Computation and Projection of Spiral Wave Trajectories During Atrial Fibrillation

Pashaei, Ali; Bayer, Jason D.; Meillet, Valentin; Dubois, Rémi; Vigmond, Edward J.

doi:10.1016/j.ccep.2014.11.001

Cited by 3 publications

(2 citation statements)

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“…In our study, problems with incorrect phase assignment between beats were not observed, in contrast to previous studies 26. This is because the filtering and normalisation steps of our algorithm led to a sinusoidal signal of suitable amplitude and mean.…”

Section: Discussioncontrasting

confidence: 75%

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

et al. 2016

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Extracellular electrograms recorded during atrial fibrillation (AF) are challenging to interpret due to the inherent beat-to-beat variability in amplitude and duration. Phase mapping represents these voltage signals in terms of relative position within the cycle, and has been widely applied to action potential and unipolar electrogram data of myocardial fibrillation. To date, however, it has not been applied to bipolar recordings, which are commonly acquired clinically. The purpose of this study is to present a novel algorithm for calculating phase from both unipolar and bipolar electrograms recorded during AF. A sequence of signal filters and processing steps are used to calculate phase from simulated, experimental, and clinical, unipolar and bipolar electrograms. The algorithm is validated against action potential phase using simulated data (trajectory centre error <0.8 mm); between experimental multi-electrode array unipolar and bipolar phase; and for wavefront identification in clinical atrial tachycardia. For clinical AF, similar rotational content (R 2 = 0.79) and propagation maps (median correlation 0.73) were measured using either unipolar or bipolar recordings. The algorithm is robust, uses standard signal processing techniques, and accurately quantifies AF wavefronts and sources. Identifying critical sources, such as rotors, in AF, may allow for more accurate targeting of ablation therapy and improved patient outcomes.Electronic supplementary materialThe online version of this article (doi:10.1007/s10439-016-1766-4) contains supplementary material, which is available to authorized users.

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Section: Discussioncontrasting

confidence: 75%

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

et al. 2016

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“…21 Other studies also described rotor attractions to long APD regions, albeit with a sharp heterogeneities. 40 A recent study by Sekar et al 41 utilized circular monolayers with overexpression of I K1 either in a central circular island or in its periphery to show that rotors stably pivot around the island regardless of the relative level of I K1 . In that study, the gradient, however, was very sharp relative to the size of the rotor core, and the preparation was highly symmetrical, which may explain why that study did not show a preferential anchoring of rotors to either low or high inward rectifying K + current levels as observed in this and other studies.…”

Section: Discussionmentioning

confidence: 99%

The Major Role of I_K1 in Mechanisms of Rotor Drift in the Atria: A Computational Study

Berenfeld

2016

Clin Med Insights Cardiol

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Maintenance of paroxysmal atrial fibrillation (AF) by fast rotors in the left atrium (LA) or at the pulmonary veins (PVs) is not fully understood. This review describes the role of the heterogeneous distribution of transmembrane currents in the PVs and LA junction (PV-LAJ) in the localization of rotors in the PVs. Experimentally observed heterogeneities in IK1, IKs, IKr, Ito, and ICaL in the PV-LAJ were incorporated into models of human atrial kinetics to simulate various conditions and investigate rotor drifting mechanisms. Spatial gradients in the currents resulted in shorter action potential duration, less negative minimum diastolic potential, slower upstroke and conduction velocity for rotors in the PV region than in the LA. Rotors under such conditions drifted toward the PV and stabilized at the less excitable region. Our simulations suggest that IK1 heterogeneity is dominant in determining the drift direction through its impact on the excitability gradient. These results provide a novel framework for understanding the complex dynamics of rotors in AF.

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Firing patterns transition and network dynamics of an extended Hindmarsh-Rose neuronal system

Fu,

Wang

2024

Indian J Phys

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Computation and Projection of Spiral Wave Trajectories During Atrial Fibrillation

Cited by 3 publications

References 20 publications

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

The Major Role of I_K1 in Mechanisms of Rotor Drift in the Atria: A Computational Study

Firing patterns transition and network dynamics of an extended Hindmarsh-Rose neuronal system

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Computation and Projection of Spiral Wave Trajectories During Atrial Fibrillation

Cited by 3 publications

References 20 publications

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

The Major Role of IK1 in Mechanisms of Rotor Drift in the Atria: A Computational Study

Firing patterns transition and network dynamics of an extended Hindmarsh-Rose neuronal system

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Product

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The Major Role of I_K1 in Mechanisms of Rotor Drift in the Atria: A Computational Study