Center for Computational Medicine in Cardiology

Phone

+41 58 666 4976

Address

Institute of Computational Science
Faculty of Informatics
Via La Santa 1
6900 Lugano
Switzerland

Mail

simone.pezzuto_AT_usi_DOT_ch

Simone Pezzuto

CCMC Group Leader

Simone Pezzuto is Group Leader at the Center for Computational Medicine in Cardiology (CCMC). The center of the research activities of Dr. Pezzuto lies at the interdisciplinary intersection between applied mathematics and cardiac physiology. In the spirit of the CCMC vision, Dr. Pezzuto fosters a tight collaboration with the clinical partners to translate mathematical modeling of the heart into clinical applications. While being a numerical analyst by education, Dr. Pezzuto collaborates on a daily basis with clinical cardiac electrophysiologists at addressing, by means of computer models, questions of clinical interest.

The group of Dr. Pezzuto, currently consisting of 1 postdoc (Dr. Ali Gharaviri) and 1 PhD student (Lia Gander), has the objective to develop novel numerical methods to tackle problems of clinical relevance, such as inverse problems and parameter identification, uncertainty quantification, and efficient simulation of both cardiac electrophysiology and mechanics.

Patient-Specific modeling

Patient-specific modeling in cardiac electrophysiology is based on sophisticated mathematical models which require special care in their numerical solution and parametrization. Given the increasing availability of patient data, from the standard 12-lead electrocardiogram to minimally invasive, high-density catheter mapping, we employ modern numerical algorithms to assimilate such data into the model for further individualization and, ultimately, improved therapeutic intervention. Amongst our recent achievements, we have been able to identify sites of earliest ventricular activation from the 12-lead ECG and to reconstruct the fiber architecture and conduction velocity from contact-mapping recordings.

Uncertainty Quantification

Fibrosis Random Field In view of clinical applications, and given its importance, our group has recently started to include uncertainty quantification (UQ) into our electrophysiology models. The strategy we pursued was to combine existing models for cardiac electrophysiology to accelerate the standard Monte Carlo procedure (multifidelity approach). Incidentally, we have also developed a method for sampling random fields on general and possibly complex geometries, such as the heart anatomy.

Academic Career

Current position

Group Leader, Center for Computational Medicine in Cardiology, Institute of Computational Science, USI: 11-2019 - present

Past positions

Postdoctoral researcher, Center for Computational Medicine in Cardiology, Institute of Computational Science, USI: 01-2015 - 10-2019
Postdoctoral researcher, Simula Research Laboratory: 08-2013 - 12-2014
Research assistant, Politecnico di Milano: 01-2013 - 08-2013

Education

Ph.D. in Mathematics, MOX, Politecnico di Milano: 01-2010 - 05-2013 (XXV ciclo)
Thesis: Mechanics of the Heart: Constitutive Issues and Numerical Experiments, advisor Prof. D.Ambrosi
Visiting student, Cardiac Mechanics Research Group, UCSD: 07-2011 - 12-2011
Master's Degree in Mathematical Engineering, Politecnico di Milano: 04-2008 - 12-2009
Thesis: Space-time adaptivity for non-linear reaction-diffusion systems with application to electrocardiology (pdf in italian), advisors Prof. F.Nobile and S.Perotto.
Bachelor in Mathematical Engineering, Politecnico di Milano: 09-2004 - 03-2008
Thesis: Analytical estimates of principal frequency of polygonal membranes (pdf in italian), advisor Prof. M. Bramanti.

Projects

Running

EuroHPC-JU: MICROCARD: Numerical modeling of cardiac electrophysiology at the cellular scale, with U. Bordeaux, U. Strasbourg, Simula, U. Pavia, USI, KIT, ZIB Berlin, Megware, NumeriCor, Orobix. 04-2021 - 03-2025.
Swiss Heart Foundation: Impact of sex hormones on regional atrial electrical function and sex differences in atrial fibrillation, with Katja Odening (Universität Bern)
01-2021 - 12-2021.
CSCS Production Grant (Swiss National Supercomputing Centre): LongAF: In silico Study of the Combined Effect of Structural and Electrical Heterogeneities in Long Episodes of Atrial Fibrillation,
A. Gharaviri, U. Schotten, G. Conte, R. Krause, A. Auricchio
04-2021 - 03-2024.

Past

CSCS Production Grant (Swiss National Supercomputing Centre): Development of patient-specific prediction model of efficacy of antiarrhythmic drug therapy and ablation strategy in patients with atrial fibrillation,
with Ali Gharaviri, Ulrich Schotten, Jordi Heijman, Rolf Krause, Angelo Auricchio
04-2018 - 03-2021.

Teaching

Current academic year

Introduction to Ordinary Differential Equations, Master in CS/AI, USI. Material hosted on iCorsi3.
Mathematical Cardiac Physiology, Master/PhD in CS, USI
Winter School on Cardiac Simulations, USI, Invited lecturer (More information). Slide available upon request.

Past courses

Introduction to Ordinary Differential Equations, USI (since 2017, lecturer)
Mathematical Cardiac Physiology, USI (2018-2019, More information). Material available upon request.
Introduction to Partial Differential Equations, USI (2015 and 2017, assistant lecturer)
Introduction to Differential Equations, USI (2016, lecturer)
Introduction to Numerical Methods for Ordinary Differential Equations, USI (2015, assistant lecturer)
Optimization Methods, USI (2017, assistant lecturer)
Multiscale Methods, USI (2017, assistant lecturer)
Linear and Nonlinear Multiscale Solution Techniques, USI (2016, assistant lecturer)
Computational Medicine, USI (2015, assistant lecturer)
Summer School on Computational Physiology, Simula Research Laboratory, invited lecturer (2014-2015)
Biomathematical Modeling, Politecnico di Milano (2011-2012, teaching assistant)
Ordinary Differential Equations, Politecnico di Milano (2011-2013, teaching assistant)
Analytical and Numerical Methods in Engineering, Politecnico di Milano (2012-2013, teaching assistant)

Publications

Peer-reviewed journals

Gander, L., S. Pezzuto, A. Gharaviri, R. Krause, P. Perdikaris, F. Sahli-Costabal. Fast characterization of inducible regions of atrial fibrillation models with multi-fidelity Gaussian process classification. (submitted)
Grandits, T., A. Effland, T. Pock, R. Krause, G. Plank, S. Pezzuto (2021). GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models. Int J Numer Meth Biomed Engng, 37(8):e3505. DOI: 10.1002/cnm.3505. arXiv: 2102.09962.
Gander, L., R. Krause, M. Multerer, and S. Pezzuto (2021). Space-time shape uncertainty in the forward and inverse problem of electrocardiography. Int J Numer Meth Biomed Engng, in press. DOI: 10.1002/cnm.3522. arXiv: 2010.16104.
Gharaviri, A., S. Pezzuto, M. Potse, G. Conte, S. Zeemering, V. Sobota, S. Verheule, R. Krause, A. Auricchio, and U. Schotten (2021). Synergistic antiarrhythmic effect of inward rectifier current inhibition and pulmonary vein isolation in a 3D computer model for atrial fibrillation. EP Europace, 23(suppl_i), pag. i161-i168. DOI: 10.1093/europace/euaa413
Lubrecht, J. M., T. Grandits, A. Gharaviri, U. Schotten, T. Pock, G. Plank, R. Krause, A. Auricchio, and S. Pezzuto (2021). Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fiber structure and anisotropic conduction in a patient-specific model. EP Europace, 23(suppl_i) pag. i63-i70. DOI: 10.1093/europace/euaa392
Auricchio, A., T. Özkartal, F. Salghetti, L. Neumann, S. Pezzuto, A. Gharaviri, A. Demarchi, M. L. Caputo, F. Regoli, C. De Asmundis, G.-B. Chierchia, P. Brugada, C. Klersy, T. Moccetti, U. Schotten, and G. Conte (2021). A short P-wave duration is a marker of higher rate of atrial fibrillation recurrences after pulmonary vein isolation: new insights into the pathophysiological mechanisms through computer simulations. Journal of the American Heart Association, 10(2) pag. e018572. DOI: 10.1161/JAHA.120.018572
Gharaviri, A., S. Pezzuto, M. Potse, S. Verheule, G. Conte, R. Krause, U. Schotten, and A. Auricchio (2021). Left atrial appendage electrical isolation reduces atrial fibrillation recurrences: simulation study. Circulation: Arrhythmia and Electrophysiology 14(1) pag. e009230. DOI: 10.1161/CIRCEP.120.009230
Pezzuto, S., F. W. Prinzen, M. Potse, F. Maffessanti, F. Regoli, M. L. Caputo, G. Conte, R. Krause, and A. Auricchio (2021). Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling. EP Europace, 23(4), pag. 640-647. DOI: 10.1093/europace/euaa330.
Gharaviri, A., E. Bidar, M. Potse, S. Zeemering, S. Verheule, S. Pezzuto, R. Krause, J. G. Maessen, A. Auricchio, and U. Schotten (2020). Epicardial Fibrosis Explains Increased Endo-Epicardial Dissociation and Epicardial Breakthroughs in Human Atrial Fibrillation. Frontiers in Physiology 11:68. DOI: 10.3389/fphys.2020.00068.
Maffessanti, F., Jadczyk, T., Kurzelowski, R., Regoli, F., Caputo, M.L., Conte, G., Gołba, K.S., Biernat, J., Wilczek, J., Dąbrowska, M., Pezzuto, S., Moccetti, T., Krause, R., Wojakowski, W., Prinzen, F.W., Auricchio A. (2020). The influence of scar on the spatio-temporal relationship between electrical and mechanical activation in heart failure patients. EP Europace 22(5), pag. 777-786. DOI: 10.1093/europace/euz346.
Quaglino, A., Pezzuto, S., Krause, R. (2019). High-dimensional and higher-order multifidelity Monte Carlo estimators. J Comp Phys, 388, pag. 300-315. DOI: 10.1016/j.jcp.2019.03.026
Pezzuto, S., Gharaviri, A., Schotten, U., Conte, G., Krause, R., Auricchio, A. (2018). Beat-to-beat P-wave morphological variability in patients with paroxysmal AF: an in-silico study. Europace, 20(suppl 3), pag. 26-35. DOI: 10.1093/europace/euy227.
Quaglino, A., Pezzuto, S., Koutsourelakis, P.S., Auricchio, A., Krause, R. (2018). Fast uncertainty quantification of activation sequences in patient-specific cardiac electrophysiology meeting clinical time constraints. Int J Numer Meth Biomed Engng, e2985, DOI: 10.1002/cnm.2985.
Pezzuto, S., Kal'avský, P., Potse, M., Prinzen, F.W., Auricchio, A., Krause, R. (2017). Evaluation of a Rapid Anisotropic Model for ECG Simulation. Front Physiol, 8, pag. 265. DOI: 10.3389/fphys.2017.00265.
Ambrosi D., Pezzuto, S., Riccobelli, D., Stylianopoulos, T., Ciarletta, P. (2017). Solid tumors are poroelastic solids with a chemo-mechanical feedback on growth. J Elast, 129(1-2), pag. 107-124. DOI: 10.1007/s10659-016-9619-9
Favino, M., Pozzi, S., Pezzuto, S., Prinzen, F.W., Auricchio, A., Krause, R. (2016). Impact of mechanical deformation on pseudo-ECG: a simulation study. Europace, 18(suppl 4), pag. iv77-iv84. DOI: 10.1093/europace/euw353.
Pettinati, V., Ambrosi, D., Ciarletta, P., Pezzuto, S. (2016). Finite element simulations of the active stress in the imaginal disc of the Drosophila Melanogaster. Comput Methods Biomech Biomed Eng 19(12), pag. 1241-1253. DOI: 10.1080/10255842.2015.1124270.
Pezzuto, S., Hake, J., Sundnes, J. (2016). Space-discretization error analysis and stabilization schemes for conduction velocity in cardiac electrophysiology. Int J Numer Meth Biomed Engng, 32(10). DOI: 10.1002/cnm.2762.
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., Griffith, B.E., Hurtado, D.E., Krause, R., Luo, X., Nash, M.P., Pezzuto, S., Plank, G., Rossi, S., Ruprecht, D., Seemann, G., Smith, N.P., Sundnes, J., Rice, J.J., Trayanova, N., Wang, D., Wang, Z.J., Niederer, S.A. (2015). Verification of cardiac mechanics software: Benchmark problems and solutions for testing active and passive material behaviour. Proceedings of the Royal Society A, 471(2184). DOI: 10.1098/rspa.2015.0641
Vincent, K. P., Gonzales, M. J., Gillette, A. K., Villongco, C. T., Pezzuto, S., Omens, J. H., McCulloch, A. D. (2015). High-order finite element methods for cardiac monodomain simulations. Front Phys, 6(217). DOI: 10.3389/fphys.2015.00217
Pezzuto, S., Ambrosi, D. (2014). Active contraction of the cardiac ventricle and distortion of the microstructural architecture. Int J Numer Meth Biomed Engng, 30(12), 1578-1596. DOI: 10.1002/cnm.2690
Pezzuto, S., Ambrosi, D., Quarteroni, A. (2014). An orthotropic active-strain model for the myocardium mechanics and its numerical approximation. Eur J Mech A Solids, 48, 83-96. DOI: 10.1016/j.euromechsol.2014.03.006
Ambrosi, D., Pezzuto, S. (2012). Active stress vs. active strain in mechanobiology: constitutive issues. J Elast, 107(2), pag. 199-212. DOI: 10.1007/s10659-011-9351-4.

Peer-reviewed conference proceedings

Marques, V., A. Gharaviri, S. Pezzuto, P. Bonizzi, S. Zeemering, U. Schotten (2021). Spatial Relationship Between Atrial Fibrillation Drivers and the Presence of Repetitive Conduction Patterns Using Recurrence Analysis on In-Silico Models CinC 2021.
Grandits, T., S. Pezzuto, F. Sahli Costabal, P. Perdikaris, T. Pock, G. Plank, R. Krause (2021). Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural network. In Functional Imaging and Modeling of the Heart. FIMH 2021, edited by Ennis, D.B., Perotti, L.E., Wang, V.Y. DOI: 978-3-030-78710-3_62. arXiv: 2102.10863.
Multerer, M., S. Pezzuto (2021). Fast and Accurate Uncertainty Quantification for the ECG with Random Electrodes Location. In Functional Imaging and Modeling of the Heart. FIMH 2021, edited by Ennis, D.B., Perotti, L.E., Wang, V.Y. DOI: 10.1007/978-3-030-78710-3_54. arXiv: 2102.09960.
Grandits, T., S. Pezzuto, J. M. Lubrecht, T. Pock, G. Plank, and R. Krause (2021). PIEMAP: Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps. In Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges. Puyol Anton, E., M. Pop, M. Sermesant, V. Campello, A. Lalande, K. Lekadir, A. Suinesiaputra, O. Camara, and A. Young, Eds., ser. Lecture Notes in Computer Science, vol. 12592, Cham: Springer, pp. 76–86. DOI: 10.1007/978-3-030-68107-4_8. arXiv: 2008.10724.
Pezzuto, S., F. W. Prinzen, M. Potse, F. Regoli, M. L. Caputo, G. Conte, R. Krause, and A. Auricchio. Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling. In Heart Rhythm, 16(S51), 2019. DOI: 10.1016/j.hrthm.2019.04.013.
Pezzuto, S., A. Quaglino, and M. Potse. On Sampling Spatially-Correlated Random Fields for Complex Geometries. In Functional Imaging and Modeling of the Heart, edited by Coudière, Y., V. Ozenne, E. Vigmond, and N. Zemzemi, 11504:103–111. Lecture Notes in Computer Science. Cham: Springer, 2019. DOI: 10.1007/978-3-030-21949-9_12.
Potse, M., A. Vinet, A. Gharaviri, and S. Pezzuto. Fibrillation Patterns Creep and Jump in a Detailed Three-Dimensional Model of the Human Atria. In Functional Imaging and Modeling of the Heart, edited by Coudière, Y., V. Ozenne, E. Vigmond, and N. Zemzemi, 11504:131–138. Lecture Notes in Computer Science. Cham: Springer, 2019. 10.1007/978-3-030-21949-9_15.
Gharaviri, A., Pezzuto, S., Potse, M., Verheule, S., , Krause, R., Auricchio, A., Schotten, U. (2019). Fibrosis explains atrial fibrillation recurrences after pulmonary vein isolation. A simulation study. EHRA Congress 2019. DOI: 10.1093/europace/euz093
Gharaviri, A., Zink, M., Potse, M., Pezzuto, S., Zeemering, S., Krause, R., Auricchio, A., Schotten, U. (2018). Acute Changes in P-Wave Morphology by Pulmonary Vein Isolation in Atrial Fibrillation Patients. CinC 2018. PDF
Potse, M., Gharaviri, A., Pezzuto, S., Auricchio, A., Krause, R., Verheule, S., Schotten, U. (2018). Anatomically-induced Fibrillation in a 3D model of the Human Atria. Beat-to-beat P-wave morphological variability in patients with paroxysmal AF: an in-silico study. CinC 2018. PDF
Pezzuto, S., Kal'avský, P., Potse, M., Prinzen, F.W., Auricchio, A., Krause, R. (2016). Fast simulation of standard 12-lead ECG and 3d ventricular activation. EP Europace 19(suppl 3). DOI: 10.1093/ehjci/eux155.007
Pezzuto, S., Kal'avský, P., Potse, M., Regoli, F., Caputo, M.L., Conte, G., Moccetti, T., Prinzen, F.W., Auricchio, A., Krause, R. (2016). Accurate estimation of 3D ventricular activation from electroanatomic mapping. Cardiostim EHRA Europace.
Gjerald, S., Hake, J., Pezzuto, S., Sundnes, J., Wall, S.T. (2015). Patient-Specific Parameter Estimation for a Transversely Isotropic Active Strain Model of Left Ventricular Mechanics. Statistical Atlases and Computational Models of the Heart-Imaging and Modelling Challenges (pp. 93-104). Springer International Publishing. DOI: 10.1007/978-3-319-14678-2_10
Ruiz-Baier, R., Ambrosi, D., Pezzuto, S., Rossi, S., Quarteroni, A. (2013). Activation models for the numerical simulation of cardiac electromechanical interactions. Computer Models in Biomechanics: From Nano to Macro (pp. 189-201). Springer Netherlands.

Code

FIMH2021: Illustrative code for UQ for the ECG with random electrode locations on the chest.
FIMH2019: Code for sampling random fields on complex domains, for instance to model spatial heterogeneities (with spatial correlation) on the heart. We use this code to model patchy fibrosis patterns, for instance. The code provides two sampling strategies: a stochastic PDE approach and another based on a truncated Karhunen-Loeve expansion with correlation kernel as function of the geodesic distance. The geodesic distance is computed with the eikonal equation.
Propeiko, fast eikonal solver and ECG simulator.
Propag, massively parallel OpenMPI+OpenMP+CUDA solver for electrophysiology of the heart (contributing author).
mechbench, code for the mechanics benchmark from Sander et al.
lvchallenge, code for STACOM LVChallenge, results published in Gjerald et al.
pulse, FEniCS code for simulating the mechanics of the heart.
fenicshotools, FEniCS tools for importing Gmsh files, with support for high-order geometries.