Use of a neural network to generate a whole atrium 3D reconstruction of electrographic flow and basket catheter geometry from biosignals alone. (19th May 2022)

• Record Type: Journal Article
• Authors: Gagyi, R; Szili-Torok, T; Grund, A; Ahapov, K; Ruppersberg, P; Kong, M; Haeusser, P
• Is Part Of: Europace. Volume 24:Supplement 1(2022)
• Publication Date: 2022-05-19
• Subjects: Arrhythmia -- Treatment -- Periodicals; Cardiac pacing -- Periodicals; Catheter ablation -- Periodicals; Heart -- Physiology -- Periodicals; Electrophysiology -- Periodicals; 617.4120645
• DOI: 10.1093/europace/euac053.598
• Languages: English
• ISSNs: 1099-5129

Abstract

Abstract: Funding Acknowledgements: Type of funding sources: None. Background: Electrographic flow (EGF) mapping detects and quantifies patterns of electrical wavefront propagation in the atrial myocardium from basket catheter recordings. However, no single catheter can map the entire endocardial surface simultaneously. Creating panoramic maps of the whole atrium may be possible by reconstructing multiple basket positions obtained within a few minutes of each other. Purpose: Present a method of 3D reconstruction of EGF maps generated from individual basket recordings using QRS morphologies and CT anatomies. Methods: EGF maps were generated from unipolar signals recorded over 1 minute from 64-pole basket catheters. QRS morphologies recorded by each individual electrode were used to train a neural network (NN) on the reconstruction of the basket geometries in 3D. The NN uses the similarities between QRS morphologies to represent multiple recordings in one coherent 3D space and spatially integrate phenomena across multiple recordings without any external navigation system. Results: A basket catheter was placed in the superior vena cava of a chronic AF canine model. The catheter was manually pulled back in steps of 5mm under fluoroscopic supervision. After reconstruction of the 3D electrode positions, a successive displacement of 3.5±1.2mm per step was reproduced. We applied the proposed method on recordings of 18 patients where an EGF source was identified. Independently, an expert determined the source locations on a 3rd party navigation system, based on 10 predefined regions in the left atrium. In 83% of the cases, the proposed method projected the sources in the same or adjacent region. Conclusion: Novel 3D reconstruction from QRS signatures enables integration of EGF maps from multiple basket recordings that can be aligned with CT anatomy. Due to the real-time EGF map acquisition, synthesizing maps from more than 1 basket position provides a more panoramic visualization of complex atrial flow patterns.