Spatial Correlation Analysis of Atrial Activation Patterns during Sustained Atrial Fibrillation in Conscious Goats

In this study we applied both linear and nonlinear spatial correlation measures to characterize epicardial activation patterns of sustained atrial fibrillation in instrumented conscious goats. It was investigated if nonlinearity was involved in the spatial coupling of atrial regions and to what extent fibrillation was organized in the experimental model of sustained atrial fibrillation (AF) in instrumented goats. Data were collected in five goats during experiments to convert AF by continuous infusion of cibenzoline. Spatial organization during AF was quantified with the linear spatial cross correlation function and the nonlinear spatial cross redundancy which was calculated using the Grassberger-Procaccia correlation integral. Two different types of correlation were evaluated to distinguish simultaneous interaction from non-simultaneous interaction, for instance resulting from propagation of fibrillation waves. The nonlinear association length and the linear correlation length were estimated along the principal axes of iso-correlation contours in two-dimensional correlation maps of the nonlinear spatial redundancy and the linear spatial correlation function, respectively. To quantitatively assess the degree of nonlinearity, the association length was also estimated from the linearized spatial redundancy using multivariate surrogate data. The differences between the nonlinear and linearized association lengths indicated that a nonlinear component in the spatial organization of AF predominantly existed in the right atrium. The degree of organization characterized by association length along the short principal axis was higher in the right atrium (15 ± 7 mm) than in the left atrium (8 ± 4 mm). The spatial extension of coherent atrial patches was estimated from a surface of association equal to the area spanned by the principal axes of iso-correlation contours from the redundancy, including the effects from non-simultaneous interaction. Interpreting this area as the spatial domain of a fibrillation wavelet, the results suggest that the mapped region was activated on average by two wavelets in the left atrium and by one wavelet in the right atrium. Therefore, the activation pattern of sustained AF in goats was relatively organized, consistent with type II of AF. It is suggested that the surface of association is a measure of the number of independent wavelets present in the atria during sustained AF, and that larger association lengths result from fewer and larger reentrant circuits.

[1]  A. Sahakian,et al.  Measuring the organization of cardiac rhythms using the magnitude-squared coherence function , 1990, IEEE Engineering in Medicine and Biology Magazine.

[2]  Milan PALUS Testing For Nonlinearity Using Redundancies: Quantitative and Qualitative Aspects , 1994 .

[3]  Maurits A. Allessie,et al.  What Are the Electrophysiological Mechanisms of Perpetuation of Atrial Fibrillation , 1998 .

[4]  Richard A. Gray,et al.  SPIRAL WAVES AND THE HEART , 1996 .

[5]  F.X. Witkowski,et al.  Epicardial cardiac source-field behavior , 1995, IEEE Transactions on Biomedical Engineering.

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

[7]  S. Olsson,et al.  Epicardial right atrial free wall mapping in chronic atrial fibrillation. Documentation of repetitive activation with a focal spread--a hitherto unrecognised phenomenon in man. , 1997, European heart journal.

[8]  M. Allessie,et al.  Experimental evaluation of Moe's multiple wavelet hypothesis of atrial fibrillation , 1985 .

[9]  Milan Paluš,et al.  Testing for Nonlinearity in Weather Records , 1994 .

[10]  J.B. Peck,et al.  The effects of refractoriness and conduction velocity on spatial organization in a computer model of atrial fibrillation , 1994, Computers in Cardiology 1994.

[11]  P B Corr,et al.  The surgical treatment of atrial fibrillation. II. Intraoperative electrophysiologic mapping and description of the electrophysiologic basis of atrial flutter and atrial fibrillation. , 1991, The Journal of thoracic and cardiovascular surgery.

[12]  L. J. Leon,et al.  Spatiotemporal evolution of ventricular fibrillation , 1998, Nature.

[13]  C. Starmer The Cardiac Vulnerable Period and Reentrant Arrhythmias: Targets of Anti‐ and Proarrhythmic Processes , 1997, Pacing and clinical electrophysiology : PACE.

[14]  J L Cox,et al.  Simultaneous Epicardial and Endocardial Activation Sequence Mapping in the Isolated Canine Right Atrium , 1993, Circulation.

[15]  S. Pogwizd,et al.  Mechanisms Underlying Ventricular Tachycardia and Fibrillation in the Ischemic Heart: Relation to Nonlinear Dynamics a , 1990, Annals of the New York Academy of Sciences.

[16]  Theiler,et al.  Generating surrogate data for time series with several simultaneously measured variables. , 1994, Physical review letters.

[17]  M. Allessie,et al.  Unravelling the electrical mysteries of atrial fibrillation. , 1996, European heart journal.

[18]  Josep Brugada,et al.  Regional Entrainment of Atrial Fibrillation Studied by High‐Resolution Mapping in Open‐Chest Dogs , 1993, Circulation.

[19]  M. Fishbein,et al.  Reentrant wave fronts in Wiggers' stage II ventricular fibrillation. Characteristics and mechanisms of termination and spontaneous regeneration. , 1996, Circulation research.

[20]  W. M. Smith,et al.  Spatial organization, predictability, and determinism in ventricular fibrillation. , 1998, Chaos.

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

[22]  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.

[23]  Cornelis J. Stam,et al.  Reliable detection of nonlinearity in experimental time series with strong periodic components , 1998 .

[24]  M Eiselt,et al.  Using mutual information to measure coupling in the cardiorespiratory system. , 1998, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[25]  F. Witkowski,et al.  Activation Patterns During Ventricular Fibrillation a , 1990, Annals of the New York Academy of Sciences.

[26]  G. Moe,et al.  On the multiple wavelet hypothesis o f atrial fibrillation. , 1962 .

[27]  S Swiryn,et al.  Differentiation of ventricular tachyarrhythmias. , 1990, Circulation.

[28]  James Theiler,et al.  Testing for nonlinearity in time series: the method of surrogate data , 1992 .

[29]  S Swiryn,et al.  The coherence spectrum. A quantitative discriminator of fibrillatory and nonfibrillatory cardiac rhythms. , 1989, Circulation.

[30]  M. Paluš Detecting Nonlinearity in Multivariate Time Series , 1996 .

[31]  J.M. Smith,et al.  A technique for measurement of the extent of spatial organization of atrial activation during atrial fibrillation in the intact human heart , 1995, IEEE Transactions on Biomedical Engineering.

[32]  B F Hoffman,et al.  Cellular mechanisms for cardiac arrhythmias. , 1981, Circulation research.

[33]  Schreiber,et al.  Improved Surrogate Data for Nonlinearity Tests. , 1996, Physical review letters.

[34]  M. Allessie,et al.  Atrial fibrillation begets atrial fibrillation. A study in awake chronically instrumented goats. , 1995, Circulation.

[35]  A Garfinkel,et al.  Role of pectinate muscle bundles in the generation and maintenance of intra-atrial reentry: potential implications for the mechanism of conversion between atrial fibrillation and atrial flutter. , 1998, Circulation research.

[36]  P D Wolf,et al.  Regional capture of fibrillating ventricular myocardium. Evidence of an excitable gap. , 1995, Circulation research.

[37]  R. Gray,et al.  Incomplete reentry and epicardial breakthrough patterns during atrial fibrillation in the sheep heart. , 1996, Circulation.

[38]  P. Grassberger Finite sample corrections to entropy and dimension estimates , 1988 .

[39]  James Theiler,et al.  Generalized redundancies for time series analysis , 1995 .

[40]  R. Damle,et al.  Spatial and Temporal Linking of Epicardial Activation Directions During Ventricular Fibrillation in Dogs: Evidence for Underlying Organization , 1992, Circulation.

[41]  G. Sawicki,et al.  Flecainide and the Electrophysiologic Matrix: , 1996, Journal of cardiovascular electrophysiology.

[42]  J Jalife,et al.  Mechanisms of atrial fibrillation: mother rotors or multiple daughter wavelets, or both? , 1998, Journal of cardiovascular electrophysiology.

[43]  M. Allessie,et al.  High-density mapping of electrically induced atrial fibrillation in humans. , 1994, Circulation.

[44]  James Theiler,et al.  Constrained-realization Monte-carlo Method for Hypothesis Testing , 1996 .

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

[46]  M J Janse,et al.  Ventricular Fibrillation Is Not Always Due to Multiple Wavelet Reentry , 1995, Journal of cardiovascular electrophysiology.

[47]  Y. Rudy,et al.  Mapping the conversion of atrial flutter to atrial fibrillation and atrial fibrillation to atrial flutter. Insights into mechanisms. , 1994, Circulation research.

[48]  James Theiler,et al.  Using surrogate data to detect nonlinearity in time series , 1991 .

[49]  H.J. Sih,et al.  A frequency domain analysis of spatial organization of epicardial maps , 1995, IEEE Transactions on Biomedical Engineering.

[50]  Estimate of electromotive surface dimension during ventricular fibrillation , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[51]  R. Ideker,et al.  Evolution of the Organization of Epicardial Activation Patterns During Ventricular Fibrillation , 1998, Journal of cardiovascular electrophysiology.

[52]  N. Kouchoukos,et al.  Characterization of Atrial Fibrillation in Man: Studies Following Open Heart Surgery * , 1978, Pacing and clinical electrophysiology : PACE.

[53]  Allessie,et al.  Circus movement in rabbit atrial muscle as a mechanism of tachycardia. III. The "leading circle" concept: a new model of circus movement in cardiac tissue without the involvement of an anatomical obstacle. , 1977, Circulation research.

[54]  A Murray,et al.  Evidence for Electrical Organization During Ventricular Fibrillation in the Human Heart , 1995, Journal of cardiovascular electrophysiology.

[55]  Alfonso M Albano,et al.  Phase-randomized surrogates can produce spurious identifications of non-random structure , 1994 .

[56]  M. Paluš,et al.  Information theoretic test for nonlinearity in time series , 1993 .

[57]  P V Bayly,et al.  Quantitative techniques for analyzing high-resolution cardiac-mapping data. , 1998, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[58]  P. Grassberger,et al.  Estimation of the Kolmogorov entropy from a chaotic signal , 1983 .

[59]  S Swiryn,et al.  Evidence for Transient Linking of Atrial Excitation During Atrial Fibrillation in Humans , 1992, Circulation.

[60]  W. Rheinboldt,et al.  A COMPUTER MODEL OF ATRIAL FIBRILLATION. , 1964, American heart journal.

[61]  L. Glass,et al.  Theory of heart : biomechanics, biophysics, and nonlinear dynamics of cardiac function , 1991 .

[62]  D. Ruelle,et al.  Ergodic theory of chaos and strange attractors , 1985 .

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

[64]  Al Young Providence, Rhode Island , 1975 .

[65]  A. T. Winfree,et al.  Estimating the Ventricular Fibrillation Threshold , 1991 .

[66]  P. Wolf,et al.  A Quantitative Measurement of Spatial Orderin Ventricular Fibrillation , 1993, Journal of cardiovascular electrophysiology.

[67]  Maurits A. Allessie,et al.  Nonlinear analysis of the pharmacological conversion of sustained atrial fibrillation in conscious goats by the class Ic drug cibenzoline. , 1997, Chaos.

[68]  A. Winfree,et al.  Electrical turbulence in three-dimensional heart muscle. , 1994, Science.

[69]  A. Sahakian,et al.  Computer Discrimination of Atrial Fibrillation and Regular Atrial Rhythms from Intra‐Atrial Electrograms , 1988, Pacing and clinical electrophysiology : PACE.

[70]  A. Fraser Reconstructing attractors from scalar time series: A comparison of singular system and redundancy criteria , 1989 .

[71]  R. Ideker,et al.  Efficient electrode spacing for examining spatial organization during ventricular fibrillation , 1993, IEEE Transactions on Biomedical Engineering.

[72]  M. Lesh,et al.  Organized Activation During Atrial Fibrillation in Man , 1998, Journal of cardiovascular electrophysiology.

[73]  James Theiler,et al.  Detecting Nonlinearity in Data with Long Coherence Times , 1993, comp-gas/9302003.

[74]  J Jalife,et al.  Drifting vortices of electrical waves underlie ventricular fibrillation in the rabbit heart. , 1996, Acta physiologica Scandinavica.

[75]  M. Allessie,et al.  Configuration of unipolar atrial electrograms during electrically induced atrial fibrillation in humans. , 1997, Circulation.

[76]  M. Allessie,et al.  Widening of the excitable gap during pharmacological cardioversion of atrial fibrillation in the goat: effects of cibenzoline, hydroquinidine, flecainide, and d-sotalol. , 2000, Circulation.

[77]  E.J. Berbari,et al.  A high-temporal resolution algorithm for quantifying organization during atrial fibrillation , 1999, IEEE Transactions on Biomedical Engineering.

[78]  M. Allessie,et al.  Circus Movement in Rabbit Atrial Muscle as a Mechanism of Tachycardia , 1973, Circulation research.

[79]  Schuster,et al.  Generalized dimensions and entropies from a measured time series. , 1987, Physical review. A, General physics.

[80]  R. A. Gray,et al.  Mechanisms of Cardiac Fibrillation , 1995, Science.