Spatial autocorrelation dimension as a potential determinant for the temporal persistence of human atrial and ventricular fibrillation

Background: Despite being central to atrial fibrillation (AF) and ventricular fibrillation (VF) mechanisms and therapy, the factors governing AF and VF termination are poorly understood. It has been noted that ratio of system size (L) and the two-point spatial correlation length (ξ2) are associated with time until termination in transient spatiotemporally chaotic systems, but the relationship between these characteristics and termination has not been systematically studied in human AF and VF. Objective: We aimed assess whether the time to cardiac fibrillation termination can be predicted using a novel estimator, the spatial autocorrelation dimension (Di), defined as the ratio of L and ξ2, in human AF and VF. Methods: Di was computed and compared in a multi-centre, multi-system study with data for sustained versus spontaneously terminating human AF/VF. VF data was collected during coronary-bypass surgery; and AF data during clinically indicated AF ablation. We analyzed: i) VF mapped using a 256-electrode epicardial sock (n=12pts); ii) AF mapped using a 64-electrode constellation basket-catheter (n=15pts); iii) AF mapped using a 16-electrode HD-grid catheter (n=42pts). To investigate temporal fibrillation persistence, the response of AF-episodes to flecainide (n=7pts) was also studied. Results: Spontaneously terminating fibrillation demonstrated a lower Di (P<0.001 all systems). Lower Di was also seen in paroxysmal compared to persistent AF (P=0.002). Post-flecainide, Di decreased over time (P<0.001). Lower Di was also associated with longer-lasting episodes of AF/VF (R2>0.90, P<0.05 in all cases). Using k-means clustering, two distinct clusters and their centroids were identified i) a cluster of spontaneously terminating episodes, and ii) a cluster of sustained epochs. Conclusion: Di predicts the temporal persistence of cardiac fibrillation. This finding provides potentially important insights into a possible common pathway to termination and therapeutic approaches.

[1]  S. Bun,et al.  Recurrences of Atrial Fibrillation Despite Durable Pulmonary Vein Isolation: The PARTY-PVI Study , 2023, Circulation. Arrhythmia and electrophysiology.

[2]  L. Morrison,et al.  Defibrillation Strategies for Refractory Ventricular Fibrillation. , 2022, The New England journal of medicine.

[3]  Rahul Wadke,et al.  Atrial fibrillation. , 2022, Disease-a-month : DM.

[4]  R. Clayton,et al.  A governing equation for rotor and wavelet number in human clinical ventricular fibrillation: Implications for sudden cardiac death. , 2021, Heart rhythm.

[5]  K. Higuchi,et al.  Propagation Vectors Facilitate Differentiation Between Conduction Block, Slow Conduction, and Wavefront Collision , 2021, Circulation. Arrhythmia and electrophysiology.

[6]  R. Clayton,et al.  M/M/Infinity Birth-Death Processes – A Quantitative Representational Framework to Summarize and Explain Phase Singularity and Wavelet Dynamics in Atrial Fibrillation , 2021, Frontiers in Physiology.

[7]  R. Perry,et al.  Prospective cross‐sectional study using Poisson renewal theory to study phase singularity formation and destruction rates in atrial fibrillation (RENEWAL‐AF): Study design , 2020, Journal of arrhythmia.

[8]  Jörn Dunkel,et al.  Topological turbulence in the membrane of a living cell , 2020 .

[9]  U. Parlitz,et al.  Terminating transient chaos in spatially extended systems. , 2020, Chaos.

[10]  K. Pope,et al.  Renewal Theory as a Universal Quantitative Framework to Characterize Phase Singularity Regeneration in Mammalian Cardiac Fibrillation. , 2019, Circulation. Arrhythmia and electrophysiology.

[11]  P. Sommer,et al.  Cardiac Mapping Systems: Rhythmia, Topera, EnSite Precision, and CARTO. , 2019, Cardiac electrophysiology clinics.

[12]  W. Sauer,et al.  Mapping Atrial Fibrillation and Finding a Method to the Madness. , 2019, JACC. Clinical electrophysiology.

[13]  Erez Brem,et al.  A novel octaray multielectrode catheter for high‐resolution atrial mapping: Electrogram characterization and utility for mapping ablation gaps , 2019, Journal of cardiovascular electrophysiology.

[14]  S. Chacko,et al.  High-resolution mapping of the atria using the HD Grid catheter , 2019, HeartRhythm case reports.

[15]  S. Nattel,et al.  Controversies About Atrial Fibrillation Mechanisms: Aiming for Order in Chaos and Whether it Matters , 2017, Circulation research.

[16]  Kalyanam Shivkumar,et al.  Long-term clinical outcomes of focal impulse and rotor modulation for treatment of atrial fibrillation: A multicenter experience. , 2016, Heart rhythm.

[17]  Michel Haïssaguerre,et al.  Ablation of Persistent Atrial Fibrillation Targeting Low-Voltage Areas With Selective Activation Characteristics , 2016, Circulation. Arrhythmia and electrophysiology.

[18]  Mathias Baumert,et al.  Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation , 2016, Proceedings of the IEEE.

[19]  Prashanthan Sanders,et al.  Long‐term Outcomes of Catheter Ablation of Atrial Fibrillation: A Systematic Review and Meta‐analysis , 2013, Journal of the American Heart Association.

[20]  Daniel Steven,et al.  Long-term single- and multiple-procedure outcome and predictors of success after catheter ablation for persistent atrial fibrillation. , 2011, Heart rhythm.

[21]  José Jalife,et al.  Déjà vu in the theories of atrial fibrillation dynamics. , 2011, Cardiovascular research.

[22]  Jian-Young Wu,et al.  Spiral Wave Dynamics in Neocortex , 2010, Neuron.

[23]  Patrick T. Ellinor,et al.  Challenges in the classification of atrial fibrillation , 2010, Nature Reviews Cardiology.

[24]  Prashanthan Sanders,et al.  Outcomes of long-standing persistent atrial fibrillation ablation: a systematic review. , 2010, Heart rhythm.

[25]  Prashanthan Sanders,et al.  Characterization of electrograms associated with termination of chronic atrial fibrillation by catheter ablation. , 2008, Journal of the American College of Cardiology.

[26]  Martyn P. Nash,et al.  Evidence for Multiple Mechanisms in Human Ventricular Fibrillation , 2006, Circulation.

[27]  Prashanthan Sanders,et al.  Spectral Analysis Identifies Sites of High-Frequency Activity Maintaining Atrial Fibrillation in Humans , 2005, Circulation.

[28]  K. Nademanee,et al.  A new approach for catheter ablation of atrial fibrillation: mapping of the electrophysiologic substrate. , 2004, Journal of the American College of Cardiology.

[29]  Lance B Becker,et al.  Resuscitation after cardiac arrest: a 3-phase time-sensitive model. , 2002, JAMA.

[30]  S. Hohnloser,et al.  Rhythm or rate control in atrial fibrillation—Pharmacological Intervention in Atrial Fibrillation (PIAF): a randomised trial , 2000, The Lancet.

[31]  Ilarion V. Melnikov,et al.  Mechanisms of extensive spatiotemporal chaos in Rayleigh–Bénard convection , 2000, Nature.

[32]  M. Allessie,et al.  Spatial Correlation Analysis of Atrial Activation Patterns during Sustained Atrial Fibrillation in Conscious Goats , 2000, Archives of physiology and biochemistry.

[33]  R. A. Gray,et al.  Ventricular fibrillation and atrial fibrillation are two different beasts. , 1998, Chaos.

[34]  M. Courtemanche,et al.  Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. , 1998, The American journal of physiology.

[35]  R. Gray,et al.  Spatial and temporal organization during cardiac fibrillation , 1998, Nature.

[36]  A Garfinkel,et al.  Spatiotemporal complexity of ventricular fibrillation revealed by tissue mass reduction in isolated swine right ventricle. Further evidence for the quasiperiodic route to chaos hypothesis. , 1997, The Journal of clinical investigation.

[37]  R. Ecke,et al.  Spiral defect chaos in Rayleigh-Be´nard convection: defect population statistics , 1997 .

[38]  M. Fishbein,et al.  Mechanism of spontaneous termination of functional reentry in isolated canine right atrium. Evidence for the presence of an excitable but nonexcited core. , 1996, Circulation.

[39]  Feudel,et al.  Supertransient chaos in the two-dimensional complex Ginzburg-Landau equation. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[40]  J. M. Smith,et al.  Quantitative assessment of the spatial organization of atrial fibrillation in the intact human heart. , 1996, Circulation.

[41]  Sailes K. Sengijpta.  Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[42]  Ying-Cheng Lai,et al.  Persistence of supertransients of spatiotemporal chaotic dynamical systems in noisy environment , 1995 .

[43]  Henry S. Greenside,et al.  Relation between fractal dimension and spatial correlation length for extensive chaos , 1994, Nature.

[44]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[45]  A. Murray,et al.  Self-terminating ventricular tachyarrhythmias—a diagnostic dilemma? , 1993, The Lancet.

[46]  Huber,et al.  Nucleation and transients at the onset of vortex turbulence. , 1992, Physical review letters.

[47]  Kunihiko Kaneko,et al.  Supertransients, spatiotemporal intermittency and stability of fully developed spatiotemporal chaos , 1990 .

[48]  Jensen,et al.  Transition to turbulence in a discrete Ginzburg-Landau model. , 1990, Physical review. A, Atomic, molecular, and optical physics.

[49]  John J. Tyson,et al.  When Time Breaks Down: The Three‐Dimensional Dynamics of Electrochemical Waves and Cardiac Arrhythmias , 1988 .

[50]  Crutchfield,et al.  Are attractors relevant to turbulence? , 1988, Physical review letters.

[51]  J. Bigby.  Harrison's Principles of Internal Medicine , 1988 .

[52]  D P Zipes,et al.  Termination of ventricular fibrillation in dogs by depolarizing a critical amount of myocardium. , 1975, The American journal of cardiology.

[53]  A. Winfree.  Spiral Waves of Chemical Activity , 1972, Science.

[54]  W. Garrey.  THE NATURE OF FIBRILLARY CONTRACTION OF THE HEART. ‐ ITS RELATION TO TISSUE MASS AND FORM 1 , 1914 .

[55]  P. Kirchhof,et al.  Pathophysiological mechanisms of atrial fibrillation: a translational appraisal. , 2011, Physiological reviews.

[56]  Nathalie Virag,et al.  Wavelength and vulnerability to atrial fibrillation: Insights from a computer model of human atria. , 2005, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[57]  M. Courtemanche,et al.  Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. , 1998, American journal of physiology. Heart and circulatory physiology.