Propagation of meandering rotors surrounded by areas of high dominant frequency in persistent atrial fibrillation

Salinet, João; Schlindwein, Fernando S.; Stafford, Peter J.; Almeida, Tiago P.; Li, Xin; Vanheusden, Frederique J.; Guillem, María S.; Ng, Guseva

doi:10.1016/j.hrthm.2017.04.031

Cited by 29 publications

(39 citation statements)

References 34 publications

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“…The results suggest that the increase of irregular activations on fractionated AEGs was not necessarily associated to a random structure. On the contrary, RQA has revealed a residual amount of determinism, which could be related to unstable periodic orbits in repeating patterns of activations, indicating the presence of mechanisms recurring intermittently in preferred atrial regions during persAF, in line with recent findings [6,9].…”

Section: Discussionsupporting

confidence: 83%

“…Different methods have been introduced to identify such remodelled atrial substrates to guide persAF ablation -such as fractionated atrial electrograms (AEGs) and functional re-entrieswith promising initial results [2,3]. More recent works, however, could not reproduce such results [4,5], possibly due to the existence of multiple mechanisms participating -either simultaneously or intermittently -in its perpetuation [2,3,6], methodological heterogeneities [7], and poor understanding of the underlying AF dynamics [4,6,8,9]. Therefore, biological markers that better explain AF behaviour to guide ablation are still in debate.…”

Section: Introductionmentioning

confidence: 99%

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Deterministic Structures in Fractionated Atrial Electrograms During Human Persistent Atrial Fibrillation

Almeida

Schlindwein

Salinet

et al. 2017

Computing in Cardiology Conference (CinC)

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Deterministic Structures in Fractionated Atrial Electrograms During Human Persistent Atrial Fibrillation

Almeida

Schlindwein

Salinet

et al. 2017

Computing in Cardiology Conference (CinC)

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“…Phase maps were generated for detecting singularity points (SPs), defined as the points around which all the phases converge [9], using a method based on edge detection: endpoints of edges detected by Canny's method were defined as SP candidates [11]. The detection of the SPs is based on the phase progression along 5 rings (radii from 2 to 10 cm) around the SP candidates.…”

Section: Phase Analysismentioning

confidence: 99%

Effects of Reducing the Number of Leads from Body Surface Potential Mapping in Computer Models of Atrial Arrhythmias

Marques¹,

Rodrigo²,

Sánchez³

et al. 2019

2019 Computing in Cardiology Conference (CinC)

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Body surface potential mapping (BSPM) can be an important tool in ablation therapy planning. Results obtained with high resolution (HR) computer models must be translated to realistic numbers of leads. This study aims to evaluate the impact on atrial tachycardia (AT), flutter (AFL) and fibrillation (AF) characterization by reducing the number of BSPM leads. 19 realistic computer simulations with 567 leads (HR) have been used to characterize the arrhythmias concerning the dominant frequencies (DF) and phase singularity point (SP) distributions. DF maps were generated combining Welch periodogram and activation detection with wavelet transform modulus maxima. Phase was calculated with Hilbert transform on signals filtered around the highest DF (±1Hz); dynamics of SPs were analyzed using histograms (heatmaps, HMs) and connecting SPs along time (filaments). The analyses were reproduced for 6 layouts with 252 to 16 leads and results were compared using the structural similarity index (SSIM), sensitivity and precision in SP detection and analyzing features extracted from the maps. SSIM was lower in AF than in AFL or AT for DF maps and HMs, but was in average above 0.6 for layouts with 32 leads or more. In HMs, a loss in spatial resolution with fewer leads is reflected in decreasing values for sensitivity and precision. Features from DF maps, filaments or HMs were statistically equivalent in all layouts. HR 252 leads 131 leads 67 leads 64 leads 32 leads 16 leads Frequency Analysis AT 4.06 ± 0.03 4.06 ± 0.03 4.06 ± 0.03 5.04 ± 0.97 5.04 ± 0.97 4.06 ± 0.03 4.06 ± 0.03 AFL 4.09 ± 0.12 4.09 ± 0.12 4.09 ± 0.12 4.09 ± 0.12 4.09 ± 0.12 4.09 ± 0.12 4.09 ± 0.12 f d r i ve (Hz) AF 5.58 ± 0.23 5.58 ± 0.23 5.58 ± 0.23 5.37 ± 0.30 5.58 ± 0.23 5.56 ± 0.23 5.59 ± 0.22 AT 0.76 ± 0.70 1.28 ± 0.78 1.10 ± 0.69 2.26 ± 2.28 1.89 ± 1.61 0.67 ± 0.66 0.70 ± 0.67 AFL 0.24 ± 0.49 0.24 ± 0.49 0.24 ± 0.49 0.24 ± 0.49 0.24 ± 0.49 0.24 ± 0.49 0.24 ± 0.49

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“…Phase maps were generated in order to detect singularity points (SPs), defined as the points around which all the phases converge [6], using a method based on edge detection: endpoints of edges detected by Canny's method were defined as SP candidates [8].…”

Section: Phase Analysismentioning

confidence: 99%

Non-Invasive Characterization of Atrial Arrhythmic Driving Mechanisms in Computer Models

Marques¹,

Rodrigo²,

Sánchez³

et al. 2019

2019 Computing in Cardiology Conference (CinC)

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Atrial tachycardia (AT), atrial flutter (AFL) and atrial fibrillation (AF) are among the most common cardiac arrhythmias and are driven by localized sources (ectopic focus in AT, macro-reentrant circuit in AFL and rotors in AF) that can be targeted for ablation. We aimed to characterize such mechanisms from the non-invasive perspective of body surface potential mapping (BSPM), using realistic computer models. Dominant frequency (DF) maps were studied to estimate the frequency of the driving mechanism and to analyze its spatio-temporal distribution of this frequency. Singularity points (SPs) were detected in phase maps and their distribution and rotational patterns were compared between arrhythmias. The driver frequencies were more expressed on the anterior portion of the torso for the right atrium and on the posterior portion for the left atrium. Rotational activity was detected in all arrhythmias, with increasing levels of spatial-temporal stability (AF, AT and AFL, respectively). These results can be used to identify the driving mechanisms and, in the future, to locate them in the atria.

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Propagation of meandering rotors surrounded by areas of high dominant frequency in persistent atrial fibrillation

Abstract: Multiple PS points drifting over the LA were identified with their clusters correlating spatially with the DF regions. After pulmonary vein isolation, the PS's complexity was reduced, which supports the notion that PS sites represent areas of relevance to the atrial substrate.

Cited by 29 publications

References 34 publications

Deterministic Structures in Fractionated Atrial Electrograms During Human Persistent Atrial Fibrillation

Deterministic Structures in Fractionated Atrial Electrograms During Human Persistent Atrial Fibrillation

Effects of Reducing the Number of Leads from Body Surface Potential Mapping in Computer Models of Atrial Arrhythmias

Non-Invasive Characterization of Atrial Arrhythmic Driving Mechanisms in Computer Models

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