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.
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