Patient-Specific Modeling of Structure and Function of Cardiac Cells



Cardiovascular diseases (CVDs) are the major cause of death in the developed world. Also, CVDs produce significant economic burden on society [37]. Development and implementation of approaches for prevention, diagnosis, and treatment of CVDs constitute large-scale and long-term efforts of healthcare systems, industry, and academia. Despite significant advances in technologies such as cardiac imaging and medical devices in the last decades, there are still major gaps in our basic knowledge of CVDs and their diagnosis and treatment, in particular, in individual patients.


Cardiac Cell Congenital Heart Defect Hypoplastic Left Heart Syndrome Rectifier Potassium Current Myosin Interaction 



This work has been supported by National Heart, Lung, and Blood Institute grant R01 HL094464, the Richard A. and Nora Eccles Fund for Cardiovascular Research, and awards from the Nora Eccles Treadwell Foundation.


  1. 1.
    Anandasabapathy, S. 2008b. Novel endoscopic techniques for the detection of Barrett’s ­dysplasia. Gastrointest Cancer Res, 2, 81–4.PubMedGoogle Scholar
  2. 2.
    Anandasabapathy, S. 2008a. Endoscopic imaging: emerging optical techniques for the detection of colorectal neoplasia. Curr Opin Gastroenterol, 24, 64–9.PubMedCrossRefGoogle Scholar
  3. 3.
    Ashcroft, F. M. 2000. Ion channels and disease, San Diego, CA, Academic Press.Google Scholar
  4. 4.
    Bassnett, S., Reinisch, L. & Beebe, D. C. 1990. Intracellular pH measurement using single excitation-dual emission fluorescence ratios. Am J Physiol Cell Physiol, 258(27), C171–8.Google Scholar
  5. 5.
    Bolte, S. & Cordelieres, F. P. 2006. A guided tour into subcellular colocalization analysis in light microscopy. J Microsc, 224, 213–32.PubMedCrossRefGoogle Scholar
  6. 6.
    Boutet de Monvel, J., Le Calvez, S. & Ulfendahl, M. 2001. Image restoration for confocal microscopy: improving the limits of deconvolution, with application to the visualization of the mammalian hearing organ. Biophys J, 80, 2455–70.CrossRefGoogle Scholar
  7. 7.
    Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J. M., Diesmann, M., Morrison, A., Goodman, P. H., Harris, F. C., Jr., Zirpe, M., Natschlager, T., Pecevski, D., Ermentrout, B., Djurfeldt, M., Lansner, A., Rochel, O., Vieville, T., Muller, E., Davison, A. P., El Boustani, S. & Destexhe, A. 2007. Simulation of networks of spiking neurons: a review of tools and strategies. J Comput Neurosci, 23, 349–98.PubMedCrossRefGoogle Scholar
  8. 8.
    Buckler, K. J. & Vaughan-Jones, R. D. 1990. Application of a new pH-sensitive fluoroprobe (carboxy-SNARF-1) for intracellular pH measurement in small, isolated cells. Pflüger? Arch, 417, 234–9.PubMedCrossRefGoogle Scholar
  9. 9.
    Diaspro, A. 2002. Confocal and two-photon microscopy: foundations, applications, and advances, New York, Wiley.Google Scholar
  10. 10.
    Fawcett, D. W. & McNutt, N. S. 1969. The ultrastructure of the cat myocardium. I. Ventricular papillary muscle. J Cell Biol, 42, 1–45.PubMedCrossRefGoogle Scholar
  11. 11.
    Fluhler, E., Burnham, V. G. & Loew, L. M. 1985. Spectra, membrane binding, and potentiometric responses of new charge shift probes. Biochemistry, 24, 5749–55.PubMedCrossRefGoogle Scholar
  12. 12.
    Flusberg, B. A., Cocker, E. D., Piyawattanametha, W., Jung, J. C., Cheung, E. L. M. & Schnitzer, M. J. 2005. Fiber-optic fluorescence imaging. Nat Methods, 2, 941–50.PubMedCrossRefGoogle Scholar
  13. 13.
    Garny, A., Noble, D., Hunter, P. J. & Kohl, P. 2009. CELLULAR OPEN RESOURCE (COR): current status and future directions. Philos Transact A Math Phys Eng Sci, 367, 1885–905.PubMedCrossRefGoogle Scholar
  14. 14.
    Goetz, M., Hoffman, A., Galle, P. R., Neurath, M. F. & Kiesslich, R. 2006. Confocal laser endoscopy: new approach to the early diagnosis of tumors of the esophagus and stomach. Future Oncol, 2, 469–76.PubMedCrossRefGoogle Scholar
  15. 15.
    Goldman, R. D. & Spector, D. L. 2005. Live cell imaging, a laboratory manual, Cold Spring Harbor, NY, Cold Spring Harbor Laboratory Press.Google Scholar
  16. 16.
    Gonzalez, R. C. & Woods, R. E. 1992. Digital image processing, Reading, MA, Addison-Wesley.Google Scholar
  17. 17.
    Gross, E., Bedlack, R. S., Jr. & Loew, L. M. 1994. Dual-wavelength ratiometric fluorescence measurement of the membrane dipole potential. Biophys J, 67, 208–16.PubMedCrossRefGoogle Scholar
  18. 18.
    Grynkiewicz, G., Poenie, M. & Tsien, R. Y. 1985. A new generation of Ca2+ indicators with greatly improved fluorescence properties. J Biol Chem, 260, 3440–50.PubMedGoogle Scholar
  19. 19.
    He, J. Q., Conklin, M. W., Foell, J. D., Wolff, M. R., Haworth, R. A., Coronado, R. & Kamp, T. J. 2001. Reduction in density of transverse tubules and L-type Ca2+ channels in canine tachycardia-induced heart failure. Cardiovasc Res, 49, 298–307.PubMedCrossRefGoogle Scholar
  20. 20.
    Hecht, E. 1987. Optics, Reading, MA, Addison-Wesley Publishing Company.Google Scholar
  21. 21.
    Heiden, W., Goetze, T. & Brickmann, J. 1991. ‘Marching-Cube’-Algorithmen zur schnellen Generierung von Isoflaechen auf der Basis dreidimensionaler Datenfelder. In: Fruehauf, M. & Goebel, M. (eds.) Visualisierung von Volumendaten. Berlin, Heidelberg, New York: Springer.Google Scholar
  22. 22.
    Heinzel, F. R., Bito, V., Biesmans, L., Wu, M., Detre, E., von Wegner, F., Claus, P., Dymarkowski, S., Maes, F. & Bogaert, J. 2008. Remodeling of T-tubules and reduced synchrony of Ca2+ release in myocytes from chronically ischemic myocardium. Circ Res, 102, 338–46.PubMedCrossRefGoogle Scholar
  23. 23.
    Hoffman, A., Goetz, M., Vieth, M., Galle, P. R., Neurath, M. F. & Kiesslich, R. 2006. Confocal laser endomicroscopy: technical status and current indications. Endoscopy, 38, 1275–83.PubMedCrossRefGoogle Scholar
  24. 24.
    Hong, K., Piper, D. R., Diaz-Valdecantos, A., Brugada, J., Oliva, A., Burashnikov, E., Santos-de-Soto, J., Grueso-Montero, J., Diaz-Enfante, E., Brugada, P., Sachse, F., Sanguinetti, M. C. & Brugada, R. 2005. De novo KCNQ1 mutation responsible for atrial fibrillation and short QT syndrome in utero. Cardiovasc Res, 68, 433–40.PubMedCrossRefGoogle Scholar
  25. 25.
    Hucka, M., Finney, A., Sauro, H. M., Bolouri, H., Doyle, J. C., Kitano, H., Arkin, A. P., Bornstein, B. J., Bray, D., Cornish-Bowden, A., Cuellar, A. A., Dronov, S., Gilles, E. D., Ginkel, M., GOR, V., Goryanin, II, Hedley, W. J., Hodgman, T. C., Hofmeyr, J. H., Hunter, P. J., Juty, N. S., Kasberger, J. L., Kremling, A., Kummer, U., Le Novere, N., Loew, L. M., Lucio, D., Mendes, P., Minch, E., Mjolsness, E. D., Nakayama, Y., Nelson, M. R., Nielsen, P. F., Sakurada, T., Schaff, J. C., Shapiro, B. E., Shimizu, T. S., Spence, H. D., Stelling, J., Takahashi, K., Tomita, M., Wagner, J. & Wang, J. 2003. The systems biology markup language (SBML): a medium for representation and exchange of biochemical ­network models. Bioinformatics, 19, 524–31.PubMedCrossRefGoogle Scholar
  26. 26.
    Inada, S., Hancox, J. C., Zhang, H. & Boyett, M. R. 2009. One-dimensional mathematical model of the atrioventricular node including atrio-nodal, nodal, and nodal-his cells. Biophys J, 97, 2117–27.PubMedCrossRefGoogle Scholar
  27. 27.
    Inoue, H., Kudo, S. E. & Shiokawa, A. 2004. Novel endoscopic imaging techniques toward in vivo observation of living cancer cells in the gastrointestinal tract. Dig Dis, 22, 334–7.PubMedCrossRefGoogle Scholar
  28. 28.
    Iyer, V., Mazhari, R. & Winslow, R. L. 2004. A computational model of the human left-­ventricular epicardial myocyte. Biophys J, 87, 1507–25.PubMedCrossRefGoogle Scholar
  29. 29.
    Jayasinghe, I. D., Cannell, M. B. & Soeller, C. 2009. Organization of ryanodine receptors, transverse tubules, and sodium–calcium exchanger in rat myocytes. Biophys J, 97, 2664–73.PubMedCrossRefGoogle Scholar
  30. 30.
    JSIM. 2010. JSim Home Page [Online]. Available: [Accessed].
  31. 31.
    Kaprielian, Z., Imondi, R. & Runko, E. 2000. Axon guidance at the midline of the developing CNS. Anat Rec, 261, 176–97.PubMedCrossRefGoogle Scholar
  32. 32.
    Karp, G. 2005. Cell and molecular biology: concepts and experiments, Hoboken, NJ, Wiley.Google Scholar
  33. 33.
    Kostin, S., Scholz, D., Shimada, T., Maeno, Y., Mollnau, H., Hein, S. & Schaper, J. 1998. The internal and external protein scaffold of the T-tubular system in cardiomyocytes. Cell Tissue Res, 294, 449–60.PubMedCrossRefGoogle Scholar
  34. 34.
    Lasher, R. A., Hitchcock, R. W. & Sachse, F. B. 2009. Towards modeling of cardiac micro-structure with catheter-based confocal microscopy: a novel approach for dye delivery and tissue characterization. IEEE Trans Med Imaging, 28, 1156–64.PubMedCrossRefGoogle Scholar
  35. 35.
    Lloyd, C. M., Halstead, M. D. & Nielsen, P. F. 2004. CellML: its future, present and past. Prog Biophys Mol Biol, 85, 433–50.PubMedCrossRefGoogle Scholar
  36. 36.
    Lloyd, C. M., Lawson, J. R., Hunter, P. J. & Nielsen, P. F. 2008. The CellML model repository. Bioinformatics, 24, 2122–3.PubMedCrossRefGoogle Scholar
  37. 37.
    Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T. & Murray, C. J. L. 2006. Global burden of disease and risk factors, New York, Oxford University Press.CrossRefGoogle Scholar
  38. 38.
    Lorensen, W. E. & Cline, H. E. 1987. Marching cubes: a high resolution 3d surface construction algorithm. Comput Graph, 4, 163–9.Google Scholar
  39. 39.
    Louch, W. E., Bito, V., Heinzel, F. R., Macianskiene, R., Vanhaecke, J., Flameng, W., Mubagwa, K. & Sipido, K. R. 2004. Reduced synchrony of Ca2+ release with loss of T-tubules – a comparison to Ca2+ release in human failing cardiomyocytes. Cardiovasc Res, 62, 63–73.PubMedCrossRefGoogle Scholar
  40. 40.
    Luo, C. & Rudy, Y. 1991. A model of the ventricular cardiac action potential. Depolarization, repolarization, and their interaction. Circ Res, 68, 1501–26.PubMedCrossRefGoogle Scholar
  41. 41.
    Mardis, E. R. 2006. Anticipating the 1,000 dollar genome. Genome Biol, 7, 112.PubMedCrossRefGoogle Scholar
  42. 42.
    McNutt, N. S. & Fawcett, D. W. 1969. The ultrastructure of the cat myocardium. II. Atrial muscle. J Cell Biol, 42, 46–67.PubMedCrossRefGoogle Scholar
  43. 43.
    Milescu, L. S., Akk, G. & Sachs, F. 2005. Maximum likelihood estimation of ion channel kinetics from macroscopic currents. Biophys J, 88, 2494–515.PubMedCrossRefGoogle Scholar
  44. 44.
    Missan, S. & McDonald, T. F. 2005. CESE: cell electrophysiology simulation environment. Appl Bioinformatics, 4, 155–6.PubMedCrossRefGoogle Scholar
  45. 45.
    Muldoon, T. J., Anandasabapathy, S., Maru, D. & Richards-Kortum, R. 2008. High-resolution imaging in Barrett’s esophagus: a novel, low-cost endoscopic microscope. Gastrointest Endosc, 68, 737–44.PubMedCrossRefGoogle Scholar
  46. 46.
    Neal, M. L. & Kerckhoffs, R. 2010. Current progress in patient-specific modeling. Brief Bioinform, 11(1), 111–26.PubMedCrossRefGoogle Scholar
  47. 47.
    Opencell. 2010. Available: [Accessed].
  48. 48.
    Perrin, M. J., Subbiah, R. N., Vandenberg, J. I. & Hill, A. P. 2008. Human ether-a-go-go related gene (hERG) K+ channels: function and dysfunction. Prog Biophys Mol Biol, 98, 137–48.PubMedCrossRefGoogle Scholar
  49. 49.
    Plaster, N. M., Tawil, R., Tristani-Firouzi, M., Canun, S., Bendahhou, S., Tsunoda, A., Donaldson, M. R., Iannaccone, S. T., Brunt, E., Barohn, R., Clark, J., Deymeer, F., George, A. L., Jr., Fish, F. A., Hahn, A., Nitu, A., Ozdemir, C., Serdaroglu, P., Subramony, S. H., Wolfe, G., Fu, Y. H. & Ptacek, L. J. 2001. Mutations in Kir2.1 cause the developmental and episodic electrical phenotypes of Andersen’s syndrome. Cell, 105, 511–9.PubMedCrossRefGoogle Scholar
  50. 50.
    Press, W. H. 1992. Numerical recipes in C: the art of scientific computing, Cambridge; NY, Cambridge University Press.Google Scholar
  51. 51.
    Richardson, W. H. 1972. Bayesian-based iterative method of image restoration. J Opt Soc Am, 62, 55–9.CrossRefGoogle Scholar
  52. 52.
    Ruan, Y., Liu, N. & Priori, S. G. 2009. Sodium channel mutations and arrhythmias. Nat Rev Cardiol, 6, 337–48.PubMedCrossRefGoogle Scholar
  53. 53.
    Sachse, F. B. 2004. Computational cardiology: modeling of anatomy, electrophysiology, and mechanics, Heidelberg, Springer.Google Scholar
  54. 54.
    Sachse, F. B. & Seemann, G. 2009. Special issue: functional imaging and modelling of the heart. Med Image Anal, 13, 345.PubMedCrossRefGoogle Scholar
  55. 55.
    Sachse, F. B., Glänzel, K. & Seemann, G. 2003. Modeling of protein interactions involved in cardiac tension development. Int J Bifurcat Chaos, 13, 3561–78.CrossRefGoogle Scholar
  56. 56.
    Sachse, F. B., Moreno, A. P. & Abildskov, J. A. 2008. Electrophysiological modeling of fibroblasts and their interaction with myocytes. Ann Biomed Eng, 36, 41–56.PubMedCrossRefGoogle Scholar
  57. 57.
    Sachse, F. B., Savio-Galimberti, E., Goldhaber, J. I. & Bridge, J. H. 2009. Towards computational modeling of excitation-contraction coupling in cardiac myocytes: reconstruction of structures and proteins from confocal imaging. Pac Symp Biocomput, 14, 328–39.Google Scholar
  58. 58.
    Sanguinetti, M. C. & Tristani-Firouzi, M. 2006. hERG potassium channels and cardiac arrhythmia. Nature, 440, 463–9.PubMedCrossRefGoogle Scholar
  59. 59.
    Savio, E., Goldhaber, J. I., Bridge, J. H. B. & Sachse, F. B. 2007. A framework for analyzing confocal images of transversal tubules in cardiomyocytes. Lect Notes Comput Sci, 4466, 110–19.CrossRefGoogle Scholar
  60. 60.
    Savio-Galimberti, E., Frank, J., Inoue, M., Goldhaber, J. I., Cannell, M. B., Bridge, J. H. & Sachse, F. B. 2008. Novel features of the rabbit transverse tubular system revealed by quantitative analysis of three-dimensional reconstructions from confocal images. Biophys J, 95(4), 2053–62.PubMedCrossRefGoogle Scholar
  61. 61.
    Schaff, J. & Loew, L. M. 1999. The virtual cell. Pac Symp Biocomput, 5, 228–39.Google Scholar
  62. 62.
    Seemann, G., Sachse, F. B., Weiss, D. L., Ptacek, L. J. & Tristani-Firouzi, M. 2007. Modeling of IK1 mutations in human left ventricular myocytes and tissue. Am J Physiol Heart Circ Physiol, 292, H549–59.PubMedCrossRefGoogle Scholar
  63. 63.
    Seemann, G., Lurz, S., Keller, D. U. J., Weiss, D. L., Scholz, E. P. & Dössel, O. 2008. Adaption of mathematical ion channel models to measured data using the particle swarm optimization. IFMBE Proc, 22, 2507–10.CrossRefGoogle Scholar
  64. 64.
    Soeller, C. & Cannell, M. B. 1999. Examination of the transverse tubular system in living cardiac rat myocytes by 2-photon microscopy and digital image-processing techniques. Circ Res, 84, 266–75.PubMedCrossRefGoogle Scholar
  65. 65.
    Soeller, C., Jayasinghe, I. D., Li, P., Holden, A. V. & Cannell, M. B. 2009. Three-dimensional high-resolution imaging of cardiac proteins to construct models of intracellular Ca2+ signalling in rat ventricular myocytes. Exp Physiol, 94, 496–508.PubMedCrossRefGoogle Scholar
  66. 66.
    Souders, C. A., Bowers, S. L. & Baudino, T. A. 2009. Cardiac fibroblast: the renaissance cell. Circ Res, 105, 1164–76.PubMedCrossRefGoogle Scholar
  67. 67.
    Splawski, I., Timothy, K. W., Sharpe, L. M., Decher, N., Kumar, P., Bloise, R., Napolitano, C., Schwartz, P. J., Joseph, R. M., Condouris, K., Tager-Flusberg, H., Priori, S. G., Sanguinetti, M. C. & Keating, M. T. 2004. Ca(V)1.2 calcium channel dysfunction causes a multisystem disorder including arrhythmia and autism. Cell, 119, 19–31.PubMedCrossRefGoogle Scholar
  68. 68.
    Splawski, I., Timothy, K. W., Decher, N., Kumar, P., Sachse, F. B., Beggs, A. H., Sanguinetti, M. C. & Keating, M. T. 2005. Severe arrhythmia disorder caused by cardiac L-type calcium channel mutations. Proc Natl Acad Sci U S A, 102, 8089–96.PubMedCrossRefGoogle Scholar
  69. 69.
    Stark, J. F., de Leval, M. R., Tsang, V. T. & Courtney, M. 2006. Surgery for congenital heart defects. pp. 754Google Scholar
  70. 70.
    Stewart, P., Aslanidi, O. V., Noble, D., Noble, P. J., Boyett, M. R. & Zhang, H. 2009. Mathematical models of the electrical action potential of Purkinje fibre cells. Philos Transact A Math Phys Eng Sci, 367, 2225–55.PubMedCrossRefGoogle Scholar
  71. 71.
    Stuehmer, W. & Parekh, A. B. 1995. Electrophysiological recordings from xenopus oocytes. In: Sakmann, B. & Neher, E. (eds.) Single-channel recordings. 2 ed. New York and London: Plenum Press.Google Scholar
  72. 72.
    Weiss, D. L., Seemann, G., Sachse, F. B. & Dossel, O. 2005. Modelling of short QT syndrome in a heterogeneous model of the human ventricular wall. Europace, 7 Suppl 2, 105–17.PubMedCrossRefGoogle Scholar
  73. 73.
    Wong, C., Soeller, C., Burton, L. & Cannell, M. B. 2001. Changes in transverse-tubular ­system architecture in myocytes from diseased human ventricles. Biophys J, 80, 588A.Google Scholar

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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Nora Eccles Harrison Cardiovascular Research and Training Institute, and Bioengineering DepartmentUniversity of UtahSalt Lake CityUSA

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