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Local activation time sampling density for atrial tachycardia contact mapping: how much is enough?

AIMS: Local activation time (LAT) mapping forms the cornerstone of atrial tachycardia diagnosis. Although anatomic and positional accuracy of electroanatomic mapping (EAM) systems have been validated, the effect of electrode sampling density on LAT map reconstruction is not known. Here, we study the...

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Detalles Bibliográficos
Autores principales: Williams, Steven E, Harrison, James L, Chubb, Henry, Whitaker, John, Kiedrowicz, Radek, Rinaldi, Christopher A, Cooklin, Michael, Wright, Matthew, Niederer, Steven, O'Neill, Mark D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834039/
https://www.ncbi.nlm.nih.gov/pubmed/28379525
http://dx.doi.org/10.1093/europace/eux037
Descripción
Sumario:AIMS: Local activation time (LAT) mapping forms the cornerstone of atrial tachycardia diagnosis. Although anatomic and positional accuracy of electroanatomic mapping (EAM) systems have been validated, the effect of electrode sampling density on LAT map reconstruction is not known. Here, we study the effect of chamber geometry and activation complexity on optimal LAT sampling density using a combined in silico and in vivo approach. METHODS AND RESULTS: In vivo 21 atrial tachycardia maps were studied in three groups: (1) focal activation, (2) macro-re-entry, and (3) localized re-entry. In silico activation was simulated on a 4×4cm atrial monolayer, sampled randomly at 0.25–10 points/cm(2) and used to re-interpolate LAT maps. Activation patterns were studied in the geometrically simple porcine right atrium (RA) and complex human left atrium (LA). Activation complexity was introduced into the porcine RA by incomplete inter-caval linear ablation. In all cases, optimal sampling density was defined as the highest density resulting in minimal further error reduction in the re-interpolated maps. Optimal sampling densities for LA tachycardias were 0.67 ± 0.17 points/cm(2) (focal activation), 1.05 ± 0.32 points/cm(2) (macro-re-entry) and 1.23 ± 0.26 points/cm(2) (localized re-entry), P = 0.0031. Increasing activation complexity was associated with increased optimal sampling density both in silico (focal activation 1.09 ± 0.14 points/cm(2); re-entry 1.44 ± 0.49 points/cm(2); spiral-wave 1.50 ± 0.34 points/cm(2), P < 0.0001) and in vivo (porcine RA pre-ablation 0.45 ± 0.13 vs. post-ablation 0.78 ± 0.17 points/cm(2), P = 0.0008). Increasing chamber geometry was also associated with increased optimal sampling density (0.61 ± 0.22 points/cm(2) vs. 1.0 ± 0.34 points/cm(2), P = 0.0015). CONCLUSION: Optimal sampling densities can be identified to maximize diagnostic yield of LAT maps. Greater sampling density is required to correctly reveal complex activation and represent activation across complex geometries. Overall, the optimal sampling density for LAT map interpolation defined in this study was ∼1.0–1.5 points/cm(2).