Skip to main content

A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias

Part of the Lecture Notes in Computer Science book series (LNIP,volume 10263)


Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomical models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In consequence, fiber information from RBM does not match with histological data in other areas of the heart, having a negative impact in cardiac simulations beyond the LV. In this work, we present a RBM where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the right ventricle endocardium, the interventricular septum and the outflow tracts. Electrophysiological simulations including these anatomical structures were then performed, with patient-specific data of outflow tract ventricular arrhythmias (OTVA) cases. A comparison between the obtained simulations and electro-anatomical data of these patients confirm the potential for in silico identification of the site of origin in OTVAs before the intervention.


  • Fiber orientation
  • Rule-based method
  • Electrophysiological simulations
  • Arrhythmias
  • Outflow tracts

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-59448-4_33
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-59448-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   99.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.


  1. 1.

  2. 2.

  3. 3.

  4. 4.

    An Open Source medical simulation software


  1. Arevalo, H.J., et al.: Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nat. Commun. 7, 11437 (2016)

    CrossRef  Google Scholar 

  2. Lombaert, H., et al.: Human atlas of the cardiac fiber architecture: study on a healthy population. IEEE Trans. Med. Imaging 31(7), 1436–1447 (2012)

    MathSciNet  CrossRef  Google Scholar 

  3. Young, R.J., Panfilov, A.V.: Anisotropy of wave propagation in the heart can be modeled by a Riemannian electrophysiological metric. Proc. Natl. Acad. Sci. U.S.A. 107(34), 15063–15068 (2010)

    CrossRef  Google Scholar 

  4. Hooks, D.A., et al.: Laminar arrangement of ventricular myocytes influences electrical behavior of the heart. Circ. Res. 101(10), 103–113 (2007)

    CrossRef  Google Scholar 

  5. Bayer, J.D., et al.: A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann. Biomed. Eng. 40(10), 2243–2254 (2012)

    CrossRef  Google Scholar 

  6. Agger, P., et al.: Insights from echocardiography, magnetic resonance imaging, and microcomputed tomography relative to the mid-myocardial left ventricular echogenic zone. Echocardiography 33(10), 1546–1556 (2016)

    CrossRef  Google Scholar 

  7. Boettler, P., et al.: New aspects of the ventricular septum and its function: an echocardiographic study. Heart 91(10), 1343–1348 (2005)

    CrossRef  Google Scholar 

  8. Kocica, M.J., et al.: The helical ventricular myocardial band: global, three-dimensional, functional architecture of the ventricular myocardium. Eur. J. Cardio-thoracic Surg. 29(SUPPL.), 1 (2006)

    Google Scholar 

  9. Streeter, D.D., et al.: Fiber orientation in the canine left ventricle during diastole and systole. Circ. Res. 24(3), 339–347 (1969)

    CrossRef  Google Scholar 

  10. Greenbaum, R.A., et al.: Left ventricular fibre architecture in man. Br. Heart J. 45(1980), 248–263 (1981)

    CrossRef  Google Scholar 

  11. Sanchez-Quintana, D., et al.: Anatomical basis for the cardiac interventional electrophysiologist. BioMed. Res. Int. Ao. 2015 (2015)

    Google Scholar 

  12. Talbot, H., et al.: Towards an interactive electromechanical model of the heart. Interface Focus 3(2) (2013)

    Google Scholar 

  13. Acosta, J., et al.: Impact of earliest activation site location in the septal right ventricular outflow tract for identification of left vs right outflow tract origin of idiopathic ventricular arrhythmias. Heart Rhythm 12(4), 726–734 (2015)

    CrossRef  Google Scholar 

  14. Herczku, C., et al.: Mapping data predictors of a left ventricular outflow tract origin of idiopathic ventricular tachycardia with V3 transition and septal earliest activation. Circ. Arrhythm. Electrophysiol. 5(3), 484–491 (2012)

    CrossRef  Google Scholar 

  15. Toussaint, N., et al.: In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing. Med. Image Anal. 17(8), 1243–1255 (2013)

    CrossRef  Google Scholar 

  16. Mekkaoui, C., et al.: Diffusion tractography of the entire left ventricle by using free-breathing accelerated simultaneous multisection imaging. Radiology, 152613 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Rubén Doste .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Doste, R. et al. (2017). A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias. In: Pop, M., Wright, G. (eds) Functional Imaging and Modelling of the Heart. FIMH 2017. Lecture Notes in Computer Science(), vol 10263. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59447-7

  • Online ISBN: 978-3-319-59448-4

  • eBook Packages: Computer ScienceComputer Science (R0)