Skip to main content
Log in

Estimating the time scale and anatomical location of atrial fibrillation spontaneous termination in a biophysical model

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Due to their transient nature, spontaneous terminations of atrial fibrillation (AF) are difficult to investigate. Apparently, confounding experimental findings about the time scale of this phenomenon have been reported, with values ranging from 1 s to 1 min. We propose a biophysical modeling approach to study the mechanisms of spontaneous termination in two models of AF with different levels of dynamical complexity. 8 s preceding spontaneous terminations were studied and the evolution of cycle length and wavefront propagation were documented to assess the time scale and anatomical location of the phenomenon. Results suggest that termination mechanisms are dependent on the underlying complexity of AF. During simulated AF of low complexity, the total process of spontaneous termination lasted 3,200 ms and was triggered in the left atrium 800 ms earlier than in the right atrium. The last fibrillatory activity was observed more often in the right atrium. These asymmetric termination mechanisms in both time and space were not observed during spontaneous terminations of complex AF simulations, which showed less predictable termination patterns lasting only 1,600 ms. This study contributes to the interpretation of previous clinical observations, and illustrates how computer modeling provides a complementary approach to study the mechanisms of cardiac arrhythmias.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Agladze K, Kay MW, Krinsky V, Sarvazyan N (2006) Interaction between spiral and paced waves in cardiac tissue. Am J Physiol Heart Circ Physiol 293(1):H503–H513

    Article  Google Scholar 

  2. Alcaraz R, Rieta JJ, Hornero F (2008) Non-invasive characterization of atrial activity immediately prior to termination of paroxysmal atrial fibrillation. Rev Esp Cardiol 61(2):154–160

    Article  PubMed  Google Scholar 

  3. Camm AJ, Kirchhof P, Lip GYH, Schotten U, Savelieva I, Ernst S, Gelder ICV, Al-Attar N, Hindricks G, Prendergast B, Heidbuchel H, Alfieri O, Angelini A, Atar D, Colonna P, Caterina RD, Sutter JD, Goette A, Gorenek B, Heldal M, Hohloser SH, Kolh P, Heuzey JYL, Ponikowski P, Rutten FH (2010) Guidelines for the management of atrial fibrillation: the task force for the management of atrial fibrillation of the European Society of Cardiology (ESC). Eur Heart J 31(19):2369–2429

    Article  PubMed  Google Scholar 

  4. Courtemanche M, Ramirez R, Nattel S (1998) Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. Am J Physiol 275(1):H301–H321

    PubMed  CAS  Google Scholar 

  5. Fujiki A, Sakabe M, Nishida K, Mizumaki K, Inoue H (2003) Role of fibrillation cycle length in spontaneous and drug-induced termination of human atrial fibrillation. Circ J 67(5):391–395

    Article  PubMed  Google Scholar 

  6. Harrild D, Henriquez C (2000) A computer model of normal conduction in the human atria. Circ Res 87:e25–e36

    Article  PubMed  CAS  Google Scholar 

  7. Jacquemet V, Virag N, Ihara Z, Dang L, Blanc O, Zozor S, Vesin JM, Kappenberger L, Henriquez C (2003) Study of unipolar electrogram morphology in a computer model of atrial fibrillation. J Cardiovasc Electrophysiol 14:S172–S179

    Article  PubMed  Google Scholar 

  8. Jacquemet V, Virag N, Kappenberger L (2005) Wavelength and vulnerability to atrial fibrillation: insights from a computer model of human atria. Europace 7:S83–S92

    Article  Google Scholar 

  9. Kim BS, Kim YH, Hwang GS, Pak HN, Lee SC, Shim WJ, Oh DJ, Ru YM (2002) Action potential duration restitution kinetics in human atrial fibrillation. J Am Coll Cardiol 39:1329–1336

    Article  PubMed  Google Scholar 

  10. Kneller J, Kalifa J, Zou R, Zaitsev AV, Warren M, Berenfeld O, Vigmond EJ, Leon LJ, Nattel S, Jalife J (2005) Mechanisms of atrial fibrillation termination by pure sodium channel blockade in an ionically-realistic mathematical model. Circ Res 96(5):e35–e47

    Article  PubMed  CAS  Google Scholar 

  11. Konings KT, Kirchhof CJ, Smeets JR, Wellens HJ, Penn OC, Allessie MA (1994) High-density mapping of electrically induced atrial fibrillation in humans. Circulation 89(4):1665–1680

    PubMed  CAS  Google Scholar 

  12. Lines GT, MacLachlan MC, Linge S, Tveito A (2009) Synchronizing computer simulations with measurement data for a case of atrial flutter. Ann Biomed Eng 37:1287–1293

    Article  PubMed  Google Scholar 

  13. Luo CH, Rudy Y (1991) A model of ventricular cardiac action potential. Circ Res 68:1501–1526

    PubMed  CAS  Google Scholar 

  14. Moe GK (1962) On the multiple wavelet hypothesis of atrial fibrillation. Arch Int Pharmacodyn Ther 140:183–188

    Google Scholar 

  15. Ndrepepa G, Weber S, Karch MR, Schneider MAE, Schömig A, Schmitt C (2002) Electrophysiologic characteristics of the spontaneous onset and termination of atrial fibrillation. Am J Cardiol 90:1215–1220

    Article  PubMed  Google Scholar 

  16. Petrutiu S, Sahakian AV, Swiryn S (2007) Abrupt changes in fibrillatory waves characteristics at the termination of paroxysmal atrial fibrillation in humans. Europace 9(7):466–470

    Article  PubMed  Google Scholar 

  17. Reumann M, Bohnert J, Seeman G, Osswals B, Dössel O (2008) Preventive ablation strategies in a biophysical model of atrial fibrillation based on realistic anatomical data. IEEE Trans Biomed Eng 55:399–406

    Article  PubMed  Google Scholar 

  18. Ruchat P, Dang L, Virag N, von Segesser LK, Kappenberger L (2007) Use of a biophysical model of atrial fibrillation in the interpretation of the outcomes of surgical ablation procedures. Eur J Cardiothorac Surg 32:90–95

    Article  PubMed  Google Scholar 

  19. Shao H, Sampson KJ, Pormann JB, Rose DJ, Henriquez CS (2004) A resistor interpretation of general anisotropic cardiac tissue. Math Biosci 187:155–174

    Article  PubMed  Google Scholar 

  20. Sih HJ, Ropella KM, Swiryn S, Gerstenfeld EP, Sahakian AV (1994) Observations from intraatrial recordings on the termination of electrically induced atrial fibrillation in humans. Pacing Clin Electrophysiol 17:1231–1242

    Article  PubMed  CAS  Google Scholar 

  21. Sih HJ, Zipes DP, Berbari EJ, Adams E, Olgin JE (2000) Differences in organization between acute and chronic atrial fibrillation in dogs. J Am Coll Cardiol 36(3):924–931

    Article  PubMed  CAS  Google Scholar 

  22. Spector PS, Habel N, Sobel BE, Bates JHT (2011) Emergence of complex behavior: an interactive model of cardiac excitation provides a powerful tool for understanding electrical propagation. Circ Arrhythm Electrophysiol 4(4):586–591

    Article  PubMed  Google Scholar 

  23. Uldry L, Virag N, Vesin JM, Kappenberger L (2010) Optimizing local capture of atrial fibrillation: a model based study of the influence of tissue dynamics on the outcome of rapid pacing. Ann Biomed Eng 38(12):3664–3673

    Article  PubMed  Google Scholar 

  24. Vaisrub S (1950) Spontaneous reversion to normal sinus rhythm in a case of auricular fibrillation of long standing. Can Med Assoc J 63:599–600

    PubMed  CAS  Google Scholar 

  25. Vigmond EJ, Tsoi V, Kuo S, Arvalo H, Kneller J, Nattel S, Trayanova N (2004) The effect of vagally induced dispersion of action potential duration on atrial arrhythmogenesis. Heart Rhythm 1:334–344

    Article  PubMed  Google Scholar 

  26. Virag N, Jacquemet V, Henriquez CS, Zozor S, Blanc O, Vesin JM, Pruvot E, Kappenberger L (2002) Study of arrhythmias in a computer model based on magnetic resonance images of human atria. Chaos 12:754–763

    Article  PubMed  Google Scholar 

  27. Zozor S, Blanc O, Jacquemet V, Virag N, Vesin JM, Pruvot E, Kappenberger L, Henriquez CS (2003) A numerical scheme for modeling wavefront propagation on a monolayer of arbitrary geometry. IEEE Trans Biomed Eng 50:412–420

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the Theo-Rossi-Di-Montelera Foundation, the Swiss Governmental Commission of Innovative Technologies (CTI), Medtronic Europe, the Natural Sciences and Engineering Research Council of Canada, and the Heart and Stroke Foundation of Québec.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Laurent Uldry.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (MPG 3198 kb)

Supplementary material 2 (MPG 3174 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Uldry, L., Jacquemet, V., Virag, N. et al. Estimating the time scale and anatomical location of atrial fibrillation spontaneous termination in a biophysical model. Med Biol Eng Comput 50, 155–163 (2012). https://doi.org/10.1007/s11517-011-0859-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-011-0859-3

Keywords

Navigation