directed network. DGM requires the local activation times (LAT) and the spatial coordinates of the measured electrodes. There is no requirement for any spatial organization of the electrodes, allowing to analyze clinical, experimental or computational data (see left). An example could be the LATs and coordinates from a CARTO file. DGM creates a directed network of the activation by (1) determining the neighbors of each node, 2 (2) allowing a directed arrow between two neighbors if propagation of the electrical wave is possible, (3) repeating this process for all nodes, (4) if necessary, redistributing the nodes more uniformly and repeating step (1)-(3). Two possible steps are (5) to visualize the wavefront by creating an average graph or (6) find the cycles in the network which represent the reentry loops. Focal sources are nodes with only outgoing arrows.

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http://dx.doi.org/10.1007/s11517-022-02550-yDOI Listing

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