Analysis of QRS-T subtraction in unipolar atrial fibrillation electrograms

Salinet, João; Madeiro, João Paulo do Vale; Cortez, Paulo César; Stafford, Peter J.; Ng, Guseva; Schlindwein, Fernando S.

doi:10.1007/s11517-013-1071-4

Cited by 37 publications

(26 citation statements)

References 24 publications

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“…AF electrograms are challenging to analyze because of fractionation, varying cycle lengths, and complex activation patterns, which result in difficulty assigning activation times and windows when assigning isochronal maps and hence unlike atrial tachycardias are not suitable for clinical activation mapping. Removal of the ventricular signal from atrial electrograms can also be problematic, 28 and poor-quality signals can arise if an electrode is not in good contact with excitable tissue. By converting the signals into phase, spatiotemporal mapping can be performed without the need to assign activation timings or windows, and the center of rotational activation is clearly identified (PS 11 ).…”

Section: Discussionmentioning

confidence: 99%

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation

Child

Clayton

Roney

et al. 2018

Circ: Arrhythmia and Electrophysiology

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Background: The mechanisms that initiate and sustain persistent atrial fibrillation are not well characterized. Ablation results remain significantly worse than in paroxysmal atrial fibrillation in which the mechanism is better understood and subsequent targeted therapy has been developed. The aim of this study was to characterize and quantify patterns of activation during atrial fibrillation using contact mapping. Methods: Patients with persistent atrial fibrillation (n=14; mean age, 61±8 years; ejection fraction, 59±10%) underwent simultaneous biatrial contact mapping with 64 electrode catheters. The atrial electrograms were transformed into phase, and subsequent spatiotemporal mapping was performed to identify phase singularities (PSs). RESULTS: PSs were located in both atria, but we observed more PSs in the left atrium compared with the right atrium (779±302, 552±235; P =0.015). Although some PSs of duration sufficient to complete >1 rotation were detected, the maximum PS duration was only 1150 ms, and the vast majority (97%) of PSs persisted for too short a period to complete a full rotation. Although in selected patients there was evidence of PS local clustering, overall, PSs were distributed globally throughout both chambers with no clear anatomic predisposition. In a subset of patients (n=7), analysis was repeated using an alternative established atrial PS mapping technique, which confirmed our initial findings. Conclusions: No sustained rotors or localized drivers were detected, and instead, the mechanism of arrhythmia maintenance was consistent with the multiple wavelet hypothesis, with passive activation of short-lived rotational activity. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01765075.

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Section: Discussionmentioning

confidence: 99%

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation

Child

Clayton

Roney

et al. 2018

Circ: Arrhythmia and Electrophysiology

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“…Since the unipolar signals can have a significant far field ventricular component, a QRST subtraction was applied to remove the ventricular influence using a method previously described by Salinet et al [7]. Power spectra were derived using Fast Fourier Transform (FFT) with a Hamming window for every 1 s long time window with 50% overlap for all the 2048 points in the LA to find the DF, defined as the frequency component with highest power in the frequency range between 4 and 10 Hz.…”

Section: Data Acquisition and Signal Processingmentioning

confidence: 99%

Dynamic Behavior of Rotors during Human Persistent Atrial Fibrillation as observed using Non:Contact Mapping

Dastagir¹,

Almeida²,

Li³

et al. 2016

2016 Computing in Cardiology Conference (CinC)

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Rotors have been related to atrial fibrillation (AF) maintenance. We analyzed the behavior of rotors in persistent AF (persAF) utilizing a novel non-contact methodology and compared this to real time dominant frequency (DF) analysis.2048 noncontact virtual unipolar atrial electrograms (VEGMs) were collected simultaneously (EnSite Array, St. Jude Medical) from 10 persAF patients (duration: 34 ± 25 months) undergoing left atrial (LA) ablation. After QRST-removal, FFT was used to identify the global DF of the LA (range 4 -10 Hz; 1 s time-window; 50 % overlap; highest DF (HDF) (DF -0.25 Hz); up to 20 s/patient). The organization index (OI) was measured and phase was found via Hilbert-transform.Phase singularities (PSs) were tracked and were categorized according to their lifespan into short (lifespan <100 ms) and long lived (rotors) (lifespan ≥100 ms). A total of 4578 PSs were tracked. 5.05 % (IQR: 2.75 ~ 30.25 %) of the tracked PSs were long-lived and were observed in 11 % (IQR: 2.75 ~ 17.5 %) of the windows. The windows with rotors showed significantly higher HDF (mean ± SD, 8.0 ± 0.43 Hz vs 7.71 ± 0.50 Hz, p< 0.0001) and lower OI (0.76 ± 0.04 vs 0.79 ± 0.03, p< 0.0001) when compared with the short-lived PSs windows.During persAF, the LA showed distinct behaviors as characterized by rotors. Often, no rotors were observed during sustained AF and, when present, the rotors continually switched between organized and disorganized behaviors. Long-lived rotors correlated with higher atrial rates. Our results suggest that rotors are not the sole perpetuating mechanism in persAF.

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“…With this purpose, we only looked for phase variations along those frequencies in which the average power of atrial activity is concentrated [1.71-7.57Hz] [18].…”

Section: Feature Extractionmentioning

confidence: 99%

Time:Frequency Analysis for Early Classification of Persistent and Long:Standing Persistent Atrial Fibrillation

Ortigosa

Cano

Galbis

et al. 2016

2016 Computing in Cardiology Conference (CinC)

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Analysis of QRS-T subtraction in unipolar atrial fibrillation electrograms

Cited by 37 publications

References 24 publications

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation

Dynamic Behavior of Rotors during Human Persistent Atrial Fibrillation as observed using Non:Contact Mapping

Time:Frequency Analysis for Early Classification of Persistent and Long:Standing Persistent Atrial Fibrillation

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