Cross-Fourier analysis for differentiating prolonged and self-terminating ventricular tachycardia in isolated rat hearts4 views
Keywords:Ventricular tachycardia; Arrhythmia; Bivariate time-series; Mechano-electrical coupling.
The interaction between the ventricles and atria in the heart is an important aspect of cardiac function. During ventricular arrhythmias, such as ventricular tachycardia and ventricular fibrillation, the atrial interbeat interval appears different from that of normal sinus rhythm, even though there is no direct electrical connection between the ventricles and atria. To understand this phenomenon, bivariate time-series Fourier analysis was performed on ventricular and atrial signals. The results showed different levels of correlation from the ventricles to the atria during ventricular arrhythmias. We found that low interaction was associated with self-terminating ventricular arrhythmias, while strong connections were mostly seen in sustained ventricular arrhythmias. These findings suggest that the underlying mechanism behind this interaction may be due to the presence of mechano-electrical coupling, which serves as a bridge from the ventricles to the atria (reciprocal connections).
. R. J. Myerburg, A. Castellanos, “Cardiac arrest and cardiac death, in: E. Braunwald (Eds), Heart Disease: A Textbook of Cardiovascular Medicine”. Philadelphia,PA, Saunders, p. 742, (1997).
. E. Sandoe, B. Sigurd, “Arrhythmia—A Guide to Clinical Electrocardiology”, chapter 3, Verlags GmbH, Bingen am Rhein, Germany, (1991).
. A. Karma, R.F. Gilmore Jr, “Nonlinear dynamics of heart rhythm disorders”. Physics Today, 60(3), 51-57, (2007). DOI: https://doi.org/10.1063/1.2718757
. Z. Qu, J.N. Weiss, “Dynamics and cardiac arrhythmias”. J. Cardiovasc Electrophysiol 17 1042–1049, (2006). DOI: https://doi.org/10.1111/j.1540-8167.2006.00567.x
. R. K. Thakur, G. J. Klein, C. A. Sivaram, M .Zardini, D. E. Schleinkofer, H. Nakagawa, R. Yee, W.M. Jackman, “Anatomic substrate for idiopathic left ventricular tachycardia”, Circulation 93, 497–501, (1996). DOI: https://doi.org/10.1161/01.CIR.93.3.497
. B. Befeler, “Mechanical stimulation of the heart: its therapeutic value in tachyarrhythmia”. Chest 73, 832–838, (1978). DOI: https://doi.org/10.1378/chest.73.6.832
. T.A. Quinn, P. Kohl, “Cardiac Mechano-Electric Coupling: Acute Effects of Mechanical Stimulation on Heart Rate and Rhythm”, Physiol. Rev. 101(10), 37-92, (2021). DOI: https://doi.org/10.1152/physrev.00036.2019
. K. Daqrouq, A. Alkhateeb, M.N. Ajour, A. Morfeq, “Neural network and wavelet average framing percentage energy for atrial fibrillation classification”, Comput. Methods Prog. Biomed., 113 (3) 919-926, (2014). DOI: https://doi.org/10.1016/j.cmpb.2013.12.002
. P. D. Arini, F. H. Baglivo, J. P. Mart´ınez, and P. Laguna, “Evaluation of ventricular repolarization dispersion during acute myocardial ischemia: spatial and temporal ECG indices”, Med. Biol. Eng. Comput., 52, 375–391, (2014). DOI: https://doi.org/10.1007/s11517-014-1136-z
. P.C. Ivanov et al., “Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis”, Nature, 383, 323–327, (1996). DOI: https://doi.org/10.1038/383323a0
. R.J. Martis, U.R. Acharya, H. Adeli, “Current methods in electrocardiogram characterization”, Comput. Biol. Med. 48, 133–149, (2014). DOI: https://doi.org/10.1016/j.compbiomed.2014.02.012
. Ö. Yıldırım, P. Pławiak, R.-S. Tan, U.R. Acharya, “Arrhythmia Detection Using Deep Convolutional Neural Network with Long Duration ECG Signals”. Comput. Biol. Med. 102, 411–420, (2018). DOI: https://doi.org/10.1016/j.compbiomed.2018.09.009
. D. M. Le, A. V. Dvornikov, P. Y. Lai and C. K. Chan, “Predicting Self-terminating Ventricular Fibrillation in an Isolated Heart, Europhys”. Lett., 104, 48002, (2013). DOI: https://doi.org/10.1209/0295-5075/104/48002
. A.V. Dvornikov, Y.C. Mi, C.K. Chan, “Transient analysis of force–frequency relationships in rat hearts perfused by Krebs-Henseleit and Tyrode solutions with different [Ca2+]o. Cardiovasc”. Eng. Technol., 3, 203–210, (2012). DOI: https://doi.org/10.1007/s13239-012-0091-9
. S. Sridhar, D.M. Le, Y.C. Mi, S. Sinha, P.Y. Lai, C.K. Chan, “Suppression of cardiac alternans by alternating period feedback stimulations”, Phys. Rev. E 87, 042712, (2013). DOI: https://doi.org/10.1103/PhysRevE.87.042712
. National Research Council, “Guide for the Care and Use of Laboratory Animals”, National Academy Press, Washington DC, (2011).
. R. N. Bracewell, “The Fourier Transform and its Applications”, 3rd edition, McGraw Hill, Boston, (2000).
. A Kamkin, I Kiseleva, G Isenberg, K.D Wagner, J Günther, H Theres, H Scholz, “Cardiac fibroblasts and the mechanoelectric feedback mechanism in healthy and diseased hearts”, Prog. Biophys. Mol. Biol., 82, 111-120, (2003). DOI: https://doi.org/10.1016/S0079-6107(03)00009-9
. V. N. Biktashev, “Dissipation of the Excitation Wave Fronts”, Physics Review Letter 89, 168102, (2002). DOI: https://doi.org/10.1103/PhysRevLett.89.168102
. O. V. Aslanidi, A. Bailey, V. N. Biktashev, R. H. Clayton, and A. V. Holden, “Enhanced self-termination of re-entrant arrhythmias as a pharmacological strategy for antiarrhythmic action”, Chaos 12, 843–851, (2002). DOI: https://doi.org/10.1063/1.1500496
. I. Biktasheva, V. Biktashev, W. Dawes, A. Holden, R. Saumarez, A.M. Savill, “Dissipation of the excitation front as a mechanism of self-terminating arrhythmias”. Int. J. Bifurc. Chaos 13, 3645–3656, (2003). DOI: https://doi.org/10.1142/S0218127403008909
. M.A. de la Casa, F.J. de la Rubia, P.C. Ivanov, “Patterns of spiral wave attenuation by low-frequency periodic planar fronts”, Chaos 17, 015109, (2007). DOI: https://doi.org/10.1063/1.2404640
. C. M. Armstrong and G. Cota, “Calcium block of Na+ channels and its effect on closing rate”, Proc. Natl. Acad. Sci. U.S.A., 96, 4154-4157, (1999). DOI: https://doi.org/10.1073/pnas.96.7.4154