Publications

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Publication about openCARP

Plank, G., Loewe A., Neic. A et al. (2021). The openCARP simulation environment for cardiac electrophysiology. Computer Methods and Programs in Biomedicine 2021;208:106223. doi:10.1016/j.cmpb.2021.106223

The list below is autogenerated from the works citing this work. Not all of them necessarily used openCARP directly.

Publications using openCARP

1. Bifulco, S. F., Scott, G. D., Sarairah, S., Birjandian, Z., Roney, C. H., Niederer, S. A., Mahnkopf, C., Kuhnlein, P., Mitlacher, M., Tirschwell, D., Longstreth, W., Akoum, N., and Boyle, P. M., Computational modeling identifies embolic stroke of undetermined source patients with potential arrhythmic substrate. eLife 2021;10: doi:10.7554/elife.64213.

2. Amsaleg, A., Sánchez, J., Mikut, R., and Loewe, A., Characterization of the pace-and-drive capacity of the human sinoatrial node: A 3D in silico study. bioRxiv 2022; doi:10.1101/2022.06.03.494644.

3. Azzolin, L., Eichenlaub, M., Nagel, C., Nairn, D., Sanchez, J., Unger, L., Doessel, O., Jadidi, A., and Loewe, A., AugmentA: Patient-specific augmented atrial model generation tool. medRxiv 2022; doi:10.1101/2022.02.13.22270835.

4. Bach, F., Klar, J., Loewe, A., Sánchez, J., Seemann, G., Huang, Y.-L., and Ulrich, R., The openCARP cde–concept for and implementation of a sustainable collaborative development environment for research software. arXiv preprint arXiv:2201.04434 2022a;

5. Bach, F., Klar, J., Loewe, A., Sánchez, J., Seemann, G., Huang, Y.-L., and Ulrich, R., The openCARP CDE: Concept for and implementation of a sustainable collaborativedevelopment environment for research software. Bausteine Forschungsdatenmanagement 2022b;2022:64–84. doi:10.17192/bfdm.2022.1.8368.

6. Blackwell, D. J., Faggioni, M., Wleklinski, M. J., Gomez-Hurtado, N., Venkataraman, R., Gibbs, C. E., Baudenbacher, F. J., Gong, S., Fishman, G. I., Boyle, P. M., and others, The purkinje–myocardial junction is the anatomic origin of ventricular arrhythmia in cpvt. JCI insight 2022;7: doi:10.1172/jci.insight.151893.

7. Campos, F. O., Neic, A., Costa, C. M., Whitaker, J., O’Neill, M., Razavi, R., Rinaldi, C. A., Niederer, S. A., Plank, G., Bishop, M. J., and others, An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias. Medical Image Analysis 2022;80:102483. doi:10.1016/j.media.2022.102483.

8. Coveney, S., Cantwell, C., and Roney, C., Atrial conduction velocity mapping: Clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate. Medical & Biological Engineering & Computing 2022a;1–16. doi:10.1007/s11517-022-02621-0.

9. Coveney, S., Roney, C. H., Corrado, C., Wilkinson, R. D., Oakley, J. E., Niederer, S. A., and Clayton, R. H., Calibrating cardiac electrophysiology models using latent gaussian processes on atrial manifolds. arXiv preprint arXiv:2206.03804 2022b;

10. Esmailie, F., Razavi, A., Yeats, B., Sivakumar, S. K., Chen, H., Samaee, M., Shah, I. A., Veneziani, A., Yadav, P., Thourani, V. H., and others, Biomechanics of transcatheter aortic valve replacement complications and computational predictive modeling. Structural Heart 2022;6:100032. doi:10.1016/j.shj.2022.100032.

11. Fuchsberger, J., Aigner, P., Niederer, S., Plank, G., Schima, H., Haase, G., and Karabelas, E., On the incorporation of obstacles in a fluid flow problem using a navier–stokes–brinkman penalization approach. Journal of Computational Science 2022;57:101506. doi:10.1016/j.jocs.2021.101506.

12. Geng, Z., Jin, L., Huang, Y., and Wu, X., Rate dependence of early afterdepolarizations in the his-purkinje system: A simulation study. Computer Methods and Programs in Biomedicine 2022;217:106665. doi:10.1016/j.cmpb.2022.106665.

13. Goette, A., Rickert, V., and Brandner, S., Simulatoren und simulatortraining in der interventionellen elektrophysiologie. Herzschrittmachertherapie+ Elektrophysiologie 2022;1–4. doi:10.1007/s00399-022-00882-8.

14. Hustad, K. G., and Cai, X., Resource-efficient use of modern processor architectures for numerically solving cardiac ionic cell models. Frontiers in Physiology 2022;956. doi:10.3389/fphys.2022.904648.

15. Jung, A., Gsell, M. A., Augustin, C. M., and Plank, G., An integrated workflow for building digital twins of cardiac electromechanics—a multi-fidelity approach for personalising active mechanics. Mathematics 2022;10:823. doi:10.3390/math10050823.

16. Karabelas, E., Gsell, M. A., Haase, G., Plank, G., and Augustin, C. M., An accurate, robust, and efficient finite element framework with applications to anisotropic, nearly and fully incompressible elasticity. Computer Methods in Applied Mechanics and Engineering 2022;394:114887. doi:10.1016/j.cma.2022.114887.

17. Klein, V. S., Modeling and measuring cardiac magnetostimulation. 2022;

18. Lee, C. H., Application of neural networks to predict patient-specific cellular parameters in computational cardiac models. 2022;

19. Nagel, C., Espinosa, C. B., Gillette, K., Gsell, M. A., Sánchez, J., Plank, G., Dössel, O., and Loewe, A., Comparison of propagation models and forward calculation methods on cellular, tissue and organ scale atrial electrophysiology. arXiv preprint arXiv:2203.07776 2022;

20. Patricio Sánchez Arciniegas, J., A multiscale in silico study to characterize the atrial electrical activity of patients with atrial fibrillation: A translational study to guide ablation therapy. KIT Scientific Publishing 2022 doi:10.4995/thesis/10251/171456.

21. Rappel, W.-J., The physics of heart rhythm disorders. Physics Reports 2022;978:1–45. doi:10.1016/j.physrep.2022.06.003.

22. Rodrı́guez-Padilla, J., Petras, A., Magat, J., Bayer, J., Bihan-Poudec, Y., El Hamrani, D., Ramlugun, G., Neic, A., Augustin, C. M., Vaillant, F., and others, Impact of intraventricular septal fiber orientation on cardiac electromechanical function. American Journal of Physiology-Heart and Circulatory Physiology 2022a;322:H936–H952. doi:10.1152/ajpheart.00050.2022.

23. Rodrı́guez-Padilla, J., Petras, A., Magat, J., Bayer, J., Bihan-Poudec, Y., El Hamrani, D., Ramlugun, G., Neic, A., Augustin, C. M., Vaillant, F., and others, Integrative cardiovascular physiology and pathophysiology: Impact of intraventricular septal fiber orientation on cardiac electromechanical function. American Journal of Physiology-Heart and Circulatory Physiology 2022b;322:H936.

24. Ryzhii, M., and Ryzhii, E., Pacemaking function of two simplified cell models. PloS one 2022;17:e0257935. doi:10.1101/2021.09.14.460406.

25. Sánchez, J., and Loewe, A., A review of healthy and fibrotic myocardium microstructure modeling and corresponding intracardiac electrograms. Frontiers in Physiology 2022;916. doi:10.3389/fphys.2022.908069.

26. Serra, D., Romero, P., Garcia-Fernandez, I., Lozano, M., Liberos, A., Rodrigo, M., Bueno-Orovio, A., Berruezo, A., and Sebastian, R., An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility. Mathematics 2022;10:1293. doi:10.3390/math10081293.

27. Sutanto, H., and Heijman, J., Integrative computational modeling of cardiomyocyte calcium handling and cardiac arrhythmias: Current status and future challenges. Cells 2022;11:1090. doi:10.3390/cells11071090.

28. Azzolin, L., Nagel, C., Nairn, D., Sánchez, J., Zheng, T., Eichenlaub, M., Jadidi, A., Dössel, O., and Loewe, A., Automated framework for the augmentation of missing anatomical structures and generation of personalized atrial models from clinical data. 2021a in 2021 Computing in Cardiology (Cinc) (IEEE), 1–4. doi:10.23919/cinc53138.2021.9662846.

29. Azzolin, L., Schuler, S., Dössel, O., and Loewe, A., A reproducible protocol to assess arrhythmia vulnerability in silico: Pacing at the end of the effective refractory period. Frontiers in physiology 2021b;12:656411. doi:10.1101/2021.01.21.21250205.

30. Beach, M., Sim, I., Mehta, A., Kotadia, I., O’Hare, D., Whitaker, J., Solis-Lemus, J. A., Razeghi, O., Chiribiri, A., O’Neill, M., Williams, S., Niederer, S. A., and Roney, C. H., Using the universal atrial coordinate system for mri and electroanatomic data registration in patient-specific left atrial model construction and simulation. 2021 in Functional Imaging and Modeling of the Heart, eds. D. B. Ennis, L. E. Perotti, and V. Y. Wang (Cham: Springer International Publishing), 629–638.

31. Coveney, S., Corrado, C., Oakley, J. E., Wilkinson, R. D., Niederer, S. A., and Clayton, R. H., Bayesian calibration of electrophysiology models using restitution curve emulators. Frontiers in Physiology 2021;1120. doi:10.3389/fphys.2021.693015.

32. Dössel, O., Luongo, G., Nagel, C., and Loewe, A., Computer modeling of the heart for ecg interpretation—a review. Hearts 2021;2:350–368. doi:10.3390/hearts2030028.

33. Luongo, G., Azzolin, L., Schuler, S., Rivolta, M. W., Almeida, T. P., Martı́nez, J. P., Soriano, D. C., Luik, A., Müller-Edenborn, B., Jadidi, A., and others, Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ecg. Cardiovascular digital health journal 2021;2:126–136. doi:10.1016/j.cvdhj.2021.03.002.

34. Maleckar, M. M., Myklebust, L., Uv, J., Florvaag, P. M., Strøm, V., Glinge, C., Jabbari, R., Vejlstrup, N., Engstrøm, T., Ahtarovski, K., and others, Combined in-silico and machine learning approaches toward predicting arrhythmic risk in post-infarction patients. Frontiers in physiology 2021;12: doi:10.3389/fphys.2021.745349.

35. Monbaliu, R., A meandering spiral due to early afterdepolarizations as possible mechanism of torsade de pointes. 2021;

36. Moreno, A., Walton, R. D., Bernus, O., Vigmond, E. J., and Bayer, J. D., Low-energy, single-pulse surface stimulation defibrillates large mammalian ventricles. Heart Rhythm 2021; doi:10.1016/j.hrthm.2021.10.006.

37. Nagel, C., Schuler, S., Dössel, O., and Loewe, A., A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ecg simulations. Medical Image Analysis 2021;74:102210. doi:10.1016/j.media.2021.102210.

38. Ochs, A. R., Karathanos, T. V., Trayanova, N. A., and Boyle, P. M., Optogenetic stimulation using anion channelrhodopsin (GtACR1) facilitates termination of reentrant arrhythmias with low light energy requirements: A computational study. Frontiers in Physiology 2021;12: doi:10.3389/fphys.2021.718622.

39. Sánchez, J., Luongo, G., Nothstein, M., Unger, L. A., Saiz, J., Trenor, B., Luik, A., Dössel, O., and Loewe, A., Using machine learning to characterize atrial fibrotic substrate from intracardiac signals with a hybrid in silico and in vivo dataset. Frontiers in Physiology 2021a;1000. doi:10.3389/fphys.2021.699291.

40. Sánchez, J., Trenor, B., Saiz, J., Dössel, O., and Loewe, A., Fibrotic remodeling during persistent atrial fibrillation: In silico investigation of the role of calcium for human atrial myofibroblast electrophysiology. Cells 2021b;10:2852. doi:10.3390/cells10112852.

41. Schicketanz, L., Unger, L. A., Sánchez, J., Dössel, O., and Loewe, A., Separating atrial near fields and atrial far fields in simulated intra-atrial electrograms. Current Directions in Biomedical Engineering 2021;7:175–178. doi:10.1515/cdbme-2021-2045.

42. Tong, L., Zhao, C., Fu, Z., Dong, R., Wu, Z., Wang, Z., Zhang, N., Wang, X., Cao, B., Sun, Y., and others, Preliminary study: Learning the impact of simulation time on reentry location and morphology induced by personalized cardiac modeling. Frontiers in Physiology 2021;2335. doi:10.3389/fphys.2021.733500.

43. Azzolin, L., Luongo, G., Rocher, S., Saiz, J., Doessel, O., and Loewe, A., Influence of gradient and smoothness of atrial wall thickness on initiation and maintenance of atrial fibrillation. 2020 in 47th Computing in Cardiology Conference (CinC) (Computing in Cardiology). doi:10.22489/cinc.2020.261.

44. Luongo, G., Azzolin, L., Rivolta, M. W., Almeida, T. P. de, Martı́nez, J. P., Soriano, D. C., Doessel, O., Sassi, R., Laguna, P., and Loewe, A., Machine learning to find areas of rotors sustaining atrial fibrillation from the ECG. 2020a in 47th Computing in Cardiology Conference (CinC) (Computing in Cardiology). doi:10.22489/cinc.2020.181.

45. Luongo, G., Azzolin, L., Rivolta, M. W., Sassi, R., Martinez, J. P., Laguna, P., Dossel, O., and Loewe, A., Non-invasive identification of atrial fibrillation driver location using the 12-lead ECG: Pulmonary vein rotors vs. Other locations. 2020b in 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (IEEE). doi:10.1109/embc44109.2020.9176135.

46. Sánchez, J., Nothstein, M., Neic, A., Huang, Y.-L., Prassl, A. J., Klar, J., Ulrich, R., Bach, F., Zschumme, P., Selzer, M., Plank, G., Vigmond, E., Seemann, G., and Loewe, A., openCARP: An open sustainable framework for in-silico cardiac electrophysiology research. 2020 in 47th Computing in Cardiology Conference (CinC) (Computing in Cardiology). doi:10.22489/cinc.2020.111.

47. Dıaz, P. M., Azzolin, L., Arciniégas, J. P. S., Nagel, C., Dössel, O., and Loewe, A., Influence of the right atrium for arrhythmia vulnerability: Geometry inference using a statistical shape model.

48. Espinosa, C. B., Skupien, N., Kachel, G., Dössel, O., and Loewe, A., Influence of wave-front and atrial tissue properties on eikonal model simulations.

49. Ogbomo-Harmitt, S., Qureshi, A., King, A., and Aslanidi, O., Impact of fibrosis border zone characterisation on fibrosis-substrate isolation ablation outcome for atrial fibrillation.

50. Trenor, B., Luik, A., Dossel, O., and Loewe, A., Jorge sánchez1, 2, giorgio luongo1, mark nothstein1, laura unger1, javier saiz2.

Publications using CARP/carpentry

1. Gillette, K., Gsell, M. A. F., Prassl, A. J., Karabelas, E., Reiter, U., Reiter, G., Grandits, T., Payer, C., Štern, D., Urschler, M., Bayer, J. D., Augustin, C. M., Neic, A., Pock, T., et al., A framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs. Medical Image Analysis 2021;71:102080. doi:10.1016/j.media.2021.102080.

2. Good, W. W., Zenger, B., Bergquist, J. A., Rupp, L. C., Gillette, K. K., Gsell, M. A. F., Plank, G., and MacLeod, R. S., Quantifying the spatiotemporal influence of acute myocardial ischemia on volumetric conduction velocity. Journal of Electrocardiology 2021;66:86–94. doi:10.1016/j.jelectrocard.2021.03.004.

3. Boyle, P. M., Yu, J., Klimas, A., Williams, J. C., Trayanova, N. A., and Entcheva, E., OptoGap is an optogenetics-enabled assay for quantification of cellcell coupling in multicellular cardiac tissue. Scientific Reports 2021;11: doi:10.1038/s41598-021-88573-1.

4. Rodero, C., Strocchi, M., Marciniak, M., Longobardi, S., Whitaker, J., O’Neill, M. D., Gillette, K., Augustin, C., Plank, G., Vigmond, E. J., Lamata, P., and Niederer, S. A., Linking statistical shape models and simulated function in the healthy adult human heart. PLOS Computational Biology 2021;17:e1008851. doi:10.1371/journal.pcbi.1008851.

5. Yu, J. K., Liang, J. A., Franceschi, W. H., Huang, Q., Pashakhanloo, F., Sung, E., Boyle, P. M., and Trayanova, N. A., Assessment of arrhythmia mechanism and burden of the infarcted ventricles following remuscularization with pluripotent stem cell-derived cardiomyocyte patches using patient-derived models. Cardiovascular Research 2021; doi:10.1093/cvr/cvab140.

6. Campos, F. O., Orini, M., Arnold, R., Whitaker, J., ONeill, M., Razavi, R., Plank, G., Hanson, B., Porter, B., Rinaldi, C. A., Gill, J., Lambiase, P. D., Taggart, P., and Bishop, M. J., Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling. Computers in Biology and Medicine 2021;130:104214. doi:10.1016/j.compbiomed.2021.104214.

7. Razeghi, O., Heinrich, M., Fastl, T. E., Corrado, C., Karim, R., Vecchi, A. D., Banks, T., Donnelly, P., Behar, J. M., Gould, J., Rajani, R., Rinaldi, C. A., and Niederer, S., Hyperparameter optimisation and validation of registration algorithms for measuring regional ventricular deformation using retrospective gated computed tomography images. Scientific Reports 2021;11: doi:10.1038/s41598-021-84935-x.

8. Balaban, G., Halliday, B. P., Porter, B., Bai, W., Nygåard, S., Owen, R., Hatipoglu, S., Ferreira, N. D., Izgi, C., Tayal, U., Corden, B., Ware, J., Pennell, D. J., Rueckert, D., et al., Late-gadolinium enhancement interface area and electrophysiological simulations predict arrhythmic events in patients with nonischemic dilated cardiomyopathy. JACC: Clinical Electrophysiology 2021;7:238–249. doi:10.1016/j.jacep.2020.08.036.

9. Rivaud, M. R., Bayer, J. D., Cluitmans, M., Waal, J. van der, Bear, L. R., Boukens, B. J., Belterman, C., Gottlieb, L., Vaillant, F., Abell, E., Dubois, R., Meijborg, V. M. F., and Coronel, R., Critical repolarization gradients determine the induction of reentry-based torsades de pointes arrhythmia in models of long QT syndrome. Heart Rhythm 2021;18:278–287. doi:10.1016/j.hrthm.2020.09.020.

10. Whitaker, J., Karády, J., Karim, R., Tobon-Gomez, C., Fastl, T., Razeghi, O., ONeill, L., Decroocq, M., Williams, S., Corrado, C., Mukherjee, R. K., Sim, I., OHare, D., Kotadia, I., et al., Standardised computed tomographic assessment of left atrial morphology and tissue thickness in humans. IJC Heart & Vasculature 2021;32:100694. doi:10.1016/j.ijcha.2020.100694.

11. Corrado, C., Williams, S., Roney, C., Plank, G., O’Neill, M., and Niederer, S., Using machine learning to identify local cellular properties that support re-entrant activation in patient-specific models of atrial fibrillation. EP Europace 2021;23:i12–i20. doi:10.1093/europace/euaa386.

12. Rogers, A. J., Selvalingam, A., Alhusseini, M. I., Krummen, D. E., Corrado, C., Abuzaid, F., Baykaner, T., Meyer, C., Clopton, P., Giles, W., Bailis, P., Niederer, S., Wang, P. J., Rappel, W.-J., et al., Machine learned cellular phenotypes in cardiomyopathy predict sudden death. Circulation Research 2021;128:172–184. doi:10.1161/circresaha.120.317345.

13. Good, W., Zenger, B., Bergquist, J., Rupp, L., Gillette, K., Plank, G., and MacLeod, R., Quantifying the spatiotemporal influence of acute myocardial ischemia on volumetric conduction velocity. 2020 in 2020 Computing in Cardiology Conference (CinC) (Computing in Cardiology). doi:10.22489/cinc.2020.279.

14. Kotadia, I., Whitaker, J., Roney, C., Niederer, S., O’Neill, M., Bishop, M., and Wright, M., Anisotropic cardiac conduction. Arrhythmia & Electrophysiology Review 2020;9:202–210. doi:10.15420/aer.2020.04.

15. Rupp, L., Good, W., Bergquist, J., Zenger, B., Gillette, K., Plank, G., and MacLeod, R., Effect of myocardial fiber direction on epicardial activation patterns. 2020 in 2020 Computing in Cardiology Conference (CinC) (Computing in Cardiology). doi:10.22489/cinc.2020.399.

16. Balaban, G., Costa, C. M., Porter, B., Halliday, B., Rinaldi, C. A., Prasad, S., Plank, G., Ismail, T. F., and Bishop, M. J., 3D electrophysiological modeling of interstitial fibrosis networks and their role in ventricular arrhythmias in non-ischemic cardiomyopathy. IEEE Transactions on Biomedical Engineering 2020;67:3125–3133. doi:10.1109/tbme.2020.2976924.

17. Strocchi, M., Lee, A. W. C., Neic, A., Bouyssier, J., Gillette, K., Plank, G., Elliott, M. K., Gould, J., Behar, J. M., Sidhu, B., Mehta, V., Bishop, M. J., Vigmond, E. J., Rinaldi, C. A., et al., His-bundle and left bundle pacing with optimized atrioventricular delay achieve superior electrical synchrony over endocardial and epicardial pacing in left bundle branch block patients. Heart Rhythm 2020;17:1922–1929. doi:10.1016/j.hrthm.2020.06.028.

18. Corrado, C., Avezzù, A., Lee, A. W. C., Costa, C. M., Roney, C. H., Strocchi, M., Bishop, M., and Niederer, S. A., Using cardiac ionic cell models to interpret clinical data. WIREs Mechanisms of Disease 2020;13: doi:10.1002/wsbm.1508.

19. Grandits, T., Gillette, K., Neic, A., Bayer, J., Vigmond, E., Pock, T., and Plank, G., An inverse eikonal method for identifying ventricular activation sequences from epicardial activation maps. Journal of Computational Physics 2020;419:109700. doi:10.1016/j.jcp.2020.109700.

20. Monaci, S., Strocchi, M., Rodero, C., Gillette, K., Whitaker, J., Rajani, R., Rinaldi, C. A., ONeill, M., Plank, G., King, A., and Bishop, M. J., In-silico pace-mapping using a detailed whole torso model and implanted electronic device electrograms for more efficient ablation planning. Computers in Biology and Medicine 2020;125:104005. doi:10.1016/j.compbiomed.2020.104005.

21. Toth, G. G., Sasi, V., Franco, D., Prassl, A. J., Serafino, L. D., Ng, J. C. K., Szanto, G., Schneller, L., Ang, H. Y., Plank, G., Wijns, W., and Barbato, E., Double-kissing culotte technique for coronary bifurcation stenting. EuroIntervention 2020;16:e724–e733. doi:10.4244/eij-d-20-00130.

22. Swenson, D. J., Taepke, R. T., Blauer, J. J. E., Kwan, E., Ghafoori, E., Plank, G., Vigmond, E., MacLeod, R. S., DeGroot, P., and Ranjan, R., Direct comparison of a novel antitachycardia pacing algorithm against present methods using virtual patient modeling. Heart Rhythm 2020;17:1602–1608. doi:10.1016/j.hrthm.2020.05.009.

23. Costa, C. M., Neic, A., Gillette, K., Porter, B., Gould, J., Sidhu, B., Chen, Z., Elliott, M., Mehta, V., Plank, G., Rinaldi, C. A., Bishop, M. J., and Niederer, S. A., Left ventricular endocardial pacing is less arrhythmogenic than conventional epicardial pacing when pacing in proximity to scar. Heart Rhythm 2020;17:1262–1270. doi:10.1016/j.hrthm.2020.03.021.

24. Gaur, N., Ortega, F., Verkerk, A. O., Mengarelli, I., Krogh-Madsen, T., Christini, D. J., Coronel, R., and Vigmond, E. J., Validation of quantitative measure of repolarization reserve as a novel marker of drug induced proarrhythmia. Journal of Molecular and Cellular Cardiology 2020;145:122–132. doi:10.1016/j.yjmcc.2020.04.019.

25. Gemmell, P. M., Gillette, K., Balaban, G., Rajani, R., Vigmond, E. J., Plank, G., and Bishop, M. J., A computational investigation into rate-dependant vectorcardiogram changes due to specific fibrosis patterns in non-ischæmic dilated cardiomyopathy. Computers in Biology and Medicine 2020;123:103895. doi:10.1016/j.compbiomed.2020.103895.

26. Gould, J., Porter, B., Sidhu, B. S., Claridge, S., Chen, Z., Sieniewicz, B. J., Elliott, M., Mehta, V., Campos, F. O., Bishop, M. J., Costa, C. M., Niederer, S., Ganeshan, B., Razavi, R., et al., High mean entropy calculated from cardiac MRI texture analysis is associated with antitachycardia pacing failure. Pacing and Clinical Electrophysiology 2020;43:737–745. doi:10.1111/pace.13969.

27. Coveney, S., Corrado, C., Roney, C. H., O’Hare, D., Williams, S. E., O’Neill, M. D., Niederer, S. A., Clayton, R. H., Oakley, J. E., and Wilkinson, R. D., Gaussian process manifold interpolation for probabilistic atrial activation maps and uncertain conduction velocity. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2020;378:20190345. doi:10.1098/rsta.2019.0345.

28. Marx, L., Gsell, M. A. F., Rund, A., Caforio, F., Prassl, A. J., Toth-Gayor, G., Kuehne, T., Augustin, C. M., and Plank, G., Personalization of electro-mechanical models of the pressure-overloaded left ventricle: Fitting of windkessel-type afterload models. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2020;378:20190342. doi:10.1098/rsta.2019.0342.

29. Roney, C. H., Bendikas, R., Pashakhanloo, F., Corrado, C., Vigmond, E. J., McVeigh, E. R., Trayanova, N. A., and Niederer, S. A., Constructing a human atrial fibre atlas. Annals of Biomedical Engineering 2020;49:233–250. doi:10.1007/s10439-020-02525-w.

30. Niestrawska, J. A., Augustin, C. M., and Plank, G., Computational modeling of cardiac growth and remodeling in pressure overloaded heartsLinking microstructure to organ phenotype. Acta Biomaterialia 2020;106:34–53. doi:10.1016/j.actbio.2020.02.010.

31. Corral-Acero, J., Margara, F., Marciniak, M., Rodero, C., Loncaric, F., Feng, Y., Gilbert, A., Fernandes, J. F., Bukhari, H. A., Wajdan, A., Martinez, M. V., Santos, M. S., Shamohammdi, M., Luo, H., et al., The “digital twin” to enable the vision of precision cardiology. European Heart Journal 2020;41:4556–4564. doi:10.1093/eurheartj/ehaa159.

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104. Jackson, N., Gizurarson, S., Viswanathan, K., King, B., Massé, S., Kusha, M., Porta-Sanchez, A., Jacob, J. R., Khan, F., Das, M., Ha, A. C. T., Pashaei, A., Vigmond, E., Downar, E., et al., Decrement evoked potential mapping. Circulation: Arrhythmia and Electrophysiology 2015;8:1433–1442. doi:10.1161/circep.115.003083.

105. Land, S., Gurev, V., Arens, S., Augustin, C. M., Baron, L., Blake, R., Bradley, C., Castro, S., Crozier, A., Favino, M., Fastl, T. E., Fritz, T., Gao, H., Gizzi, A., et al., Verification of cardiac mechanics software: Benchmark problems and solutions for testing active and passive material behaviour. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 2015;471:20150641. doi:10.1098/rspa.2015.0641.

106. Boyle, P. M., Karathanos, T. V., Entcheva, E., and Trayanova, N. A., Computational modeling of cardiac optogenetics: Methodology overview & review of findings from simulations. Computers in Biology and Medicine 2015;65:200–208. doi:10.1016/j.compbiomed.2015.04.036.

107. Hyde, E. R., Behar, J. M., Claridge, S., Jackson, T., Lee, A. W. C., Remme, E. W., Sohal, M., Plank, G., Razavi, R., Rinaldi, C. A., and Niederer, S. A., Beneficial effect on cardiac resynchronization from left ventricular endocardial pacing is mediated by early access to high conduction velocity tissue. Circulation: Arrhythmia and Electrophysiology 2015;8:1164–1172. doi:10.1161/circep.115.002677.

108. Chamakuri, N., Kunisch, K., and Plank, G., PDE constrained optimization of electrical defibrillation in a 3D ventricular slice geometry. International Journal for Numerical Methods in Biomedical Engineering 2015;32:e02742. doi:10.1002/cnm.2742.

109. Connolly, A., Trew, M. L., Smaill, B. H., Plank, G., and Bishop, M. J., Local gradients in electrotonic loading modulate the local effective refractory period: Implications for arrhythmogenesis in the infarct border zone. IEEE Transactions on Biomedical Engineering 2015;62:2251–2259. doi:10.1109/tbme.2015.2421296.

110. Bernus, O., and Vigmond, E., Asymptotic wave propagation in excitable media. Physical Review E 2015;92: doi:10.1103/physreve.92.010901.

111. Boukens, B. J., Sulkin, M. S., Gloschat, C. R., Ng, F. S., Vigmond, E. J., and Efimov, I. R., Transmural APD gradient synchronizes repolarization in the human left ventricular wall. Cardiovascular Research 2015;108:188–196. doi:10.1093/cvr/cvv202.

112. Child, N., Bishop, M. J., Hanson, B., Coronel, R., Opthof, T., Boukens, B. J., Walton, R. D., Efimov, I. R., Bostock, J., Hill, Y., Rinaldi, C. A., Razavi, R., Gill, J., and Taggart, P., An activation-repolarization time metric to predict localized regions of high susceptibility to reentry. Heart Rhythm 2015;12:1644–1653. doi:10.1016/j.hrthm.2015.04.013.

113. Campos, F. O., Shiferaw, Y., Prassl, A. J., Boyle, P. M., Vigmond, E. J., and Plank, G., Stochastic spontaneous calcium release events trigger premature ventricular complexes by overcoming electrotonic load. Cardiovascular Research 2015;107:175–183. doi:10.1093/cvr/cvv149.

114. Bishop, M., Rajani, R., Plank, G., Gaddum, N., Carr-White, G., Wright, M., ONeill, M., and Niederer, S., Three-dimensional atrial wall thickness maps to inform catheter ablation procedures for atrial fibrillation. Europace 2015;18:376–383. doi:10.1093/europace/euv073.

115. Pashaei, A., Bayer, J., Meillet, V., Dubois, R., and Vigmond, E., Computation and projection of spiral wave trajectories during atrial fibrillation. Cardiac Electrophysiology Clinics 2015;7:37–47. doi:10.1016/j.ccep.2014.11.001.

116. McDowell, K. S., Zahid, S., Vadakkumpadan, F., Blauer, J., MacLeod, R. S., and Trayanova, N. A., Virtual electrophysiological study of atrial fibrillation in fibrotic remodeling. PLOS ONE 2015;10:e0117110. doi:10.1371/journal.pone.0117110.

117. Chang, K. C., Bayer, J. D., and Trayanova, N. A., Disrupted calcium release as a mechanism for atrial alternans associated with human atrial fibrillation. PLoS Computational Biology 2014;10:e1004011. doi:10.1371/journal.pcbi.1004011.

118. Trayanova, N. A., Boyle, P. M., Arevalo, H. J., and Zahid, S., Exploring susceptibility to atrial and ventricular arrhythmias resulting from remodeling of the passive electrical properties in the heart: A simulation approach. Frontiers in Physiology 2014;5: doi:10.3389/fphys.2014.00435.

119. Bishop, M. J., Connolly, A., and Plank, G., Structural heterogeneity modulates effective refractory period: A mechanism of focal arrhythmia initiation. PLoS ONE 2014;9:e109754. doi:10.1371/journal.pone.0109754.

120. Karathanos, T. V., Boyle, P. M., and Trayanova, N. A., Optogenetics-enabled dynamic modulation of action potential duration in atrial tissue: Feasibility of a novel therapeutic approach. Europace 2014;16:iv69–iv76. doi:10.1093/europace/euu250.

121. Labarthe, S., Bayer, J., Coudiere, Y., Henry, J., Cochet, H., Jais, P., and Vigmond, E., A bilayer model of human atria: Mathematical background, construction, and assessment. Europace 2014;16:iv21–iv29. doi:10.1093/europace/euu256.

122. Kaur, J., Nygren, A., and Vigmond, E. J., Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: Application of a multi-objective parallel genetic algorithm. PLoS ONE 2014;9:e107984. doi:10.1371/journal.pone.0107984.

123. Walton, R. D., Martinez, M. E., Bishop, M. J., Hocini, M., Haïssaguerre, M., Plank, G., Bernus, O., and Vigmond, E. J., Influence of the purkinje-muscle junction on transmural repolarization heterogeneity. Cardiovascular Research 2014;103:629–640. doi:10.1093/cvr/cvu165.

124. BLAUER, J. J. E., SWENSON, D., HIGUCHI, K., PLANK, G., RANJAN, R., MARROUCHE, N., and MACLEOD, R. S., Sensitivity and specificity of substrate mapping: An in silico framework for the evaluation of electroanatomical substrate mapping strategies. Journal of Cardiovascular Electrophysiology 2014;25:774–780. doi:10.1111/jce.12444.

125. Costa, C. M., Campos, F. O., Prassl, A. J., Santos, R. W. dos, Sanchez-Quintana, D., Ahammer, H., Hofer, E., and Plank, G., An efficient finite element approach for modeling fibrotic clefts in the heart. IEEE Transactions on Biomedical Engineering 2014;61:900–910. doi:10.1109/tbme.2013.2292320.

126. Behradfar, E., Nygren, A., and Vigmond, E. J., The role of purkinje-myocardial coupling during ventricular arrhythmia: A modeling study. PLoS ONE 2014;9:e88000. doi:10.1371/journal.pone.0088000.

127. Zamiri, N., Massé, S., Ramadeen, A., Kusha, M., Hu, X., Azam, M. A., Liu, J., Lai, P. F. H., Vigmond, E. J., Boyle, P. M., Behradfar, E., Al-Hesayen, A., Waxman, M. B., Backx, P., et al., Dantrolene improves survival after ventricular fibrillation by mitigating impaired calcium handling in animal models. Circulation 2014;129:875–885. doi:10.1161/circulationaha.113.005443.

128. Zhou, L., Solhjoo, S., Millare, B., Plank, G., Abraham, M. R., Cortassa, S., Trayanova, N., and O’Rourke, B., Effects of regional mitochondrial depolarization on electrical propagation. Circulation: Arrhythmia and Electrophysiology 2014;7:143–151. doi:10.1161/circep.113.000600.

129. Boyle, P. M., Park, C. J., Arevalo, H. J., Vigmond, E. J., and Trayanova, N. A., Sodium current reduction unmasks a structure-dependent substrate for arrhythmogenesis in the normal ventricles. PLoS ONE 2014;9:e86947. doi:10.1371/journal.pone.0086947.

130. Ringenberg, J., Deo, M., Filgueiras-Rama, D., Pizarro, G., Ibañez, B., Peinado, R., Trayanova, N., Miller, M., Merino, J. I., Berenfeld, O., and Devabhaktuni, V., Corrigendum to “Effects of fibrosis morphology on reentrant ventricular tachycardia inducibility and simulation fidelity in patient-derived models”. Clinical Medicine Insights: Cardiology 2014;8s1:CMC.S22840. doi:10.4137/cmc.s22840.

131. Boyle, P. M., Entcheva, E., and Trayanova, N. A., See the light: Can optogenetics restore healthy heartbeats? And, if it can, is it really worth the effort? Expert Review of Cardiovascular Therapy 2013;12:17–20. doi:10.1586/14779072.2014.864951.

132. Trayanova, N. A., and Boyle, P. M., Advances in modeling ventricular arrhythmias: From mechanisms to the clinic. Wiley Interdisciplinary Reviews: Systems Biology and Medicine 2013;6:209–224. doi:10.1002/wsbm.1256.

133. Chamakuri, N., Kunisch, K., and Plank, G., On boundary stimulation and optimal boundary control of the bidomain equations. Mathematical Biosciences 2013;245:206–215. doi:10.1016/j.mbs.2013.07.004.

134. Vigmond, E. J., Kimber, S., Suzuki, G., Faris, P., and Leon, L. J., Defibrillation success is not associated with near field electrogram complexity or shock timing. Canadian Journal of Cardiology 2013;29:1126–1133. doi:10.1016/j.cjca.2012.11.034.

135. Ashikaga, H., Arevalo, H., Vadakkumpadan, F., Blake, R. C., Bayer, J. D., Nazarian, S., Zviman, M. M., Tandri, H., Berger, R. D., Calkins, H., Herzka, D. A., Trayanova, N. A., and Halperin, H. R., Feasibility of image-based simulation to estimate ablation target in human ventricular arrhythmia. Heart Rhythm 2013;10:1109–1116. doi:10.1016/j.hrthm.2013.04.015.

136. Kelly, A., Ghouri, I. A., Kemi, O. J., Bishop, M. J., Bernus, O., Fenton, F. H., Myles, R. C., Burton, F. L., and Smith, G. L., Subepicardial action potential characteristics are a function of depth and activation sequence in isolated rabbit hearts. Circulation: Arrhythmia and Electrophysiology 2013;6:809–817. doi:10.1161/circep.113.000334.

137. Arevalo, H., Plank, G., Helm, P., Halperin, H., and Trayanova, N., Tachycardia in post-infarction hearts: Insights from 3D image-based ventricular models. PLoS ONE 2013;8:e68872. doi:10.1371/journal.pone.0068872.

138. Eriksson, T. S. E., Prassl, A. J., Plank, G., and Holzapfel, G. A., Modeling the dispersion in electromechanically coupled myocardium. International Journal for Numerical Methods in Biomedical Engineering 2013;29:1267–1284. doi:10.1002/cnm.2575.

139. McDowell, K. S., Vadakkumpadan, F., Blake, R., Blauer, J., Plank, G., MacLeod, R. S., and Trayanova, N. A., Mechanistic inquiry into the role of tissue remodeling in fibrotic lesions in human atrial fibrillation. Biophysical Journal 2013;104:2764–2773. doi:10.1016/j.bpj.2013.05.025.

140. Bishop, M. J., Vigmond, E. J., and Plank, G., The functional role of electrophysiological heterogeneity in the rabbit ventricle during rapid pacing and arrhythmias. American Journal of Physiology-Heart and Circulatory Physiology 2013;304:H1240–H1252. doi:10.1152/ajpheart.00894.2012.

141. Hu, Y., Gurev, V., Constantino, J., Bayer, J. D., and Trayanova, N. A., Effects of mechano-electric feedback on scroll wave stability in human ventricular fibrillation. PLoS ONE 2013;8:e60287. doi:10.1371/journal.pone.0060287.

142. Satriano, A., Bellini, C., Vigmond, E. J., and Martino, E. S. D., A feature-based morphing methodology for computationally modeled biological structures applied to left atrial fiber directions. Journal of Biomechanical Engineering 2013;135: doi:10.1115/1.4023369.

143. Augustin, C. M., and Plank, G., Simulating the mechanics of myocardial tissue using strongly scalable parallel algorithms. Biomedical Engineering / Biomedizinische Technik 2013; doi:10.1515/bmt-2013-4322.

144. Campos, F. O., Shiferaw, Y., and Plank, G., Tissue structure and ca2$\mathplus$-mediated ectopic beats. Biomedical Engineering / Biomedizinische Technik 2013; doi:10.1515/bmt-2013-4320.

145. Krummen, D. E., Bayer, J. D., Ho, J., Ho, G., Smetak, M. R., Clopton, P., Trayanova, N. A., and Narayan, S. M., Mechanisms of human atrial fibrillation initiation. Circulation: Arrhythmia and Electrophysiology 2012;5:1149–1159. doi:10.1161/circep.111.969022.

146. McDowell, K. S., Vadakkumpadan, F., Blake, R., Blauer, J., Plank, G., MacLeod, R. S., and Trayanova, N. A., Methodology for patient-specific modeling of atrial fibrosis as a substrate for atrial fibrillation. Journal of Electrocardiology 2012;45:640–645. doi:10.1016/j.jelectrocard.2012.08.005.

147. Binder, J. S., Weidemann, F., Schoser, B., Niemann, M., Machann, W., Beer, M., Plank, G., Schmidt, A., Bisping, E., Poparic, I., Lafer, I., Stojakovic, T., Quasthoff, S., Vincent, J. B., et al., Spongious hypertrophic cardiomyopathy in patients with mutations in the four-and-a-half LIM domain 1 gene. Circulation: Cardiovascular Genetics 2012;5:490–502. doi:10.1161/circgenetics.111.962332.

148. Trayanova, N. A., OHara, T., Bayer, J. D., Boyle, P. M., McDowell, K. S., Constantino, J., Arevalo, H. J., Hu, Y., and Vadakkumpadan, F., Computational cardiology: How computer simulations could be used to develop new therapies and advance existing ones. Europace 2012;14:v82–v89. doi:10.1093/europace/eus277.

149. Bishop, M. J., and Plank, G., The role of fine-scale anatomical structure in the dynamics of reentry in computational models of the rabbit ventricles. The Journal of Physiology 2012;590:4515–4535. doi:10.1113/jphysiol.2012.229062.

150. Niederer, S. A., Lamata, P., Plank, G., Chinchapatnam, P., Ginks, M., Rhode, K., Rinaldi, C. A., Razavi, R., and Smith, N. P., Analyses of the redistribution of work following cardiac resynchronisation therapy in a patient specific model. PLoS ONE 2012;7:e43504. doi:10.1371/journal.pone.0043504.

151. Nagaiah, C., Kunisch, K., and Plank, G., Optimal control approach to termination of re-entry waves in cardiac electrophysiology. Journal of Mathematical Biology 2012;67:359–388. doi:10.1007/s00285-012-0557-2.

152. Rantner, L. J., Arevalo, H. J., Constantino, J. L., Efimov, I. R., Plank, G., and Trayanova, N. A., Three-dimensional mechanisms of increased vulnerability to electric shocks in myocardial infarction: Altered virtual electrode polarizations and conduction delay in the peri-infarct zone. The Journal of Physiology 2012;590:4537–4551. doi:10.1113/jphysiol.2012.229088.

153. Campos, F. O., Prassl, A. J., Seemann, G., Santos, R. W. dos, Plank, G., and Hofer, E., Influence of ischemic core muscle fibers on surface depolarization potentials in superfused cardiac tissue preparations: A simulation study. Medical & Biological Engineering & Computing 2012;50:461–472. doi:10.1007/s11517-012-0880-1.

154. Boyle, P. M., Madhavan, A., Reid, M. P., and Vigmond, E. J., Propagating unstable wavelets in cardiac tissue. Physical Review E 2012;85: doi:10.1103/physreve.85.011909.

155. Wiener, T., Campos, F. O., Plank, G., and Hofer, E., Decomposition of fractionated local electrograms using an analytic signal model based on sigmoid functions. Biomedizinische Technik/Biomedical Engineering 2012;57: doi:10.1515/bmt-2012-0008.

156. Bishop, M. J., Vigmond, E., and Plank, G., Cardiac bidomain bath-loading effects during arrhythmias: Interaction with anatomical heterogeneity. Biophysical Journal 2011;101:2871–2881. doi:10.1016/j.bpj.2011.10.052.

157. Muñoz, M. A., Kaur, J., and Vigmond, E. J., Onset of atrial arrhythmias elicited by autonomic modulation of rabbit sinoatrial node activity: A modeling study. American Journal of Physiology-Heart and Circulatory Physiology 2011;301:H1974–H1983. doi:10.1152/ajpheart.00059.2011.

158. Niederer, S. A., Kerfoot, E., Benson, A. P., Bernabeu, M. O., Bernus, O., Bradley, C., Cherry, E. M., Clayton, R., Fenton, F. H., Garny, A., Heidenreich, E., Land, S., Maleckar, M., Pathmanathan, P., et al., Verification of cardiac tissue electrophysiology simulators using an n -version benchmark. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2011;369:4331–4351. doi:10.1098/rsta.2011.0139.

159. NIEDERER, S. A., SHETTY, A. K., PLANK, G., BOSTOCK, J., RAZAVI, R., SMITH, N. P., and RINALDI, C. A., Biophysical modeling to simulate the response to multisite left ventricular stimulation using a quadripolar pacing lead. Pacing and Clinical Electrophysiology 2011;35:204–214. doi:10.1111/j.1540-8159.2011.03243.x.

160. Costa, C. M., Campos, F. O., Prassl, A. J., Santos, R. W. dos, Sanchez-Quintana, D., Hofer, E., and Plank, G., A finite element approach for modeling micro-structural discontinuities in the heart. 2011 in 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2011.6090059.

161. Moreno, J. D., Zhu, Z. I., Yang, P.-C., Bankston, J. R., Jeng, M.-T., Kang, C., Wang, L., Bayer, J. D., Christini, D. J., Trayanova, N. A., Ripplinger, C. M., Kass, R. S., and Clancy, C. E., A computational model to predict the effects of class i anti-arrhythmic drugs on ventricular rhythms. Science Translational Medicine 2011;3:98ra83–98ra83. doi:10.1126/scitranslmed.3002588.

162. Çetingül, H. E., Plank, G., Trayanova, N. A., and Vidal, R., Estimation of local orientations in fibrous structures with applications to the purkinje system. IEEE Transactions on Biomedical Engineering 2011;58:1762–1772. doi:10.1109/tbme.2011.2116119.

163. Rocha, B. M., Kickinger, F., Prassl, A. J., Haase, G., Vigmond, E. J., Santos, R. W. dos, Zaglmayr, S., and Plank, G., A macro finite-element formulation for cardiac electrophysiology simulations using hybrid unstructured grids. IEEE Transactions on Biomedical Engineering 2011;58:1055–1065. doi:10.1109/tbme.2010.2064167.

164. Ridler, M.-E., Lee, M., McQueen, D., Peskin, C., and Vigmond, E., Arrhythmogenic consequences of action potential duration gradients in the atria. Canadian Journal of Cardiology 2011;27:112–119. doi:10.1016/j.cjca.2010.12.002.

165. Bishop, M. J., Boyle, P. M., Plank, G., Welsh, D. G., and Vigmond, E. J., Modeling the role of the coronary vasculature during external field stimulation. IEEE Transactions on Biomedical Engineering 2010;57:2335–2345. doi:10.1109/tbme.2010.2051227.

166. Deo, M., Boyle, P. M., Kim, A. M., and Vigmond, E. J., Arrhythmogenesis by single ectopic beats originating in the purkinje system. American Journal of Physiology-Heart and Circulatory Physiology 2010;299:H1002–H1011. doi:10.1152/ajpheart.01237.2009.

167. Niederer, S. A., Plank, G., Chinchapatnam, P., Ginks, M., Lamata, P., Rhode, K. S., Rinaldi, C. A., Razavi, R., and Smith, N. P., Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. Cardiovascular Research 2010;89:336–343. doi:10.1093/cvr/cvq318.

168. Bayer, J. D., Narayan, S. M., Lalani, G. G., and Trayanova, N. A., Rate-dependent action potential alternans in human heart failure implicates abnormal intracellular calcium handling. Heart Rhythm 2010;7:1093–1101. doi:10.1016/j.hrthm.2010.04.008.

169. Campos, F. O., Wiener, T., Prassl, A. J., Ahammer, H., Plank, G., Santos, R. W. dos, Sanchez-Quintana, D., and Hofer, E., A 2D-computer model of atrial tissue based on histographs describes the electro-anatomical impact of microstructure on endocardiac potentials and electric near-fields. 2010 in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology (IEEE). doi:10.1109/iembs.2010.5626870.

170. Boyle, P. M., and Vigmond, E. J., An intuitive safety factor for cardiac propagation. Biophysical Journal 2010;98:L57–L59. doi:10.1016/j.bpj.2010.03.018.

171. Vadakkumpadan, F., Arevalo, H., Prassl, A. J., Chen, J., Kickinger, F., Kohl, P., Plank, G., and Trayanova, N., Image-based models of cardiac structure in health and disease. Wiley Interdisciplinary Reviews: Systems Biology and Medicine 2010;2:489–506. doi:10.1002/wsbm.76.

172. Romero, D., Sebastian, R., Bijnens, B. H., Zimmerman, V., Boyle, P. M., Vigmond, E. J., and Frangi, A. F., Effects of the purkinje system and cardiac geometry on biventricular pacing: A model study. Annals of Biomedical Engineering 2010;38:1388–1398. doi:10.1007/s10439-010-9926-4.

173. Deo, M., Boyle, P., Plank, G., and Vigmond, E., Arrhythmogenic mechanisms of the purkinje system during electric shocks: A modeling study. Heart Rhythm 2009;6:1782–1789. doi:10.1016/j.hrthm.2009.08.023.

174. Ghaly, H. A., Boyle, P. M., Vigmond, E. J., Shimoni, Y., and Nygren, A., Simulations of reduced conduction reserve in the diabetic rat heart: Response to uncoupling and reduced excitability. Annals of Biomedical Engineering 2009;38:1415–1425. doi:10.1007/s10439-009-9855-2.

175. Boyle, P. M., Deo, M., Plank, G., and Vigmond, E. J., Purkinje-mediated effects in the response of quiescent ventricles to defibrillation shocks. Annals of Biomedical Engineering 2009;38:456–468. doi:10.1007/s10439-009-9829-4.

176. Southern, J. A., Plank, G., Vigmond, E. J., and Whiteley, J. P., Solving the coupled system improves computational efficiency of the bidomain equations. IEEE Transactions on Biomedical Engineering 2009;56:2404–2412. doi:10.1109/tbme.2009.2022548.

177. Suzuki, G., Leon, L. J., Kimber, S., and Vigmond, E. J., Predicting defibrillation outcome based on phase of ventricular activity during ICD implantation. 2009 in 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2009.5334216.

178. Plank, G., Burton, R. A. B., Hales, P., Bishop, M., Mansoori, T., Bernabeu, M. O., Garny, A., Prassl, A. J., Bollensdorff, C., Mason, F., Mahmood, F., Rodriguez, B., Grau, V., Schneider, J. E., et al., Generation of histo-anatomically representative models of the individual heart: Tools and application. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2009;367:2257–2292. doi:10.1098/rsta.2009.0056.

179. Prassl, A. J., Kickinger, F., Ahammer, H., Grau, V., Schneider, J. E., Hofer, E., Vigmond, E. J., Trayanova, N. A., and Plank, G., Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems. IEEE Transactions on Biomedical Engineering 2009;56:1318–1330. doi:10.1109/tbme.2009.2014243.

180. Vigmond, E., Vadakkumpadan, F., Gurev, V., Arevalo, H., Deo, M., Plank, G., and Trayanova, N., Towards predictive modelling of the electrophysiology of the heart. Experimental Physiology 2009;94:563–577. doi:10.1113/expphysiol.2008.044073.

181. Vadakkumpadan, F., Rantner, L. J., Tice, B., Boyle, P., Prassl, A. J., Vigmond, E., Plank, G., and Trayanova, N., Image-based models of cardiac structure with applications in arrhythmia and defibrillation studies. Journal of Electrocardiology 2009;42:157.e1–157.e10. doi:10.1016/j.jelectrocard.2008.12.003.

182. Morgan, S. W., Plank, G., Biktasheva, I. V., and Biktashev, V. N., Low energy defibrillation in human cardiac tissue: A simulation study. Biophysical Journal 2009;96:1364–1373. doi:10.1016/j.bpj.2008.11.031.

183. Narayan, S. M., Bayer, J. D., Lalani, G., and Trayanova, N. A., Action potential dynamics explain arrhythmic vulnerability in human heart failure. Journal of the American College of Cardiology 2008;52:1782–1792. doi:10.1016/j.jacc.2008.08.037.

184. Deo, M., Boyle, P., Plank, G., and Vigmond, E., Role of purkinje system in cardiac arrhythmias. 2008 in 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2008.4649112.

185. Plank, G., Zhou, L., Greenstein, J. L., Cortassa, S., Winslow, R. L., ORourke, B., and Trayanova, N. A., From mitochondrial ion channels to arrhythmias in the heart: Computational techniques to bridge the spatio-temporal scales. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2008;366:3381–3409. doi:10.1098/rsta.2008.0112.

186. Vigmond, E. J., Clements, C., McQueen, D. M., and Peskin, C. S., Effect of bundle branch block on cardiac output: A whole heart simulation study. Progress in Biophysics and Molecular Biology 2008;97:520–542. doi:10.1016/j.pbiomolbio.2008.02.022.

187. Boyle, P. M., Deo, M., and Vigmond, E. J., Behaviour of the purkinje system during defibrillation-strength shocks. 2007 in 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2007.4352313.

188. Hofer, E., Wiener, T., Prassl, A. J., Thurner, T., and Plank, G., Oblique propagation of activation allows the detection of uncoupling microstructures from cardiac near field behavior. 2007 in 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2007.4352312.

189. Trayanova, N., and Plank, G., Arrhythmogenesis research: A perspective from computational electrophysiology viewpoint. 2007 in 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2007.4352310.

190. Wiener, T., Thurner, T., Prassl, A. J., Plank, G., and Hofer, E., Accuracy of local conduction velocity determination from non-fractionated cardiac activation signals. 2007 in 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2007.4352214.

191. Deo, M., Bauer, S., Plank, G., and Vigmond, E., Reduced-order preconditioning for bidomain simulations. IEEE Transactions on Biomedical Engineering 2007;54:938–942. doi:10.1109/tbme.2006.889203.

192. Plank, G., Liebmann, M., Santos, R. W. dos, Vigmond, E. J., and Haase, G., Algebraic multigrid preconditioner for the cardiac bidomain model. IEEE Transactions on Biomedical Engineering 2007;54:585–596. doi:10.1109/tbme.2006.889181.

193. Vigmond, E. J., and Clements, C., Construction of a computer model to investigate sawtooth effects in the purkinje system. IEEE Transactions on Biomedical Engineering 2007;54:389–399. doi:10.1109/tbme.2006.888817.

194. BURTON, R. A. B., PLANK, G., SCHNEIDER, J. E., GRAU, V., AHAMMER, H., KEELING, S. L., LEE, J., SMITH, N. P., GAVAGHAN, D., TRAYANOVA, N., and KOHL, P., Three-dimensional models of individual cardiac histoanatomy: Tools and challenges. Annals of the New York Academy of Sciences 2006;1080:301–319. doi:10.1196/annals.1380.023.

195. Trayanova, N., Plank, G., and Rodrı́guez, B., What have we learned from mathematical models of defibrillation and postshock arrhythmogenesis? Application of bidomain simulations. Heart Rhythm 2006;3:1232–1235. doi:10.1016/j.hrthm.2006.04.015.

196. Deo, M., Bauer, S., Plank, G., and Vigmond, E., Accelerating large cardiac bidomain simulations by arnoldi preconditioning. 2006 in 2006 International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2006.259271.

197. Ridler, M., McQueen, D. M., Peskin, C. S., and Vigmond, E., Action potential duration gradient protects the right atrium from fibrillating. 2006 in 2006 International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2006.260522.

198. Vigmond, E. J., Tsoi, V., and Page, P., Atrial action potential heterogeneity measured by unipolar electrograms. 2006 in 2006 International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE). doi:10.1109/iembs.2006.259830.

199. Mechanisms of atrial fibrillation termination by pure sodium channel blockade in an ionically-realistic mathematical model, Circulation Research 2005;96: doi:10.1161/01.res.0000160709.49633.2b.

200. PLANK, G., LEON, L. J., KIMBER, S., and VIGMOND, E. J., Defibrillation depends on conductivity fluctuations and the degree of disorganization in reentry patterns. Journal of Cardiovascular Electrophysiology 2005;16:205–216. doi:10.1046/j.1540-8167.2005.40140.x.

201. WeberdosSantos, R., Plank, G., Bauer, S., and Vigmond, E. J., Parallel multigrid preconditioner for the cardiac bidomain model. IEEE Transactions on Biomedical Engineering 2004;51:1960–1968. doi:10.1109/tbme.2004.834275.

202. Vigmond, E. J., Tsoi, V., Kuo, S., Arevalo, H., Kneller, J., Nattel, S., and Trayanova, N., The effect of vagally induced dispersion of action potential duration on atrial arrhythmogenesis. Heart Rhythm 2004;1:334–344. doi:10.1016/j.hrthm.2004.03.077.

203. Vigmond, E. J., Hughes, M., Plank, G., and Leon, L., Computational tools for modeling electrical activity in cardiac tissue. Journal of Electrocardiology 2003;36:69–74. doi:10.1016/j.jelectrocard.2003.09.017.

204. Vigmond, E. J., Aguel, F., and Trayanova, N. A., Computational techniques for solving the bidomain equations in three dimensions. IEEE Transactions on Biomedical Engineering 2002;49:1260–1269. doi:10.1109/tbme.2002.804597.

205. Kneller, J., Zou, R., Vigmond, E. J., Wang, Z., Leon, L. J., and Nattel, S., Cholinergic atrial fibrillation in a computer model of a two-dimensional sheet of canine atrial cells with realistic ionic properties. Circulation Research 2002;90: doi:10.1161/01.res.0000019783.88094.ba.

206. Vigmond, E. J., Blauer, J., Neic, A., Swenson, D., and Plank, G., How electrode position affects selective his bundle capture: A modelling study. IEEE Transactions on Biomedical Engineering 2021;1–1. doi:10.1109/tbme.2021.3072334.

207. Trayanova, N., Constantino, J., Ashihara, T., and Plank, G., Modeling defibrillation of the heart: Approaches and insights. IEEE Reviews in Biomedical Engineering 2011;4:89–102. doi:10.1109/rbme.2011.2173761.

208. Bajaj, N., Leon, L. J., Vigmond, E., and Kimber, S., Fibrillation complexity as a predictor of successful defibrillation. 2005 in 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (IEEE). doi:10.1109/iembs.2005.1616528.

209. Clements, C. J., and Vigmond, E. J., Construction of a cardiac conduction system subject to extracellular stimulation. 2005 in 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (IEEE). doi:10.1109/iembs.2005.1615399.

210. Deo, M., and Vigmond, E., Arnoldi preconditioning for solving large linear biomedical systems. 2005 in 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (IEEE). doi:10.1109/iembs.2005.1617084.

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