Skip to Main Content

Bulletin of the American Mathematical Society

The Bulletin publishes expository articles on contemporary mathematical research, written in a way that gives insight to mathematicians who may not be experts in the particular topic. The Bulletin also publishes reviews of selected books in mathematics and short articles in the Mathematical Perspectives section, both by invitation only.

ISSN 1088-9485 (online) ISSN 0273-0979 (print)

The 2020 MCQ for Bulletin of the American Mathematical Society is 0.84.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.

 

Modeling the cardiac electromechanical function: A mathematical journey
HTML articles powered by AMS MathViewer

by Alfio Quarteroni, Luca Dedè and Francesco Regazzoni HTML | PDF
Bull. Amer. Math. Soc. 59 (2022), 371-403 Request permission

Abstract:

In this paper we introduce the electromechanical mathematical model of the human heart. After deriving it from physical first principles, we discuss its mathematical properties and the way numerical methods can be set up to obtain numerical approximations of the (otherwise unachievable) mathematical solutions. The major challenges that we need to face—e.g., possible lack of initial and boundary data, the trade off between increasing the accuracy of the numerical model and its computational complexity—are addressed. Numerical tests here presented have a twofold aim: to show that numerical solutions match the expected theoretical rate of convergence, and that our model can provide a preliminary valuable tool to face problems of clinical relevance.
References
  • World Health Organization (2017). Cardiovascular diseases (CVDs)., https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds), visited on 12/05/2020.
  • Zygote 3D models, https://www.zygote.com, 2019.
  • Robert A. Adams and John J. F. Fournier, Sobolev spaces, 2nd ed., Pure and Applied Mathematics (Amsterdam), vol. 140, Elsevier/Academic Press, Amsterdam, 2003. MR 2424078
  • R. R. Aliev and A. V. Panfilov, A simple two-variable model of cardiac excitation, Chaos, Solitons & Fractals 7 (1996), no. 3, 293–301.
  • D. Ambrosi, G. Arioli, F. Nobile, and A. Quarteroni, Electromechanical coupling in cardiac dynamics: the active strain approach, SIAM J. Appl. Math. 71 (2011), no. 2, 605–621. MR 2788339, DOI 10.1137/100788379
  • D. Ambrosi and S. Pezzuto, Active stress vs. active strain in mechanobiology: constitutive issues, J. Elasticity 107 (2012), no. 2, 199–212. MR 2899010, DOI 10.1007/s10659-011-9351-4
  • Boris Andreianov, Mostafa Bendahmane, Alfio Quarteroni, and Ricardo Ruiz-Baier, Solvability analysis and numerical approximation of linearized cardiac electromechanics, Math. Models Methods Appl. Sci. 25 (2015), no. 5, 959–993. MR 3319342, DOI 10.1142/S0218202515500244
  • Stuart S. Antman, Nonlinear problems of elasticity, Applied Mathematical Sciences, vol. 107, Springer-Verlag, New York, 1995. MR 1323857, DOI 10.1007/978-1-4757-4147-6
  • H. Arevalo, F. Vadakkumpadan, E. Guallar, A. Jebb, P. Malamas, K. C. Wu, and N. A. Trayanova, Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models, Nature Communications 7 (2016), no. 11437.
  • Christoph M. Augustin, Aurel Neic, Manfred Liebmann, Anton J. Prassl, Steven A. Niederer, Gundolf Haase, and Gernot Plank, Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation, J. Comput. Phys. 305 (2016), 622–646. MR 3429598, DOI 10.1016/j.jcp.2015.10.045
  • Brian Baillargeon, Nuno Rebelo, David D. Fox, Robert L. Taylor, and Ellen Kuhl, The living heart project: a robust and integrative simulator for human heart function, Eur. J. Mech. A Solids 48 (2014), 38–47. MR 3258230, DOI 10.1016/j.euromechsol.2014.04.001
  • John M. Ball, Convexity conditions and existence theorems in nonlinear elasticity, Arch. Rational Mech. Anal. 63 (1976/77), no. 4, 337–403. MR 475169, DOI 10.1007/BF00279992
  • J. D. Bayer, R. C. Blake, G. Plank, and N. A. Trayanova, A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models, Annals of Biomedical Engineering 40 (2012), no. 10, 2243–2254.
  • G. W. Beeler and H. Reuter, Reconstruction of the action potential of ventricular myocardial fibres, The Journal of Physiology 268 (1977), no. 1, 177–210.
  • Mostafa Bendahmane, Fatima Mroue, Mazen Saad, and Raafat Talhouk, Mathematical analysis of cardiac electromechanics with physiological ionic model, Discrete Contin. Dyn. Syst. Ser. B 24 (2019), no. 9, 4863–4897. MR 3986224, DOI 10.3934/dcdsb.2019035
  • P. J. Blanco and R. A. Feijóo, A 3D-1D-0D computational model for the entire cardiovascular system, Computational Mechanics 24 (2010), 5887–5911.
  • M. Boulakia, S, Cazeau, M. A. Fernández, J.-F. Gerbeau, and N. Zemzemi, Mathematical modeling of electrocardiograms: a numerical study, Annals of biomedical engineering 38 (2010), no. 3, 1071–1097.
  • S. G. Campbell, F. V. Lionetti, K. S. Campbell, and A. D. McCulloch, Coupling of adjacent tropomyosins enhances cross-bridge-mediated cooperative activation in a markov model of the cardiac thin filament, Biophysical Journal 98 (2010), no. 10, 2254–2264.
  • M. Caruel, R. Chabiniok, P. Moireau, Y. Lecarpentier, and D. Chapelle, Dimensional reductions of a cardiac model for effective validation and calibration, Biomechanics and Modeling in Mechanobiology 13 (2014), no. 4, 897–914.
  • Jessica Cervi and Raymond J. Spiteri, A comparison of fourth-order operator splitting methods for cardiac simulations, Appl. Numer. Math. 145 (2019), 227–235. MR 3973170, DOI 10.1016/j.apnum.2019.06.002
  • R. Chabiniok, V. Y. Wang, M. Hadjicharalambous, L. Asner, J. Lee, M. Sermesant, E. Kuhl, A. A. Young, P. Moireau, M. P. Nash, D. Chapelle, and D. A. Nordsletten, Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics, Interface Focus 6 (2016), no. 2, 20150083.
  • Philippe G. Ciarlet, The finite element method for elliptic problems, Classics in Applied Mathematics, vol. 40, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2002. Reprint of the 1978 original [North-Holland, Amsterdam; MR0520174 (58 #25001)]. MR 1930132, DOI 10.1137/1.9780898719208
  • Albert Cohen and Ronald DeVore, Approximation of high-dimensional parametric PDEs, Acta Numer. 24 (2015), 1–159. MR 3349307, DOI 10.1017/S0962492915000033
  • Piero Colli Franzone, Luca F. Pavarino, and Simone Scacchi, Mathematical cardiac electrophysiology, MS&A. Modeling, Simulation and Applications, vol. 13, Springer, Cham, 2014. MR 3308707, DOI 10.1007/978-3-319-04801-7
  • P. Colli Franzone, L. F. Pavarino, and G. Savaré, Computational electrocardiology: mathematical and numerical modeling, Complex systems in biomedicine, Springer Italia, Milan, 2006, pp. 187–241. MR 2488001, DOI 10.1007/88-470-0396-2_{6}
  • Edmund J Crampin, Matthew Halstead, Peter Hunter, Poul Nielsen, Denis Noble, Nicolas Smith, and Merryn Tawhai, Computational physiology and the physiome project, Experimental Physiology 89 (2004), no. 1, 1–26.
  • Bernard Dacorogna, Direct methods in the calculus of variations, 2nd ed., Applied Mathematical Sciences, vol. 78, Springer, New York, 2008. MR 2361288
  • L. Dede’, A. Gerbi, and A. Quarteroni, Segregated algorithms for the numerical simulation of cardiac electromechanics in the left human ventricle, The mathematics of mechanobiology, Lecture Notes in Math., vol. 2260, Springer, Cham, [2020] ©2020, pp. 81–116. MR 4175795, DOI 10.1007/978-3-030-45197-4_{3}
  • A. Einstein, Eine neue bestimmung der moleküldimensionen, Ph.D. thesis, ETH Zurich, 1905.
  • L. Euler, Principia pro motu sanguinis per arterias determinando, Euler Archive—All Works 855 (1862).
  • C. Farhat, S. Grimberg, A. Manzoni, and A. Quateroni, Computational bottlenecks for proms: Pre-computation and hyperreduction, Handbook on Model Order Reduction (P. Benner, S. Grivet-Talocia, A. Quarteroni, G Rozza, W. H. A. Schilders, and L. M. Silveira, eds.), De Gruyter, 2019.
  • M. Fink, S. A. Niederer, E. M. Cherry, F. H. Fenton, J. T. Koivumäki, G. Seemann, R. Thul, H. Zhang, F. B. Sachse, D. Beard, E. J. Crampin, and N. P. Smith, Cardiac cell modelling: observations from the heart of the cardiac physiome project, Progress in Biophysics and Molecular Biology 104 (2011), no. 1, 2–21.
  • R. FitzHugh, Impulses and physiological states in theoretical models of nerve membrane, Biophysical Journal 1 (1961), no. 6, 445–466.
  • Piero Colli Franzone and Giuseppe Savaré, Degenerate evolution systems modeling the cardiac electric field at micro- and macroscopic level, Evolution equations, semigroups and functional analysis (Milano, 2000) Progr. Nonlinear Differential Equations Appl., vol. 50, Birkhäuser, Basel, 2002, pp. 49–78. MR 1944157
  • A. Frontera, S. Pagani, L. R. Limite, A. Hadjis, A. Manzoni, L. Dedè, A. Quarteroni, and P. Della Bella, Outer loop and isthmus in ventricular tachycardia circuits: Characteristics and implications, Heart Rhythm 17 (2020), no. 10, 1719–1728, Focus Issue: Sudden Death.
  • Antonello Gerbi, Luca Dedè, and Alfio Quarteroni, A monolithic algorithm for the simulation of cardiac electromechanics in the human left ventricle, Math. Eng. 1 (2019), no. 1, 1–37. MR 4135067, DOI 10.3934/Mine.2018.1.1
  • Leon Glass, Peter Hunter, and Andrew McCulloch, Theory of heart: biomechanics, biophysics, and nonlinear dynamics of cardiac function, Springer Science & Business Media, 2012.
  • Gene Golub and James M. Ortega, Scientific computing, Academic Press, Inc., Boston, MA, 1993. An introduction with parallel computing. MR 1200454
  • J. M. Guccione, K. D. Costa, and A. D. McCulloch, Finite element stress analysis of left ventricular mechanics in the beating dog heart, Journal of Biomechanics 28 (1995), no. 10, 1167–1177.
  • J. M. Guccione, A. D. McCulloch, and L. K. Waldman, Passive material properties of intact ventricular myocardium determined from a cylindrical model, Journal of Biomechanical Engineering 113 (1991), no. 1, 42–55.
  • Jan S. Hesthaven, Gianluigi Rozza, and Benjamin Stamm, Certified reduced basis methods for parametrized partial differential equations, SpringerBriefs in Mathematics, Springer, Cham; BCAM Basque Center for Applied Mathematics, Bilbao, 2016. BCAM SpringerBriefs. MR 3408061, DOI 10.1007/978-3-319-22470-1
  • Marc Hirschvogel, Marina Bassilious, Lasse Jagschies, Stephen M. Wildhirt, and Michael W. Gee, A monolithic 3D-0D coupled closed-loop model of the heart and the vascular system: experiment-based parameter estimation for patient-specific cardiac mechanics, Int. J. Numer. Methods Biomed. Eng. 33 (2017), no. 8, e2842, 22. MR 3690497, DOI 10.1002/cnm.2842
  • Gerhard A. Holzapfel and Ray W. Ogden, Constitutive modelling of passive myocardium: a structurally based framework for material characterization, Philos. Trans. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 367 (2009), no. 1902, 3445–3475. MR 2529287, DOI 10.1098/rsta.2009.0091
  • P. J. Hunter, A. D. McCulloch, and H. E. D. J. Ter Keurs, Modelling the mechanical properties of cardiac muscle, Progress in Biophysics and Molecular Biology 69 (1998), no. 2, 289–331.
  • A. F. Huxley and R. Niedergerke, Structural changes in muscle during contraction: Interference microscopy of living muscle fibres, Nature 173 (1954), no. 4412, 971–973.
  • H. Huxley and J. Hanson, Changes in the cross-striations of muscle during contraction and stretch and their structural interpretation, Nature 173 (1954), no. 4412, 973–976.
  • G. W. Jenkins, C. P. Kemnitz, and G. J. Tortora, Anatomy and Physiology: from Science to Life, Wiley, Hoboken, 2007.
  • A. M. Katz, Physiology of the Heart, Lippincott Williams & Wilkins, 2010.
  • S. Land and S. A. Niederer, A spatially detailed model of isometric contraction based on competitive binding of troponin i explains cooperative interactions between tropomyosin and crossbridges, PLoS Computational Biology 11 (2015), no. 8, e1004376.
  • S. Land, S. Park-Holohan, N. P. Smith, C. G. dos Remedios, J. C. Kentish, and S. A. Niederer, A model of cardiac contraction based on novel measurements of tension development in human cardiomyocytes, Journal of Molecular and Cellular Cardiology 106 (2017), 68–83.
  • Sa. Land, S. A. Niederer, J. M. Aronsen, E. K. S. Espe, L. Zhang, W. E. Louch, I. Sjaastad, O. M. Sejersted, and N. P. Smith, An analysis of deformation-dependent electromechanical coupling in the mouse heart, The Journal of Physiology 590 (2012), no. 18, 4553–4569.
  • C.-H. Luo and Y. Rudy, A dynamic model of the cardiac ventricular action potential. I. Simulations of ionic currents and concentration changes., Circulation Research 74 (1994), no. 6, 1071–1096.
  • Charles B. Morrey Jr., Quasi-convexity and the lower semicontinuity of multiple integrals, Pacific J. Math. 2 (1952), 25–53. MR 54865, DOI 10.2140/pjm.1952.2.25
  • J. Nagumo, S. Arimoto, and S. Yoshizawa, An active pulse transmission line simulating nerve axon, Proceedings of the IRE 50 (1962), no. 10, 2061–2070.
  • S. A. Niederer, P. J. Hunter, and N. P. Smith, A quantitative analysis of cardiac myocyte relaxation: a simulation study, Biophysical Journal 90 (2006), no. 5, 1697–1722.
  • S. A. Niederer, K. S. Campbell, and S. G. Campbell, A short history of the development of mathematical models of cardiac mechanics, Journal of Molecular and Cellular Cardiology 127 (2019), 11–19.
  • D. A. Nordsletten, S. A. Niederer, M. P. Nash, P. J. Hunter, and N. P. Smith, Coupling multi-physics models to cardiac mechanics, Progress in Biophysics and Molecular Biology 104 (2011), no. 1-3, 77–88.
  • R. W. Ogden, Nonlinear elastic deformations, Ellis Horwood Series: Mathematics and its Applications, Ellis Horwood Ltd., Chichester; Halsted Press [John Wiley & Sons, Inc.], New York, 1984. MR 770388
  • T. O’Hara, L/ Virág, A. Varró, and Y. Rudy, Simulation of the undiseased human cardiac ventricular action potential: model formulation and experimental validation, PLoS Computational Biology 7 (2011), no. 5, e1002061.
  • P. Pathmanathan, S. J. Chapman, D. J. Gavaghan, and J. P. Whiteley, Cardiac electromechanics: the effect of contraction model on the mathematical problem and accuracy of the numerical scheme, Quart. J. Mech. Appl. Math. 63 (2010), no. 3, 375–399. MR 2672150, DOI 10.1093/qjmam/hbq014
  • C. S. Peskin, Flow patterns around heart valves: a numerical method, Journal of Computational Physics 10 (1972), no. 2, 252–271.
  • Charles S. Peskin, Numerical analysis of blood flow in the heart, J. Comput. Phys. 25 (1977), no. 3, 220–252. MR 490027, DOI 10.1016/0021-9991(77)90100-0
  • C. S. Peskin, The fluid dynamics of heart valves: experimental, theoretical, and computational methods., Annual Review of Fluid Mechanics 14 (1982), 235–259.
  • Alfio Quarteroni, Numerical models for differential problems, MS&A. Modeling, Simulation and Applications, vol. 16, Springer, Cham, 2017. Third edition of [ MR3183828]. MR 3702005, DOI 10.1007/978-3-319-49316-9
  • Alfio Quarteroni, Luca Dede’, Andrea Manzoni, and Christian Vergara, Mathematical modelling of the human cardiovascular system, Cambridge Monographs on Applied and Computational Mathematics, vol. 33, Cambridge University Press, Cambridge, 2019. Data, numerical approximation, clinical applications. MR 3967732, DOI 10.1017/9781108616096
  • Alfio Quarteroni, Andrea Manzoni, and Federico Negri, Reduced basis methods for partial differential equations, Unitext, vol. 92, Springer, Cham, 2016. An introduction; La Matematica per il 3+2. MR 3379913, DOI 10.1007/978-3-319-15431-2
  • A. Quarteroni, R. Sacco, and F. Saleri, Numerical Mathematics, vol. 37, Springer Science & Business Media, 2010.
  • Alfio Quarteroni and Alberto Valli, Numerical approximation of partial differential equations, Springer Series in Computational Mathematics, vol. 23, Springer-Verlag, Berlin, 1994. MR 1299729, DOI 10.1007/978-3-540-85268-1
  • A. Quarteroni, A. Veneziani, and C. Vergara, Geometric multiscale modeling of the cardiovascular system, between theory and practice, Comput. Methods Appl. Mech. Engrg. 302 (2016), 193–252. MR 3461111, DOI 10.1016/j.cma.2016.01.007
  • F. Regazzoni, Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics, Ph.D. thesis, Politecnico di Milano, 2020.
  • F. Regazzoni, L. Dedè, and A. Quarteroni, Active contraction of cardiac cells: a reduced model for sarcomere dynamics with cooperative interactions, Biomechanics and Modeling in Mechanobiology 17 (2018), 1663–1686.
  • F. Regazzoni, L. Dedè, and A. Quarteroni, Biophysically detailed mathematical models of multiscale cardiac active mechanics, PLOS Computational Biology 16 (2020), no. 10, e1008294.
  • F. Regazzoni, L. Dedè, and A. Quarteroni, Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics, Comput. Methods Appl. Mech. Engrg. 370 (2020), 113268, 30. MR 4122006, DOI 10.1016/j.cma.2020.113268
  • Francesco Regazzoni, Luca Dedè, and Alfio Quarteroni, Active force generation in cardiac muscle cells: mathematical modeling and numerical simulation of the actin-myosin interaction, Vietnam J. Math. 49 (2021), no. 1, 87–118. MR 4236966, DOI 10.1007/s10013-020-00433-z
  • F. Regazzoni, M. Salvador, P. C. Africa, M. Fedele, L. Dede’, and A. Quarteroni, A cardiac electromechanics model coupled with a lumped parameters model for closed-loop blood circulation. Part I: Model derivation, arXiv preprint arXiv:2011.15040 (2020).
  • F. Regazzoni, L. Dedè, and A. Quarteroni, A cardiac electromechanics model coupled with a lumped parameters model for closed-loop blood circulation. Part II: Numerical approximation, arXiv preprint arXiv:2011.15051 (2020).
  • J. J. Rice and P. P. de Tombe, Approaches to modeling crossbridges and calcium-dependent activation in cardiac muscle, Progress in Biophysics and Molecular Biology 85 (2004), no. 2, 179–195.
  • J. J. Rice, G. Stolovitzky, Y. Tu, and P. P. de Tombe, Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions, Biophysical Journal 84 (2003), no. 2, 897–909.
  • J. J. Rice, F. Wang, D. M. Bers, and P. P. de Tombe, Approximate model of cooperative activation and crossbridge cycling in cardiac muscle using ordinary differential equations, Biophysical Journal 95 (2008), no. 5, 2368–2390.
  • J. J. Rice, R. L. Winslow, and W. C. Hunter, Comparison of putative cooperative mechanisms in cardiac muscle: length dependence and dynamic responses, American Journal of Physiology-Heart and Circulatory Physiology 276 (1999), no. 5, H1734–H1754.
  • F. B. Sachse, K. G. Glänzel, and G. Seemann, Modeling of protein interactions involved in cardiac tension development, Internat. J. Bifur. Chaos Appl. Sci. Engrg. 13 (2003), no. 12, 3561–3578. Virtual tissue engineering of the heart. MR 2056733, DOI 10.1142/S0218127403008855
  • Matteo Salvador, Luca Dede’, and Alfio Quarteroni, An intergrid transfer operator using radial basis functions with application to cardiac electromechanics, Comput. Mech. 66 (2020), no. 2, 491–511. MR 4124980, DOI 10.1007/s00466-020-01861-x
  • N. P. Smith, D. P. Nickerson, E. J. Crampin, and P. J. Hunter, Multiscale computational modelling of the heart, Acta Numer. 13 (2004), 371–431. MR 2249149, DOI 10.1017/S0962492904000200
  • S. Stella, C. Vergara, M. Maines, D. Catanzariti, P. C. Africa, C. Demattè, M. Centonze, F. Nobile, M. Del Greco, and A. Quarteroni, Integration of activation maps of epicardial veins in computational cardiac electrophysiology, Computers in Biology and Medicine 127 (2020), 104047.
  • S. Sugiura, T. Washio, A. Hatano, J. Okada, H. Watanabe, and T. Hisada, Multi-scale simulations of cardiac electrophysiology and mechanics using the university of tokyo heart simulator, Progress in Biophysics and Molecular Biology 110 (2012), no. 2, 380–389.
  • Joakim Sundnes, Glenn Terje Lines, Xing Cai, Bjørn Fredrik Nielsen, Kent-Andre Mardal, and Aslak Tveito, Computing the electrical activity in the heart, Monographs in Computational Science and Engineering, vol. 1, Springer-Verlag, Berlin, 2006. MR 2258456
  • Anna Tagliabue, Luca Dedè, and Alfio Quarteroni, Complex blood flow patterns in an idealized left ventricle: a numerical study, Chaos 27 (2017), no. 9, 093939, 26. MR 3705219, DOI 10.1063/1.5002120
  • A. Tagliabue, L. Dedè, and A. Quarteroni, Fluid dynamics of an idealized left ventricle: the extended Nitsche’s method for the treatment of heart valves as mixed time varying boundary conditions, Internat. J. Numer. Methods Fluids 85 (2017), no. 3, 135–164. MR 3688092, DOI 10.1002/fld.4375
  • K. H. W. J. Ten Tusscher and A. V. Panfilov, Alternans and spiral breakup in a human ventricular tissue model, American Journal of Physiology–Heart and Circulatory Physiology 291 (2006), no. 3, H1088–H1100.
  • N. A. Trayanova, Whole-heart modeling applications to cardiac electrophysiology and electromechanics, Circulation Research 108 (2011), 113–128.
  • Lloyd N. Trefethen and David Bau III, Numerical linear algebra, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 1997. MR 1444820, DOI 10.1137/1.9780898719574
  • T. P. Usyk, I. J. LeGrice, and A. D. McCulloch, Computational model of three-dimensional cardiac electromechanics, Computing and Visualization in Science 4 (2002), no. 4, 249–257.
  • Marco Veneroni, Reaction-diffusion systems for the macroscopic bidomain model of the cardiac electric field, Nonlinear Anal. Real World Appl. 10 (2009), no. 2, 849–868. MR 2474265, DOI 10.1016/j.nonrwa.2007.11.008
  • E. J. Vigmond, C. Clements, D. M. McQueen, and C. S. Peskin, Effect of bundle branch block on cardiac output: a whole heart simulation study, Progress in Biophysics and Molecular Biology 97 (2008), no. 2-3, 520–542.
  • T. Washio, J. Okada, S. Sugiura, and T. Hisada, Approximation for cooperative interactions of a spatially-detailed cardiac sarcomere model, Cellular and Molecular Bioengineering 5 (2012), no. 1, 113–126.
  • Takumi Washio, Jun-ichi Okada, Akihito Takahashi, Kazunori Yoneda, Yoshimasa Kadooka, Seiryo Sugiura, and Toshiaki Hisada, Multiscale heart simulation with cooperative stochastic cross-bridge dynamics and cellular structures, Multiscale Model. Simul. 11 (2013), no. 4, 965–999. MR 3111652, DOI 10.1137/120892866
  • Takumi Washio, Kazunori Yoneda, Jun-ichi Okada, Taro Kariya, Seiryo Sugiura, and Toshiaki Hisada, Ventricular fiber optimization utilizing the branching structure, Int. J. Numer. Methods Biomed. Eng. 32 (2016), no. 7, e02753, 34. MR 3520705, DOI 10.1002/cnm.2753
Similar Articles
  • Retrieve articles in Bulletin of the American Mathematical Society with MSC (2020): 65-02
  • Retrieve articles in all journals with MSC (2020): 65-02
Additional Information
  • Alfio Quarteroni
  • Affiliation: MOX–Dipartimento di Matematica, Politecnico di Milano, Milano, Italy; and Mathematics Institute, École Polytechnique Fédérale de Lausanne, Switzerland
  • ORCID: 0000-0002-5947-6885
  • Email: alfio.quarteroni@polimi.it
  • Luca Dedè
  • Affiliation: MOX–Dipartimento di Matematica, Politecnico di Milano, Milano, Italy
  • MR Author ID: 771823
  • Email: luca.dede@polimi.it
  • Francesco Regazzoni
  • Affiliation: MOX–Dipartimento di Matematica, Politecnico di Milano, Milano, Italy
  • MR Author ID: 1096619
  • ORCID: 0000-0002-4207-1400
  • Email: francesco.regazzoni@polimi.it
  • Received by editor(s): December 7, 2020
  • Published electronically: February 23, 2022
  • Additional Notes: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 740132, iHEART—An Integrated Heart Model for the simulation of the cardiac function, P.I., A. Quarteroni)
  • © Copyright 2022 American Mathematical Society
  • Journal: Bull. Amer. Math. Soc. 59 (2022), 371-403
  • MSC (2020): Primary 65-02
  • DOI: https://doi.org/10.1090/bull/1738
  • MathSciNet review: 4437802