Europace (2014) 16, 703–704 doi:10.1093/europace/euu085
FOCUSED ISSUE: EDITORIAL
Computational cardiac electrophysiology is moving towards translation medicine Stefano Severi1*, Blanca Rodriguez2, and Antonio Zaza 3 1 Department of Electrical, Electronic and Information Engineering ‘Guglielmo Marconi’, University of Bologna, Via Venezia 52, 47023 Cesena, Italy; 2Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK; and 3Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2–4, 20126 Milano, Italy
computational approaches could be used and what is their expected value in this area. With regard to diagnostic tools, two papers are focused on the use of noninvasive electroanatomical imaging to assess conduction disorders. Seger et al.6 apply this approach to assess epi- and endocardial ventricular activation during cardiac resynchronization therapy. Their tool may be useful to locate the area of latest ventricular activation, thus helping in the optimization of lead placement. Van Dam et al.7 propose a noninvasive imaging tool for the early recognition of bundle branch blocks during transcatheter aortic valve implantation. This is essentially a feasibility study, showing how the location of conduction disorders can be precisely defined by advanced computerassisted imaging. Pervolaraki et al.8 developed a computational model of propagation during normal sinus rhythm in the foetal human heart. Although awaiting validation, the study constitutes a first attempt to model this novel problem and provides a basis for computational interpretation of the response of the foetal electrocardiogram (ECG) under disease states and pharmacological interventions. The ability of septal pacing to capture AF has been investigated by Rusu et al.9 They found that an AF substrate had a significant impact on the outcome of rapid pacing, thus increasing the information that can be extracted from capture protocols. Dependency on the AF substrate would also explain the high interindividual variability in the response to pacing. In a more theoretical study, Zaniboni and Cacciani10 adopt a novel 3D representation of cardiac action potential to compactly visualize and analyse the dynamical properties of human cellular ventricular repolarization. This representation identifies an auto-regenerativerepolarization-phase, suitable to estimate repolarization stability, and its response to drugs, in single and coupled myocytes. The concept is relevant to the in silico prediction of proarrhythmia. Together, the two parts of this Focused Issue on Computational Cardiac Electrophysiology offer a comprehensive overview of the state of the art of computational approaches for studies of the mechanisms, diagnosis, and treatment of arrhythmogenesis. Moreover, two additional papers will be published in a following issue of EP-Europace. The first one is a computational study on the effects of b-blockers on AF, in which Kharche et al.11 show that AF
* Corresponding author. Tel: +39 0547 339127; fax: +39 0547 339114. E-mail address: [email protected] Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2014. For permissions please email: [email protected].
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In the present Issue of EP-Europace, we publish the second part of the Focused Issue on ‘Computational Cardiac Electrophysiology’, which was previously introduced in March 2014.1 Whereas the first part featured contributions on the computational analysis of ‘arrhythmias mechanisms’, the present Issue mainly focuses on the descriptions of novel computational approaches for diagnosis and interventions in clinical arrhythmology. In this sense, although there are clearly many challenges that must still be overcome along the way, the articles in this issue show that Computational Cardiac Electrophysiology is moving towards Translational Medicine. With regard to the application of the computational approach to the antiarrhythmic therapies, Trayanova and Rantner2 review the insights provided by the three-dimensional (3D) computational models of defibrillation and of shock-induced arrhythmogenesis, including the description of a relevant attempt of clinical translation regarding the model-based prediction of the optimal ICD placement in paediatric and congenital heart defect patients. An original contribution also related to the understanding of arrhythmia induction and defibrillation is the study by Colli Franzone et al.3 on the spatial distribution of intracellular calcium (Cai) dynamics following premature stimulations. In agreement with recent experimental investigations, they found significant regions of Cai elevation located at the virtual cathode regions. Such spatial heterogeneity in Cai dynamics may feedback on membrane potential and play an important role in arrhythmia induction by programmed stimulation. Ravelli and Mase`4 review the state of the art of computational mapping in atrial fibrillation (AF). The experimental studies, the signal processing methods and the clinical studies focused on the analysis of rate and organization of AF are reviewed. They point out how the integration of signal-derived maps may guide the localization of critical sources and the planning of new target ablation strategies. In their work, Wis´niowska et al.5 review successes, issues, and challenges associated with the use of computer-based approaches for cardiac drug safety assessment, including pro-arrhythmia. The review covers a description of in vitro, in vivo, and in silico methods for cardiac drug assessment, and discusses the challenges and limitations associated with their combined use and their validation. The discussion is set to trigger further thoughts and discussions on how
704 suppression may involve a reduced propensity for maintenance of re-entrant excitation waves, as a consequence of ionic remodelling. In the second one, Zenzemi and Rodriguez12 present a multiscale framework for preclinical in silico drug testing and use it to investigate the simultaneous effect of L-type calcium channel and hERG block on human ventricular electrophysiology from ionic to ECG level. We would like to thank all the authors for their contributions, which have enabled the illustration of the wide range of approaches and applications in Computational Cardiac Electrophysiology. We would also like to extend the invitation and encourage future submissions of high-quality papers in Computational Cardiac Electrophysiology to EP-Europace.
References 1. Severi S, Rodriguez B, Zaza A. Computational cardiac electrophysiology is ready for prime time. Europace 2014;16:382–383. 2. Trayanova NA, Rantner LJ. New insights into defibrillation of the heart from realistic simulation studies. Europace 2014;16:705–13. 3. Colli Franzone P, Pavarino LF, Scacchi S. Effects of premature anodal stimulations on cardiac transmembrane potential and intracellular calcium distributions computed by anisotropic Bidomain models. Europace 2014;16:736 – 42.
Editorial
4. Ravelli F, Mase` M. Computational mapping in atrial fibrillation: how the integration of signal-derived maps may guide the localization of critical sources. Europace 2014;16: 714 –23. 5. Wis´niowska B, Mendyk A, Fijorek K, Polak S. Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges.. Europace 2014;16:724 –35. 6. Seger M, Hanser F, Dichtl W, Stuehlinger M, Hintringer F, Trieb T et al. Non-invasive imaging of cardiac electrophysiology in a cardiac resynchronization therapy defibrillator patient with a quadripolar left ventricular lead. Europace 2014;16:743 –49. 7. van Dam PM, Proniewska K, Maugenest A-M, van Mieghem NM, Mann AC, de Jaegere PPT et al. Electrocardiographic imaging-based recognition of possible induced bundle branch blocks during transcatheter aortic valve implantations. Europace 2014;16:750 – 7. 8. Pervolaraki E, Hodgson S, Holden AV, Benson AP. Towards computational modelling of the human foetal electrocardiogram: normal sinus rhythm and congenital heart block. Europace 2014;16:758–66. 9. Rusu A, Jacquemet V, Vesin J-M, Virag N. Influence of atrial substrate on local capture induced by rapid pacing of atrial fibrillation. Europace 2014;16:766 –73. 10. Zaniboni M, Cacciani F. Instantaneous current–voltage relationships during the course of the human cardiac ventricular action potential: new computational insights into repolarization dynamics. Europace 2014;16:774–84. 11. Kharche SR, Stary T, Colman MA, Biktasheva I, Workman AJ, Rankin A et al. Effects of human atrial ionic remodelling by b-blocker therapy on mechanisms of AF: a computer simulation. Europace 2014. 12. Zemzemi N, Rodriguez B. Effects of L-type calcium channel and hERG block on the electrical activity of the human heart: a simulation study. Europace 2014.
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FOCUSED ISSUE: EDITORIAL
Computational cardiac electrophysiology is moving towards translation medicine Stefano Severi1*, Blanca Rodriguez2, and Antonio Zaza 3 1 Department of Electrical, Electronic and Information Engineering ‘Guglielmo Marconi’, University of Bologna, Via Venezia 52, 47023 Cesena, Italy; 2Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK; and 3Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2–4, 20126 Milano, Italy
computational approaches could be used and what is their expected value in this area. With regard to diagnostic tools, two papers are focused on the use of noninvasive electroanatomical imaging to assess conduction disorders. Seger et al.6 apply this approach to assess epi- and endocardial ventricular activation during cardiac resynchronization therapy. Their tool may be useful to locate the area of latest ventricular activation, thus helping in the optimization of lead placement. Van Dam et al.7 propose a noninvasive imaging tool for the early recognition of bundle branch blocks during transcatheter aortic valve implantation. This is essentially a feasibility study, showing how the location of conduction disorders can be precisely defined by advanced computerassisted imaging. Pervolaraki et al.8 developed a computational model of propagation during normal sinus rhythm in the foetal human heart. Although awaiting validation, the study constitutes a first attempt to model this novel problem and provides a basis for computational interpretation of the response of the foetal electrocardiogram (ECG) under disease states and pharmacological interventions. The ability of septal pacing to capture AF has been investigated by Rusu et al.9 They found that an AF substrate had a significant impact on the outcome of rapid pacing, thus increasing the information that can be extracted from capture protocols. Dependency on the AF substrate would also explain the high interindividual variability in the response to pacing. In a more theoretical study, Zaniboni and Cacciani10 adopt a novel 3D representation of cardiac action potential to compactly visualize and analyse the dynamical properties of human cellular ventricular repolarization. This representation identifies an auto-regenerativerepolarization-phase, suitable to estimate repolarization stability, and its response to drugs, in single and coupled myocytes. The concept is relevant to the in silico prediction of proarrhythmia. Together, the two parts of this Focused Issue on Computational Cardiac Electrophysiology offer a comprehensive overview of the state of the art of computational approaches for studies of the mechanisms, diagnosis, and treatment of arrhythmogenesis. Moreover, two additional papers will be published in a following issue of EP-Europace. The first one is a computational study on the effects of b-blockers on AF, in which Kharche et al.11 show that AF
* Corresponding author. Tel: +39 0547 339127; fax: +39 0547 339114. E-mail address: [email protected] Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2014. For permissions please email: [email protected].
Downloaded from by guest on November 20, 2015
In the present Issue of EP-Europace, we publish the second part of the Focused Issue on ‘Computational Cardiac Electrophysiology’, which was previously introduced in March 2014.1 Whereas the first part featured contributions on the computational analysis of ‘arrhythmias mechanisms’, the present Issue mainly focuses on the descriptions of novel computational approaches for diagnosis and interventions in clinical arrhythmology. In this sense, although there are clearly many challenges that must still be overcome along the way, the articles in this issue show that Computational Cardiac Electrophysiology is moving towards Translational Medicine. With regard to the application of the computational approach to the antiarrhythmic therapies, Trayanova and Rantner2 review the insights provided by the three-dimensional (3D) computational models of defibrillation and of shock-induced arrhythmogenesis, including the description of a relevant attempt of clinical translation regarding the model-based prediction of the optimal ICD placement in paediatric and congenital heart defect patients. An original contribution also related to the understanding of arrhythmia induction and defibrillation is the study by Colli Franzone et al.3 on the spatial distribution of intracellular calcium (Cai) dynamics following premature stimulations. In agreement with recent experimental investigations, they found significant regions of Cai elevation located at the virtual cathode regions. Such spatial heterogeneity in Cai dynamics may feedback on membrane potential and play an important role in arrhythmia induction by programmed stimulation. Ravelli and Mase`4 review the state of the art of computational mapping in atrial fibrillation (AF). The experimental studies, the signal processing methods and the clinical studies focused on the analysis of rate and organization of AF are reviewed. They point out how the integration of signal-derived maps may guide the localization of critical sources and the planning of new target ablation strategies. In their work, Wis´niowska et al.5 review successes, issues, and challenges associated with the use of computer-based approaches for cardiac drug safety assessment, including pro-arrhythmia. The review covers a description of in vitro, in vivo, and in silico methods for cardiac drug assessment, and discusses the challenges and limitations associated with their combined use and their validation. The discussion is set to trigger further thoughts and discussions on how
704 suppression may involve a reduced propensity for maintenance of re-entrant excitation waves, as a consequence of ionic remodelling. In the second one, Zenzemi and Rodriguez12 present a multiscale framework for preclinical in silico drug testing and use it to investigate the simultaneous effect of L-type calcium channel and hERG block on human ventricular electrophysiology from ionic to ECG level. We would like to thank all the authors for their contributions, which have enabled the illustration of the wide range of approaches and applications in Computational Cardiac Electrophysiology. We would also like to extend the invitation and encourage future submissions of high-quality papers in Computational Cardiac Electrophysiology to EP-Europace.
References 1. Severi S, Rodriguez B, Zaza A. Computational cardiac electrophysiology is ready for prime time. Europace 2014;16:382–383. 2. Trayanova NA, Rantner LJ. New insights into defibrillation of the heart from realistic simulation studies. Europace 2014;16:705–13. 3. Colli Franzone P, Pavarino LF, Scacchi S. Effects of premature anodal stimulations on cardiac transmembrane potential and intracellular calcium distributions computed by anisotropic Bidomain models. Europace 2014;16:736 – 42.
Editorial
4. Ravelli F, Mase` M. Computational mapping in atrial fibrillation: how the integration of signal-derived maps may guide the localization of critical sources. Europace 2014;16: 714 –23. 5. Wis´niowska B, Mendyk A, Fijorek K, Polak S. Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges.. Europace 2014;16:724 –35. 6. Seger M, Hanser F, Dichtl W, Stuehlinger M, Hintringer F, Trieb T et al. Non-invasive imaging of cardiac electrophysiology in a cardiac resynchronization therapy defibrillator patient with a quadripolar left ventricular lead. Europace 2014;16:743 –49. 7. van Dam PM, Proniewska K, Maugenest A-M, van Mieghem NM, Mann AC, de Jaegere PPT et al. Electrocardiographic imaging-based recognition of possible induced bundle branch blocks during transcatheter aortic valve implantations. Europace 2014;16:750 – 7. 8. Pervolaraki E, Hodgson S, Holden AV, Benson AP. Towards computational modelling of the human foetal electrocardiogram: normal sinus rhythm and congenital heart block. Europace 2014;16:758–66. 9. Rusu A, Jacquemet V, Vesin J-M, Virag N. Influence of atrial substrate on local capture induced by rapid pacing of atrial fibrillation. Europace 2014;16:766 –73. 10. Zaniboni M, Cacciani F. Instantaneous current–voltage relationships during the course of the human cardiac ventricular action potential: new computational insights into repolarization dynamics. Europace 2014;16:774–84. 11. Kharche SR, Stary T, Colman MA, Biktasheva I, Workman AJ, Rankin A et al. Effects of human atrial ionic remodelling by b-blocker therapy on mechanisms of AF: a computer simulation. Europace 2014. 12. Zemzemi N, Rodriguez B. Effects of L-type calcium channel and hERG block on the electrical activity of the human heart: a simulation study. Europace 2014.
Downloaded from by guest on November 20, 2015
