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Artificial intelligence-enabled spatio-temporal dispersion mapping for persistent AF: Similarities and differences between pacing-induced or spontaneous AF
FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Other. Main funding source(s): Volta Medical Saint Joseph Hospital Marseille, France BACKGROUND: Spatiotemporal dispersion is an electrical footprint of atrial fibrillation (AF) drivers that has been successfully implemented to target extra-pulmonar...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10207180/ http://dx.doi.org/10.1093/europace/euad122.163 |
Sumario: | FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Other. Main funding source(s): Volta Medical Saint Joseph Hospital Marseille, France BACKGROUND: Spatiotemporal dispersion is an electrical footprint of atrial fibrillation (AF) drivers that has been successfully implemented to target extra-pulmonary veins (PVs) regions during persistent AF ablation. PURPOSE: The aim of the study is to characterize spatiotemporal dispersion extent and location and to compare dispersion atrial localization and extent between pacing-induced AF and spontaneous AF. METHODS: Spatiotemporal dispersion maps were built with an artificial intelligence software (VX1, Volta Medical) and analyzed in 71 consecutives persistent (66%) and long-standing persistent (34%) AF patients admitted for a first ablation procedure. Fifty-two patients were in spontaneous AF (73%) at the outset of the procedure while AF was induced in 19 patients (27%) by burst pacing ± isoproterenol infusion. A semi-quantitative visual quantification of dispersion extent was conducted by implementing an atrial segmentation into 22 regions and a region-centered score from 0 (no dispersion) to 3 (high dispersion). Also, an automated quantification was performed as follows: (i) a gradient filter designed to extract atrial shapes from background was applied, (ii) dispersion areas were segmented using a color thresholding method, and (iii) a structuring element was used to connect segmented dispersion areas. RESULTS: The regional characterization of dispersion shows that dispersion distribution follows a similar pattern and is present in similar atrial regions, regardless of whether AF is spontaneous or induced (Figure 1). Global dispersion extent, however, is significantly higher in the left atrium of patients in spontaneous AF compared to patients with induced AF (15.43% ± 9.04 versus 9.86% ± 6.41, P=0.0025, Figure 2). Accordingly, the regional dispersion score tends to be lower when AF is induced. Dispersion hotspots are: LSPV anterior antrum -ridge (R1), RSPV anterior antrum (R5), anterior wall (R9), roof (R10), posterior wall (R11), and low left atrial septum (R15) in the left atrium. In the right atrium: low right atrial septum (R15) and posterior right atrium (R20) (Figure 1). CONCLUSIONS: Artificial intelligence-enabled dispersion persistent AF mapping indicates that dispersion is reduced in induced vs. spontaneous-AF but that its distribution follows a similar pattern. [Figure: see text] [Figure: see text] |
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