- -

Three-dimensional cardiac computational modelling: methods, features and applications

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by


Three-dimensional cardiac computational modelling: methods, features and applications

Show full item record

López Pérez, AD.; Sebastián Aguilar, R.; Ferrero De Loma-Osorio, JM. (2015). Three-dimensional cardiac computational modelling: methods, features and applications. BioMedical Engineering OnLine. 14(35):1-31. https://doi.org/10.1186/s12938-015-0033-5

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/64928

Files in this item

Item Metadata

Title: Three-dimensional cardiac computational modelling: methods, features and applications
Author: López Pérez, Alejandro Daniel Sebastián Aguilar, Rafael Ferrero De Loma-Osorio, José María
UPV Unit: Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà
Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Issued date:
[EN] The combination of computational models and biophysical simulations can help to interpret an array of experimental data and contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac ...[+]
Subjects: Cardiac modelling , Three-dimensional (3D) modelling , Computational modelling , Fibre orientation , Cardiac conduction system (CCS) , Cardiac image segmentation , Biophysical simulation , Personalisation , Patient-specific modelling
Copyrigths: Reconocimiento (by)
BioMedical Engineering OnLine. (issn: 1475-925X )
DOI: 10.1186/s12938-015-0033-5
BioMed Central
Publisher version: http://dx.doi.org/10.1186/s12938-015-0033-5
Project ID:
This work was partially supported by the "VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica" from the Ministerio de Economia y Competitividad of Spain (TIN2012-37546-C03-01 and TIN2011-28067) ...[+]
Type: Artículo


Koushanpour E, Collings W: Validation and dynamic applications of an ellipsoid model of the left ventricle. J Appl Physiol 1966, 21: 1655–61.

Ghista D, Sandler H: An analytic elastic-viscoelastic model for the shape and the forces in the left ventricle. J Biomech 1969, 2: 35–47.

Janz RF, Grimm AF: Finite-Element Model for the Mechanical Behavior of the Left Ventricle: prediction of deformation in the potassium-arrested rat heart. Circ Res 1972, 30: 244–52. [+]
Koushanpour E, Collings W: Validation and dynamic applications of an ellipsoid model of the left ventricle. J Appl Physiol 1966, 21: 1655–61.

Ghista D, Sandler H: An analytic elastic-viscoelastic model for the shape and the forces in the left ventricle. J Biomech 1969, 2: 35–47.

Janz RF, Grimm AF: Finite-Element Model for the Mechanical Behavior of the Left Ventricle: prediction of deformation in the potassium-arrested rat heart. Circ Res 1972, 30: 244–52.

Van den Broek JHJM, Van den Broek MHLM: Application of an ellipsoidal heart model in studying left ventricular contractions. J Biomech 1980, 13: 493–503.

Colli Franzone P, Guerri L, Pennacchio M, Taccardi B: Spread of excitation in 3-D models of the anisotropic cardiac tissue. II. Effects of fiber architecture and ventricular geometry. Math Biosci 1998, 147: 131–71.

Kerckhoffs RCP, Bovendeerd PHM, Kotte JCS, Prinzen FW, Smits K, Arts T: Homogeneity of cardiac contraction despite physiological asynchrony of depolarization: a model study. Ann Biomed Eng 2003, 31: 536–47.

Sermesant M, Moireau P, Camara O, Sainte-Marie J, Andriantsimiavona R, Cimrman R, et al.: Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties. Med Image Anal 2006, 10: 642–56.

Okajima M, Fujino T, Kobayashi T, Yamada K: Computer simulation of the propagation process in excitation of the ventricles. Circ Res 1968, 23: 203–11.

Horan LG, Hand RC, Johnson JC, Sridharan MR, Rankin TB, Flowers NC: A theoretical examination of ventricular repolarization and the secondary T wave. Circ Res 1978, 42: 750–7.

Miller WT, Geselowitz DB: Simulation studies of the electrocardiogram. I. The normal heart. Circ Res 1978, 43: 301–15.

Vetter FJ, McCulloch AD: Three-dimensional analysis of regional cardiac function: a model of rabbit ventricular anatomy. Prog Biophys Mol Biol 1998, 69: 157–83.

Nielsen PMF, LeGrice IJ, Smaill BH, Hunter PJ: Mathematical model of geometry and fibrous structure of the heart. Am J Physiol Heart Circ Physiol 1991, 260: H1365–78.

Stevens C, Remme E, LeGrice I, Hunter P: Ventricular mechanics in diastole: material parameter sensitivity. J Biomech 2003, 36: 737–48.

Aoki M, Okamoto Y, Musha T, Harumi KI: Three-dimensional simulation of the ventricular depolarization and repolarization processes and body surface potentials: normal heart and bundle branch block. IEEE Trans Biomed Eng 1987, 34: 454–62.

Thakor NV, Eisenman LN: Three-dimensional computer model of the heart: fibrillation induced by extrastimulation. Comput Biomed Res 1989, 22: 532–45.

Freudenberg J, Schiemann T, Tiede U, Höhne KH: Simulation of cardiac excitation patterns in a three-dimensional anatomical heart atlas. Comput Biol Med 2000, 30: 191–205.

Trunk P, Mocnik J, Trobec R, Gersak B: 3D heart model for computer simulations in cardiac surgery. Comput Biol Med 2007, 37: 1398–403.

Siregar P, Sinteff JP, Julen N, Le Beux P: An interactive 3D anisotropic cellular automata model of the heart. Comput Biomed Res 1998, 31: 323–47.

Harrild DM, Henriquez CS: A computer model of normal conduction in the human atria. Circ Res 2000, 87: e25–36.

Bodin ON, Kuz’min AV: Synthesis of a realistic model of the surface of the heart. Biomed Eng (NY) 2006, 40: 280–3.

Ruiz-Villa CA, Tobón C, Rodríguez JF, Ferrero JM, Hornero F, Saíz J: Influence of atrial dilatation in the generation of re-entries caused by ectopic activity in the left atrium. Comput Cardiol 2009, 36: 457–60.

Blanc O, Virag N, Vesin JM, Kappenberger L: A computer model of human atria with reasonable computation load and realistic anatomical properties. IEEE Trans Biomed Eng 2001, 48: 1229–37.

Zemlin CW, Herzel H, Ho SY, Panfilov AV: A realistic and efficient model of excitation propagation in the human atria. In Comput Simul Exp Assess Card Electrophysiol. Edited by: Virag N, Kappenberger L, Blanc O. Futura Publishing Company, Inc, Arkmonk, New York; 2001:29–34.

Seemann G, Höper C, Sachse FB, Dössel O, Holden AV, Zhang H: Heterogeneous three-dimensional anatomical and electrophysiological model of human atria. Philos Trans R Soc A Math Phys Eng Sci 2006, 364: 1465–81.

Zhao J, Butters TD, Zhang H, LeGrice IJ, Sands GB, Smaill BH: Image-based model of atrial anatomy and electrical activation: a computational platform for investigating atrial arrhythmia. IEEE Trans Med Imaging 2013, 32: 18–27.

Creswell LL, Wyers SG, Pirolo JS, Perman WH, Vannier MW, Pasque MK: Mathematical modeling of the heart using magnetic resonance imaging. IEEE Trans Med Imaging 1992, 11: 581–9.

Lorange M, Gulrajani RM: A computer heart model incorporating anisotropic propagation: I. Model construction and simulation of normal activation. J Electrocardiol 1993, 26: 245–61.

Winslow RL, Scollan DF, Holmes A, Yung CK, Zhang J, Jafri MS: Electrophysiological modeling of cardiac ventricular function: from cell to organ. Annu Rev Biomed Eng 2000, 2: 119–55.

Virag N, Jacquemet V, Henriquez CS, Zozor S, Blanc O, Vesin JM, et al.: Study of atrial arrhythmias in a computer model based on magnetic resonance images of human atria. Chaos 2002, 12: 754–63.

Helm PA, Tseng HJ, Younes L, McVeigh ER, Winslow RL: Ex vivo 3D diffusion tensor imaging and quantification of cardiac laminar structure. Magn Reson Med 2005, 54: 850–9.

Arevalo HJ, Helm PA, Trayanova NA: Development of a model of the infarcted canine heart that predicts arrhythmia generation from specific cardiac geometry and scar distribution. Comput Cardiol 2008, 35: 497–500.

Plotkowiak M, Rodriguez B, Plank G, Schneider JE, Gavaghan D, Kohl P, et al.: High performance computer simulations of cardiac electrical function based on high resolution MRI datasets. In Int Conf Comput Sci 2008, LNCS 5101. Springer–Verlag, Berlin Heidelberg; 2008:571–80.

Heidenreich EA, Ferrero JM, Doblaré M, Rodríguez JF: Adaptive macro finite elements for the numerical solution of monodomain equations in cardiac electrophysiology. Ann Biomed Eng 2010, 38: 2331–45.

Gurev V, Lee T, Constantino J, Arevalo H, Trayanova NA: Models of cardiac electromechanics based on individual hearts imaging data: Image-based electromechanical models of the heart. Biomech Model Mechanobiol 2011, 10: 295–306.

Deng D, Jiao P, Ye X, Xia L: An image-based model of the whole human heart with detailed anatomical structure and fiber orientation. Comput Math Methods Med 2012, 2012: 16.

Aslanidi OV, Nikolaidou T, Zhao J, Smaill BH, Gilbert SH, Holden AV, et al.: Application of micro-computed tomography with iodine staining to cardiac imaging, segmentation, and computational model development. IEEE Trans Med Imaging 2013, 32: 8–17.

Haddad R, Clarysse P, Orkisz M, Croisille P, Revel D, Magnin IE: A realistic anthropomorphic numerical model of the beating heart. In Funct Imaging Model Heart 2005, LNCS 3504. Springer–Verlag, Berlin Heidelberg; 2005:384–93.

Appleton B, Wei Q, Liu N, Xia L, Crozier S, Liu F, et al.: An electrical heart model incorporating real geometry and motion. In 27th Annu Int Conf Eng Med Biol Soc (IEEE-EMBS 2005). IEEE, Shanghai, China; 2006:345–8.

Niederer S, Rhode K, Razavi R, Smith N: The importance of model parameters and boundary conditions in whole organ models of cardiac contraction. In Funct Imaging Model Heart 2009, LNCS 5528. Springer–Verlag, Berlin Heidelberg; 2009:348–56.

Yang G, Toumoulin C, Coatrieux JL, Shu H, Luo L, Boulmier D: A 3D static heart model from a MSCT data set. In 27th Annu Int Conf IEEE Eng Med Biol Soc (IEEE-EMBS 2005). IEEE, Shangai, China; 2006:5499–502.

Romero D, Sebastian R, Bijnens BH, Zimmerman V, Boyle PM, Vigmond EJ, et al.: Effects of the purkinje system and cardiac geometry on biventricular pacing: a model study. Ann Biomed Eng 2010, 38: 1388–98.

Lorenzo-Valdés M, Sanchez-Ortiz GI, Mohiaddin R, Rueckert D: Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration. In Med Image Comput Comput Assist Interv 2002, LNCS 2488. Springer–Verlag, Berlin Heidelberg; 2002:642–50.

Ordas S, Oubel E, Sebastian R, Frangi AF: Computational anatomy atlas of the heart. In 5th Int Symp Image Signal Process Anal (ISPA 2007). IEEE, Istanbul, Turkey; 2007:338–42.

Burton RAB, Plank G, Schneider JE, Grau V, Ahammer H, Keeling SL, et al.: Three-dimensional models of individual cardiac histoanatomy: tools and challenges. Ann N Y Acad Sci 2006, 1080: 301–19.

Plank G, Burton RAB, Hales P, Bishop M, Mansoori T, Bernabeu MO, et al.: Generation of histo-anatomically representative models of the individual heart: tools and application. Philos Trans R Soc A Math Phys Eng Sci 2009, 367: 2257–92.

Bishop MJ, Plank G, Burton RAB, Schneider JE, Gavaghan DJ, Grau V, et al.: Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function. Am J Physiol - Heart Circ Physiol 2010, 298: H699–718.

Ecabert O, Peters J, Schramm H, Lorenz C, von Berg J, Walker MJ, et al.: Automatic model-based segmentation of the heart in CT images. IEEE Trans Med Imaging 2008, 27: 1189–201.

Ecabert O, Peters J, Walker MJ, Ivanc T, Lorenz C, von Berg J, et al.: Segmentation of the heart and great vessels in CT images using a model-based adaptation framework. Med Image Anal 2011, 15: 863–76.

Schulte RF, Sands GB, Sachse FB, Dössel O, Pullan AJ: Creation of a human heart model and its customisation using ultrasound images. Biomed Tech Eng 2001, 46: 26–8.

Wenk JF, Zhang Z, Cheng G, Malhotra D, Acevedo-Bolton G, Burger M, et al.: First finite element model of the left ventricle with mitral valve: insights into ischemic mitral regurgitation. Ann Thorac Surg 2010, 89: 1546–53.

Frangi AF, Rueckert D, Schnabel JA, Niessen WJ: Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling. IEEE Trans Med Imaging 2002, 21: 1151–66.

Hoogendoorn C, Duchateau N, Sánchez-Quintana D, Whitmarsh T, Sukno FM, De Craene M, et al.: A high-resolution atlas and statistical model of the human heart from multislice CT. IEEE Trans Med Imaging 2013, 32: 28–44.

Vadakkumpadan F, Rantner LJ, Tice B, Boyle P, Prassl AJ, Vigmond E, et al.: Image-based models of cardiac structure with applications in arrhythmia and defibrillation studies. J Electrocardiol 2009, 42: 157.

Perperidis D, Mohiaddin R, Rueckert D: Construction of a 4D statistical atlas of the cardiac anatomy and its use in classification. In Med Image Comput Comput Interv 2005, LNCS 3750. Springer–Verlag, Berlin Heidelberg; 2005:402–10.

Lötjönen J, Kivistö S, Koikkalainen J, Smutek D, Lauerma K: Statistical shape model of atria, ventricles and epicardium from short- and long-axis MR images. Med Image Anal 2004, 8: 371–86.

Lorenz C, von Berg J: A comprehensive shape model of the heart. Med Image Anal 2006, 10: 657–70.

Mansoori T, Plank G, Burton R, Schneider J, Khol P, Gavaghan D, et al.: An iterative method for registration of high-resolution cardiac histoanatomical and MRI images. In 4th IEEE Int Symp Biomed Imaging: From Nano to Macro (ISBI 2007). IEEE, Arlington, VA (USA); 2007:572–5.

Gibb M, Burton RAB, Bollensdorff C, Afonso C, Mansoori T, Schotten U, et al.: Resolving the three-dimensional histology of the heart. In Comput Methods Syst Biol - Lect Notes Comput Sci 7605. Springer, Berlin Heidelberg; 2012:2–16.

Burton RAB, Lee P, Casero R, Garny A, Siedlecka U, Schneider JE, et al.: Three-dimensional histology: tools and application to quantitative assessment of cell-type distribution in rabbit heart. Europace 2014,16(Suppl 4):iv86–95.

Niederer SA, Shetty AK, Plank G, Bostock J, Razavi R, Smith NP, et al.: Biophysical modeling to simulate the response to multisite left ventricular stimulation using a quadripolar pacing lead. Pacing Clin Electrophysiol 2012, 35: 204–14.

Weese J, Groth A, Nickisch H, Barschdorf H, Weber FM, Velut J, et al.: Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations. Med Biol Eng Comput 2013, 51: 1209–19.

Gibb M, Bishop M, Burton R, Kohl P, Grau V, Plank G, et al.: The role of blood vessels in rabbit propagation dynamics and cardiac arrhythmias. In Funct Imaging Model Heart - FIMH 2009, LNCS 5528. Springer, Berlin Heidelberg; 2009:268–76.

Prassl AJ, Kickinger F, Ahammer H, Grau V, Schneider JE, Hofer E, et al.: Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems. IEEE Trans Biomed Eng 2009, 56: 1318–30.

Dux-Santoy L, Sebastian R, Felix-Rodriguez J, Ferrero JM, Saiz J: Interaction of specialized cardiac conduction system with antiarrhythmic drugs: a simulation study. IEEE Trans Biomed Eng 2011, 58: 3475–8.

Lamata P, Niederer S, Nordsletten D, Barber DC, Roy I, Hose DR, et al.: An accurate, fast and robust method to generate patient-specific cubic Hermite meshes. Med Image Anal 2011, 15: 801–13.

Pathmanathan P, Cooper J, Fletcher A, Mirams G, Murray P, Osborne J, et al.: A computational study of discrete mechanical tissue models. Phys Biol 2009, 6: 036001.

Niederer SA, Kerfoot E, Benson AP, Bernabeu MO, Bernus O, Bradley C, et al.: Verification of cardiac tissue electrophysiology simulators using an N-version benchmark. Philos Trans R Soc A Math Phys Eng Sci 2011, 369: 4331–51.

Ten Tusscher KHWJ, Panfilov AV: Cell model for efficient simulation of wave propagation in human ventricular tissue under normal and pathological conditions. Phys Med Biol 2006, 51: 6141–56.

LeGrice I, Smaill B, Chai L, Edgar S, Gavin J, Hunter P: Laminar structure of the heart: ventricular myocyte arrangement and connective tissue architecture in the dog. Am J Physiol Heart Circ Physiol 1995, 269: H571–82.

Anderson RH, Smerup M, Sanchez-Quintana D, Loukas M, Lunkenheimer PP: The three-dimensional arrangement of the myocytes in the ventricular walls. Clin Anat 2009, 22: 64–76.

Clerc L: Directional differences of impulse spread in trabecular muscle from mammalian heart. J Physiol 1976, 255: 335–46.

Streeter DD Jr, Spotnitz HM, Patel DP, Ross J Jr, Sonnenblick EH: Fiber orientation in the canine left ventricle during diastole and systole. Circ Res 1969, 24: 339–47.

Scollan D, Holmes A, Winslow R, Forder J: Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. Am J Physiol Heart Circ Physiol 1998, 275: H2308–18.

Hsu EW, Muzikant AL, Matulevicius SA, Penland RC, Henriquez CS: Magnetic resonance myocardial fiber-orientation mapping with direct histological correlation. Am J Physiol Heart Circ Physiol 1998, 274: H1627–34.

Holmes AA, Scollan DF, Winslow RL: Direct histological validation of diffusion tensor MRI in formaldehyde-fixed myocardium. Magn Reson Med 2000, 44: 157–61.

Sermesant M, Forest C, Pennec X, Delingette H, Ayache N: Deformable biomechanical models: application to 4D cardiac image analysis. Med Image Anal 2003, 7: 475–88.

Peyrat JM, Sermesant M, Pennec X, Delingette H, Xu C, McVeigh ER, et al.: A computational framework for the statistical analysis of cardiac diffusion tensors: application to a small database of canine hearts. IEEE Trans Med Imaging 2007, 26: 1500–14.

Toussaint N, Sermesant M, Stoeck CT, Kozerke S, Batchelor PG: In vivo human 3D cardiac fibre architecture: reconstruction using curvilinear interpolation of diffusion tensor images. Med Image Comput Comput Assist Interv 2010,13(Pt 1):418–25.

Toussaint N, Stoeck CT, Schaeffter T, Kozerke S, Sermesant M, Batchelor PG: In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing. Med Image Anal 2013, 17: 1243–55.

Bishop MJ, Hales P, Plank G, Gavaghan DJ, Scheider J, Grau V: Comparison of rule-based and DTMRI-derived fibre architecture in a whole rat ventricular computational model. In Funct Imaging Model Heart 2009, LNCS 5528. Springer–Verlag, Berlin Heidelberg; 2009:87–96.

Bayer JD, Blake RC, Plank G, Trayanova NA: A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann Biomed Eng 2012, 40: 2243–54.

Dobrzynski H, Anderson RH, Atkinson A, Borbas Z, D’Souza A, Fraser JF, et al.: Structure, function and clinical relevance of the cardiac conduction system, including the atrioventricular ring and outflow tract tissues. Pharmacol Ther 2013, 139: 260–88.

Tranum-Jensen J, Wilde AA, Vermeulen JT, Janse MJ: Morphology of electrophysiologically identified junctions between Purkinje fibers and ventricular muscle in rabbit and pig hearts. Circ Res 1991, 69: 429–37.

Boyle PM, Deo M, Plank G, Vigmond EJ: Purkinje-mediated effects in the response of quiescent ventricles to defibrillation shocks. Ann Biomed Eng 2010, 38: 456–68.

Behradfar E, Nygren A, Vigmond EJ: The role of Purkinje-myocardial coupling during ventricular arrhythmia: a modeling study. PLoS One 2014., 9: Article ID e88000

DiFrancesco D, Noble D: A model of cardiac electrical activity incorporating ionic pumps and concentration changes. Philos Trans R Soc B Biol Sci 1985, 307: 353–98.

Stewart P, Aslanidi OV, Noble D, Noble PJ, Boyett MR, Zhang H: Mathematical models of the electrical action potential of Purkinje fibre cells. Philos Trans R Soc A Math Phys Eng Sci 2009, 367: 2225–55.

Li P, Rudy Y: A model of canine purkinje cell electrophysiology and Ca(2+) cycling: rate dependence, triggered activity, and comparison to ventricular myocytes. Circ Res 2011, 109: 71–9.

Chinchapatnam P, Rhode KS, Ginks M, Mansi T, Peyrat JM, Lambiase P, et al.: Estimation of volumetric myocardial apparent conductivity from endocardial electro-anatomical mapping. In 31st Annu Int Conf IEEE Eng Med Biol Soc (EMBC 2009). IEEE, Minneapolis, MN (USA); 2009:2907–10.

Durrer D, Van Dam RT, Freud GE, Janse MJ, Meijler FL, Arzbaecher RC: Total excitation of the isolated human heart. Circulation 1970, 41: 899–912.

Pollard AE, Barr RC: Computer simulations of activation in an anatomically based model of the human ventricular conduction system. IEEE Trans Biomed Eng 1991, 38: 982–96.

Abboud S, Berenfeld O, Sadeh D: Simulation of high-resolution QRS complex using a ventricular model with a fractal conduction system. Effects of ischemia on high-frequency QRS potentials. Circ Res 1991, 68: 1751–60.

Sebastian R, Zimmerman V, Romero D, Sanchez-Quintana D, Frangi AF: Characterization and modeling of the peripheral cardiac conduction system. IEEE Trans Med Imaging 2013, 32: 45–55.

Bordas R, Gillow K, Lou Q, Efimov IR, Gavaghan D, Kohl P, et al.: Rabbit-specific ventricular model of cardiac electrophysiological function including specialized conduction system. Prog Biophys Mol Biol 2011, 107: 90–100.

Stephenson RS, Boyett MR, Hart G, Nikolaidou T, Cai X, Corno AF, et al.: Contrast enhanced micro-computed tomography resolves the 3-dimensional morphology of the cardiac conduction system in mammalian hearts. PLoS One 2012., 7: Article ID e35299

Berenfeld O, Jalife J: Purkinje-Muscle reentry as a mechanism of polymorphic ventricular arrhythmias in a 3-dimensional model of the ventricles. Circ Res 1998, 82: 1063–77.

Azzouzi A, Coudière Y, Turpault R, Zemzemi N: A mathematical model of the Purkinje-muscle junctions. Math Biosci Eng MBE 2011, 8: 915–30.

Dux-Santoy L, Sebastian R, Rodriguez JF, Ferrero JM: Modeling the different sections of the cardiac conduction system to obtain realistic electrocardiograms. In 35th Annu Int Conf IEEE Eng Med Biol Soc (EMBC 2013). IEEE, Osaka, Japan; 2013:6846–9.

Cardenes R, Sebastian R, Berruezo A, Camara O: Inverse estimation of ventricular Purkinje tree pathways from sequences of depolarization. In Comput Cardiol. Volume 41. IEEE, Cambridge, Massachusetts (USA); 2014:677–80.

Palamara S, Vergara C, Catanzariti D, Faggiano E, Pangrazzi C, Centonze M, et al.: Computational generation of the Purkinje network driven by clinical measurements: the case of pathological propagations. Int J Numer Method Biomed Eng 2014, 30: 1558–77.

Moe GK, Rheinboldt WC, Abildskov JA: A computer model of atrial fibrillation. Am Heart J 1964, 67: 200–20.

Hodgkin AL, Huxley AF: A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 1952, 117: 500–44.

Fink M, Niederer SA, Cherry EM, Fenton FH, Koivumäki JT, Seemann G, et al.: Cardiac cell modelling: Observations from the heart of the cardiac physiome project. Prog Biophys Mol Biol 2011, 104: 2–21.

Rudy Y, Silva JR: Computational biology in the study of cardiac ion channels and cell electrophysiology. Q Rev Biophys 2006, 39: 57–116.

Sakmann B, Neher E: Patch clamp techniques for studying ionic channels in excitable membranes. Annu Rev Physiol 1984, 41: 455–72.

Maleckar MM, Greenstein JL, Giles WR, Trayanova NA: K+ current changes account for the rate dependence of the action potential in the human atrial myocyte. Am J Physiol Heart Circ Physiol 2009, 297: H1398–410.

O’Hara T, Virág L, Varró A, Rudy Y: Simulation of the undiseased human cardiac ventricular action potential: model formulation and experimental validation. PLoS Comput Biol 2011., 7: Article ID e1002061

Roberts BN, Yang PC, Behrens SB, Moreno JD, Clancy CE: Computational approaches to understand cardiac electrophysiology and arrhythmias. Am J Physiol Heart Circ Physiol 2012, 303: H766–83.

Liu DW, Gintant GA, Antzelevitch C: Ionic bases for electrophysiological distinctions among epicardial, midmyocardial, and endocardial myocytes from the free wall of the canine left ventricle. Circ Res 1993, 72: 671–87.

Szentadrassy N, Banyasz T, Biro T, Szabo G, Toth BI, Magyar J, et al.: Apico-basal inhomogeneity in distribution of ion channels in canine and human ventricular myocardium. Cardiovasc Res 2005, 65: 851–60.

Volders PG, Sipido KR, Carmeliet E, Spätjens RL, Wellens HJ, Vos MA: Repolarizing K+ currents ITO1 and IKs are larger in right than left canine ventricular midmyocardium. Circulation 1999, 99: 206–10.

Tobón C, Rodríguez JF, Ferrero JM Jr, Hornero F, Saiz J: Dominant frequency and organization index maps in a realistic three-dimensional computational model of atrial fibrillation. Europace 2012, 14: v25–32.

Tobón C, Ruiz-Villa CA, Heidenreich E, Romero L, Hornero F, Saiz J: A three-dimensional human atrial model with fiber orientation. Electrograms and arrhythmic activation patterns relationship. PLoS One 2013., 8: Article ID e50883

Roth BJ: The electrical potential produced by a strand of cardiac muscle: a bidomain analysis. Ann Biomed Eng 1988, 16: 609–37.

FitzHugh R: Impulses and physiological states in theoretical models of nerve membrane. Biophys J 1961, 1: 445–66.

Aliev RR, Panfilov AV: Modeling of heart excitation patterns caused by a local inhomogeneity. J Theor Biol 1996, 181: 33–40.

Mitchell CC, Schaeffer DG: A two-current model for the dynamics of cardiac membrane. Bull Math Biol 2003, 65: 767–93.

Fenton F, Karma A: Vortex dynamics in three-dimensional continuous myocardium with fiber rotation: filament instability and fibrillation. Chaos 1998, 8: 20–47.

Bueno-Orovio A, Cherry EM, Fenton FH: Minimal model for human ventricular action potentials in tissue. J Theor Biol 2008, 253: 544–60.

Colli Franzone P, Guerri L, Rovida S: Wavefront propagation in an activation model of the anisotropic cardiac tissue: asymptotic analysis and numerical simulations. J Math Biol 1990, 28: 121–76.

Keener JP: An eikonal-curvature equation for action potential propagation in myocardium. J Math Biol 1991, 29: 629–51.

Relan J, Chinchapatnam P, Sermesant M, Rhode K, Ginks M, Delingette H, et al.: Coupled personalization of cardiac electrophysiology models for prediction of ischaemic ventricular tachycardia. Interface Focus 2011, 1: 396–407.

Camara O, Sermesant M, Lamata P, Wang L, Pop M, Relan J, et al.: Inter-model consistency and complementarity: Learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology. Prog Biophys Mol Biol 2011, 107: 122–33.

Rice JJ, Wang F, Bers DM, de Tombe PP: Approximate model of cooperative activation and crossbridge cycling in cardiac muscle using ordinary differential equations. Biophys J 2008, 95: 2368–90.

Mullins PD, Bondarenko VE: A mathematical model of the mouse ventricular myocyte contraction. PLoS One 2013, 8: e63141.

Trayanova NA, Rice JJ: Cardiac electromechanical models: from cell to organ. Front Physiol 2011, 2: Article 43.

Williams GSB, Smith GD, Sobie EA, Jafri MS: Models of cardiac excitation-contraction coupling in ventricular myocytes. Math Biosci 2010, 226: 1–15.

Jafri MS: Models of excitation-contraction coupling in cardiac ventricular myocytes. In Bioinforma Drug Discov Methods Mol Biol. Springer Science + Business Media, New York; 2012:309–35.

Pfeiffer ER, Tangney JR, Omens JH, McCulloch AD: Biomechanics of cardiac electromechanical coupling and mechanoelectric feedback. J Biomech Eng 2014, 136: 021007–1–021007–11.

Quinn TA, Kohl P, Ravens U: Cardiac mechano-electric coupling research: fifty years of progress and scientific innovation. Prog Biophys Mol Biol 2014, 115: 71–5.

Craelius W, Chen V, El-Sherif N: Stretch activated ion channels in ventricular myocytes. Biosci Rep 1988, 8: 407–14.

Kohl P, Hunter P, Noble D: Stretch-induced changes in heart rate and rhythm: clinical observations, experiments and mathematical models. Prog Biophys Mol Biol 1999, 71: 91–138.

Kohl P, Sachs F, Franz MR: Cardiac Mechano-Electric Feedback and Arrhytmias: From Pipette to Patient. Elsevier Health Sciences, Philadelphia; 2005.

Cabo C, Boyden PA: Electrical remodeling of the epicardial border zone in the canine infarcted heart: a computational analysis. Am J Physiol Heart Circ Physiol 2003, 284: H372–84.

Clancy CE, Rudy Y: Cellular consequences of HERG mutations in the long QT syndrome: precursors to sudden cardiac death. Cardiovasc Res 2001, 50: 301–13.

Marks AR: Calcium cycling proteins and heart failure: mechanisms and therapeutics. J Clin Invest 2013, 123: 46–52.

Hansen DE, Craig CS, Hondeghem LM: Stretch-induced arrhythmias in the isolated canine ventricle. Evidence for the importance of mechanoelectrical feedback. Circulation 1990, 81: 1094–105.

Wang Z, Taylor LK, Denney WD, Hansen DE: Initiation of ventricular extrasystoles by myocardial stretch in chronically dilated and failing canine left ventricle. Circulation 1994, 90: 2022–31.

Trayanova NA, Constantino J, Gurev V: Models of stretch-activated ventricular arrhythmias. J Electrocardiol 2010, 43: 476–85.

Reumann M, Farina D, Miri R, Lurz S, Osswald B, Dössel O: Computer model for the optimization of AV and VV delay in cardiac resynchronization therapy. Med Biol Eng Comput 2007, 45: 845–54.

Wu M-T, Tseng W-YI SM-YM, Liu C-P, Chiou K-R, Wedeen VJ, Reese TG, et al.: Diffusion tensor magnetic resonance imaging mapping the fiber architecture remodeling in human myocardium after infarction: correlation with viability and wall motion. Circulation 2006, 114: 1036–45.

Rutherford SL, Trew ML, Sands GB, LeGrice IJ, Smaill BH: High-resolution 3-dimensional reconstruction of the infarct border zone: impact of structural remodeling on electrical activation. Circ Res 2012, 111: 301–11.

Ashikaga H, Arevalo H, Vadakkumpadan F, Blake RC, Bayer JD, Nazarian S, et al.: Feasibility of image-based simulation to estimate ablation target in human ventricular arrhythmia. Heart Rhythm 2013, 10: 1109–16.

Martos R, Baugh J, Ledwidge M, O’Loughlin C, Conlon C, Patle A, et al.: Diastolic heart failure: evidence of increased myocardial collagen turnover linked to diastolic dysfunction. Circulation 2007, 115: 888–95.

Ten Tusscher KHWJ, Panfilov AV: Influence of diffuse fibrosis on wave propagation in human ventricular tissue. Europace 2007,9(Suppl 6):vi38–45.

Kim RJ, Fieno DS, Parrish TB, Harris K, Chen EL, Simonetti O, et al.: Relationship of MRI delayed contrast enhancement to irreversible injury, infarct age, and contractile function. Circulation 1999, 100: 1992–2002.

Sebastian R, Zimmerman V, Sukno F, Bijnens BH, Frangi AF: Cardiac modelling for pathophysiology research and clinical applications. The need for an automated pipeline. In World Congr Med Phys Biomed Eng 2009. Springer, Berlin Heidelberg; 2010:2207–10.

Heidenreich EA, Gaspar FJ, Ferrero JM, Rodríguez JF: Compact schemes for anisotropic reaction-diffusion equations with adaptive time step. Int J Numer Methods Eng 2010, 82: 1022–43.

Mewton N, Liu CY, Croisille P, Bluemke D, Lima JAC: Assessment of myocardial fibrosis with cardiovascular magnetic resonance. J Am Coll Cardiol 2011, 57: 891–903.

Dass S, Suttie JJ, Piechnik SK, Ferreira VM, Holloway CJ, Banerjee R, et al.: Myocardial tissue characterization using magnetic resonance noncontrast T1 mapping in hypertrophic and dilated cardiomyopathy. Circ Cardiovasc Imaging 2012, 5: 726–33.

Krueger MW, Seemann G, Rhode K, Keller DUJ, Schilling C, Arujuna A, et al.: Personalization of atrial anatomy and electrophysiology as a basis for clinical modeling of radio-frequency ablation of atrial fibrillation. IEEE Trans Med Imaging 2013, 32: 73–84.

Krueger MW, Schulze WHW, Rhode KS, Razavi R, Seemann G, Dössel O: Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology. Med Biol Eng Comput 2013, 51: 1251–60.

Sermesant M, Peyrat J-M, Chinchapatnam P, Billet F, Mansi T, Rhode K, et al.: Toward patient-specific myocardial models of the heart. Heart Fail Clin 2008, 4: 289–301.

Konukoglu E, Relan J, Cilingir U, Menze BH, Chinchapatnam P, Jadidi A, et al.: Efficient probabilistic model personalization integrating uncertainty on data and parameters: Application to eikonal-diffusion models in cardiac electrophysiology. Prog Biophys Mol Biol 2011, 107: 134–46.

Lambiase PD, Rinaldi A, Hauck J, Mobb M, Gill JS, Bucknall CA: Non-contact left ventricular endocardial mapping in cardiac resynchronisation therapy. Heart 2004, 90: 44–51.

Perez-David E, Arenal A, Rubio-Guivernau JL, del Castillo R, Atea L, Arbelo E, et al.: Noninvasive identification of ventricular tachycardia-related conducting channels using contrast-enhanced magnetic resonance imaging in patients with chronic myocardial infarction: comparison of signal intensity scar mapping and endocardial voltage mappin. J Am Coll Cardiol 2011, 57: 184–94.

Fernández-Armenta J, Berruezo A, Andreu D, Camara O, Silva E, Serra L, et al.: Three-dimensional architecture of scar and conducting channels based on high resolution ce-CMR: insights for ventricular tachycardia ablation. Circ Arrhythm Electrophysiol 2013, 6: 528–37.

Petitjean C, Dacher JN: A review of segmentation methods in short axis cardiac MR images. Med Image Anal 2011, 15: 169–84.

Frangi AF, Niessen WJ, Viergever MA: Three-dimensional modeling for functional analysis of cardiac images: a review. IEEE Trans Med Imaging 2001, 20: 2–25.

Sermesant M, Delingette H, Ayache N: An electromechanical model of the heart for image analysis and simulation. IEEE Trans Med Imaging 2006, 25: 612–25.

Mitchell S, Lelieveldt B, van der Geest R, Bosch J, Reiber J, Sonka M: Segmentation of cardiac MR images: An active appearance model approach. In Proc SPIE 3979, Med Imaging 2000: Image Process. Edited by: Hanson KM. SPIE Digital Library, San Diego, CA (USA); 2000:224–34.

Mitchell SC, Bosch JG, Lelieveldt BPF, van der Geest RJ, Reiber JHC, Sonka M: 3-D active appearance models: segmentation of cardiac MR and ultrasound images. IEEE Trans Med Imaging 2002, 21: 1167–78.

Ordas S, Boisrobert L, Huguet M, Frangi AF: Active shape models with invariant optimal features (IOF-ASM) application to cardiac MRI segmentation. In Comput Cardiol. Volume 30. IEEE, Thessaloniki, Greece; 2003:633–6.

Young AA, Frangi AF: Computational cardiac atlases: from patient to population and back. Exp Physiol 2009, 94: 578–96.

Fonseca CG, Backhaus M, Bluemke DA, Britten RD, Chung JDO, Cowan BR, et al.: The Cardiac Atlas Project - an imaging database for computational modeling and statistical atlases of the heart. Bioinformatics 2011, 27: 2288–95.

Janse MJ, Kleber AG: Electrophysiological changes and ventricular arrhythmias in the early phase of regional myocardial ischemia. Circ Res 1981, 49: 1069–81.

Ferrero JM, Trenor B, Romero L: Multiscale computational analysis of the bioelectric consequences of myocardial ischaemia and infarction. Europace 2014, 16: 405–15.

Ferrero JM Jr, Sáiz J, Ferrero JM, Thakor NV: Simulation of action potentials from metabolically impaired cardiac myocytes: role of ATP-sensitive K+ current. Circ Res 1996, 79: 208–21.

Ferrero JM Jr, Trénor B, Rodríguez B, Sáiz J: Electrical activity and reentry during acute regional myocardial ischemia: insights from simulations. Int J Bifurc Chaos 2003, 13: 3703–15.

Shaw RM, Rudy Y: Electrophysiologic effects of acute myocardial ischemia: a theoretical study of altered cell excitability and action potential duration. Cardiovasc Res 1997, 35: 256–72.

Trénor B, Romero L, Ferrero JM, Sáiz J, Moltó G, Alonso JM: Vulnerability to reentry in a regionally ischemic tissue: a simulation study. Ann Biomed Eng 2007, 35: 1756–70.

Tice BM, Rodríguez B, Eason J, Trayanova N: Mechanistic investigation into the arrhythmogenic role of transmural heterogeneities in regional ischaemia phase 1A. Europace 2007,9(Suppl 6):vi46–58.

Romero L, Trénor B, Alonso JM, Tobón C, Saiz J, Ferrero JM Jr: The relative role of refractoriness and source-sink relationship in reentry generation during simulated acute ischemia. Ann Biomed Eng 2009, 37: 1560–71.

Heidenreich EA, Ferrero JM, Rodríguez JF: Modeling the human heart under acute ischemia. In Patient-Specific Comput Model. Volume 5. Edited by: Calvo Lopez B, Peña E. Dordrecht: Springer, Netherlands; 2012:81–103. [Lecture Notes in Computational Vision and Biomechanics]

Rodríguez B, Tice BM, Eason JC, Aguel F, Ferrero JM Jr, Trayanova N: Effect of acute global ischemia on the upper limit of vulnerability: a simulation study. Am J Physiol Heart Circ Physiol 2004, 286: H2078–88.

Lazzara R, Scherlag BJ: Electrophysiologic basis for arrhythmias in ischemic heart disease. Am J Cardiol 1984, 53: B1–7.

Vigmond E, Vadakkumpadan F, Gurev V, Arevalo H, Deo M, Plank G, et al.: Towards predictive modelling of the electrophysiology of the heart. Exp Physiol 2009, 94: 563–77.

Rantner LJ, Arevalo HJ, Constantino JL, Efimov IR, Plank G, Trayanova NA: Three-dimensional mechanisms of increased vulnerability to electric shocks in myocardial infarction: altered virtual electrode polarizations and conduction delay in the peri-infarct zone. J Physiol 2012, 590: 4537–51.

Pop M, Sermesant M, Mansi T, Crystal E, Ghate S, Peyrat JM, et al.: Correspondence between simple 3-D MRI-based computer models and in-vivo EP measurements in swine with chronic infarctions. IEEE Trans Biomed Eng 2011, 58: 3483–6.

Ng J, Jacobson JT, Ng JK, Gordon D, Lee DC, Carr JC, et al.: Virtual electrophysiological study in a 3-dimensional cardiac magnetic resonance imaging model of porcine myocardial infarction. J Am Coll Cardiol 2012, 60: 423–30.

Arevalo H, Plank G, Helm P, Halperin H, Trayanova N: Tachycardia in post-infarction hearts: insights from 3D image-based ventricular models. PLoS One 2013., 8: Article ID e68872

Kerckhoffs RCP, Neal ML, Gu Q, Bassingthwaighte JB, Omens JH, McCulloch AD: Coupling of a 3D finite element model of cardiac ventricular mechanics to lumped systems models of the systemic and pulmonic circulation. Ann Biomed Eng 2007, 35: 1–18.

Kerckhoffs RCP, Campbell SG, Flaim SN, Howard EJ, Sierra-Aguado J, Mulligan LJ, et al.: Multi-scale modeling of excitation-contraction coupling in the normal and failing heart. Annu Int Conf IEEE Eng Med Biol Soc 2009, 2009: 4281–2.

Sermesant M, Chabiniok R, Chinchapatnam P, Mansi T, Billet F, Moireau P, et al.: Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: a preliminary clinical validation. Med Image Anal 2012, 16: 201–15.

Vinson CA, Gibson DG, Yettram AL: Analysis of left ventricular behaviour in diastole by means of finite element method. Br Heart J 1979, 41: 60–7.

Yamaki M, Kubota I, Tomoike H: Simulation of late potentials and arrhythmias by use of a three-dimensional heart model: casuality of peri-infarctional slow conduction in ventricular fibrillation. J Electrocardiol 1999, 32: 115–21.

Kerfoot E, Lamata P, Niederer S, Hose R, Spaan J, Smith N: Share and enjoy: anatomical models database - generating and sharing cardiovascular model data using web services. Med Biol Eng Comput 2013, 51: 1181–90.




This item appears in the following Collection(s)

Show full item record