Automated quantification of atrial fibrillation complexity by probabilistic electrogram analysis and fibrillation wave reconstruction

Zeemering, Stef; Maesen, Bart; Nijs, Jan; Lau, Dennis H.; Granier, Mathieu; Verheule, Sander; Schotten, Ulrich

doi:10.1109/embc.2012.6347448

Cited by 28 publications

(43 citation statements)

References 5 publications

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“…[2][3][4][5][6]16 Detailed methods of unipolar electrogram deflection detection, AF wave reconstruction, and computation of these substrate parameters can be found in the Online Supplement. Furthermore, the automated deflection detection algorithm can differentiate local from nonlocal activations ( Figure 1).…”

Section: Characterization Of the Atrial Substrate By Highdensity Actimentioning

confidence: 99%

Indices of bipolar complex fractionated atrial electrograms correlate poorly with each other and atrial fibrillation substrate complexity

et al. 2015

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Section: Characterization Of the Atrial Substrate By Highdensity Actimentioning

confidence: 99%

Indices of bipolar complex fractionated atrial electrograms correlate poorly with each other and atrial fibrillation substrate complexity

et al. 2015

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“…The resulting plane then indicated the velocity (reciprocal value of the steepness of the plane) for each local activation point. 24 …”

Section: Analysis Of Fibrillation Electrogramsmentioning

confidence: 99%

Section: Analysis Of Fibrillation Electrogramsmentioning

confidence: 99%

“…24 Local deflections in the recorded electrograms were identified using a probabilistic electrogram algorithm. 24 Median AFCL was calculated using all fibrillation intervals of all electrodes. Effective conduction velocity was determined by plane fitting the activation time points at each electrode and its direct neighbors in a 5×5 grid.…”

Section: Analysis Of Fibrillation Electrogramsmentioning

confidence: 99%

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Catheter-Based Renal Denervation Reduces Atrial Nerve Sprouting and Complexity of Atrial Fibrillation in Goats

Linz

Hunnik

Hohl

et al. 2015

Circ: Arrhythmia and Electrophysiology

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Background-Atrial fibrillation (AF) leads to structural and neural remodeling in the atrium, which enhances AF complexity and perpetuation. Renal denervation (RDN) can reduce renal and whole-body sympathetic activity. Aim of this study was to determine the effect of sympathetic nervous system modulation by RDN on atrial arrhythmogenesis. Methods and Result-Eighteen goats were instrumented with an atrial endocardial pacemaker lead and a burst pacemaker.Percutaneous catheter-based RDN was performed in 8 goats (RDN-AF). Ten goats undergoing a sham procedure served as control (SHAM-AF). AF was induced and maintained by burst pacing for 6 weeks. High-resolution mapping was used to record epicardial conduction patterns of the right and left atrium. RDN reduced tyrosine hydroxylase-positive sympathetic nerve staining and resulted in lower transcardiac norepinephrine levels. This was associated with reduced expression of nerve growth factor-β, indicating less atrial nerve sprouting. Atrial endomysial fibrosis content was lower and myocyte diameter was smaller in RDN-AF. Median conduction velocity was higher (75±9 versus 65±10 cm/s, P=0.02), and AF cycle length was shorter in RDN-AF compared with SHAM-AF. Left atrial AF complexity (4.8±0.8 fibrillation waves/AF cycle length versus 8.5±0.8 waves/AF cycle length, P=0.001) and incidence of breakthroughs (2.0±0.3 versus 4.3±0.5 waves/AF cycle length, P=0.059) were lower in RDN-AF compared with SHAM-AF. Blood pressure was normal and not significantly different between the groups. Conclusions-RDN reduces atrial sympathetic nerve sprouting, structural alterations, and AF complexity in goats with persistent AF, independent of changes in blood pressure. (Circ Arrhythm Electrophysiol. 2015;8:466-474.

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“…[4] Candidate deflections were marked by template matching. Based on the largest and steepest candidate deflections, an estimate of the underlying probability density function of the AF cycle length was determined.…”

Section: 2mentioning

confidence: 99%

Spurious Rotor Detection During Atrial Fibrillation: Phase Singularities in Fact Reflect Blurred Conduction Block

Zeemering

Podziemski

Kuklik

et al. 2017

Computing in Cardiology Conference (CinC)

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Rotors during atrial fibrillation (AF) have been implicated as potential targets for AF ablation. Analysis in the phase domain to detect phase singularities (PS) may however blur the underlying wave front activation pattern, and obscure lines of conduction block. We investigated the coincidence of PS trajectories and lines of conduction block to assess the disruptive effect of phase reconstruction methods on the underlying propagation pattern and rotor detection accuracy. High-density unipolar electrograms were recorded in 20 patients with AF during cardiac surgery, using an electrode array (25x25 mm) placed on the left posterior and right atrial wall. Activation maps were constructed using probabilistic local deflection detection; phase maps were reconstructed using sinusoidal recomposition or frequency-based filtering, followed by phase computation using Hilbert transform or time-delay embedding. Conduction block was defined as local conduction velocity < 10 cm/s between adjacent electrode activations. In 38 recordings (10 seconds), 138 sustained PS trajectories were detected (lifespan > 1 atrial cycle), using sinusoidal recomposition and Hilbert transform, out of which 130 (94%) were consistently within 1 electrode distance (1.5 mm) of a line of conduction block. In contrast, concurrent points in the mapping array were consistently further away from a line of block than the detected PS points (median difference +2.1 mm, p 0.001). Other approaches to reconstruct phase maps yielded comparable results. The far majority of rotors detected in phase maps are co-located with a line of block in activation maps, not with a rotating wave front, showing that rotor detection by phase singularity tracking is a non-specific method in the presence of conduction block. Our results may explain why ablation at the core of a rotor can sometimes be successful.

show abstract

Automated quantification of atrial fibrillation complexity by probabilistic electrogram analysis and fibrillation wave reconstruction

Cited by 28 publications

References 5 publications

Indices of bipolar complex fractionated atrial electrograms correlate poorly with each other and atrial fibrillation substrate complexity

Indices of bipolar complex fractionated atrial electrograms correlate poorly with each other and atrial fibrillation substrate complexity

Catheter-Based Renal Denervation Reduces Atrial Nerve Sprouting and Complexity of Atrial Fibrillation in Goats

Spurious Rotor Detection During Atrial Fibrillation: Phase Singularities in Fact Reflect Blurred Conduction Block

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