Skip to main content

Estimation of Diastolic Biomarkers: Sensitiviy to Fibre Orientation

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8896))

Abstract

An accurate estimation of myocardial stiffness and decaying active tension is critical for the characterization of the diastolic function of the heart. Computational cardiac models can be used to analyse deformation and pressure data from the left ventricle in order to estimate these diastolic metrics. The results of this methodology depend on several model assumptions. In this work we reveal a nominal impact of the choice of myocardial fibre orientation between a rule-based description and personalised approach based on diffusion-tensor magnetic resonance imaging. This result suggests the viability of simplified clinical imaging protocols for the model-based estimation of diastolic biomarkers.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Carapella, V., Bordas, R., Pathmanathan, P., Lohezic, M., Schneider, J.E., Kohl, P., Burrage, K., Grau, V.: Quantitative study of the effect of tissue microstructure on contraction in a computational model of rat left ventricle. PLoS ONE 9(4), e92792 (2014)

    Article  Google Scholar 

  2. Geerts, L., Kerckhoffs, R., Bovendeerd, P., Arts, T.: Towards patient specific models of cardiac mechanics: a sensitivity study. In: Magnin, I.E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T. (eds.) FIMH 2003. LNCS, vol. 2674, pp. 81–90. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  3. Gil, D., et al.: What a difference in biomechanics cardiac fiber makes. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds.) STACOM 2012. LNCS, vol. 7746, pp. 253–260. Springer, Heidelberg (2013)

    Google Scholar 

  4. Imperiale, A., Routier, A., Durrleman, S., Moireau, P.: Improving efficiency of data assimilation procedure for a biomechanical heart model by representing surfaces as currents. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 342–351. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  5. Lamata, P., Niederer, S., Nordsletten, D., Barber, D., Roy, I., Hose, D., Smith, N.: An accurate, fast and robust method to generate patient-specific cubic hermite meshes. Medical Image Analysis 15(6), 801–813 (2011)

    Article  Google Scholar 

  6. Lamata, P., Niederer, S., Plank, G., Smith, N.: Generic conduction parameters for predicting activation waves in customised cardiac electrophysiology models. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds.) STACOM 2010. LNCS, vol. 6364, pp. 252–260. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. Lamata, P., Roy, I., Blazevic, B., Crozier, A., Land, S., Niederer, S., Rod Hose, D., Smith, N.: Quality metrics for high order meshes: Analysis of the mechanical simulation of the heart beat. IEEE Transactions on Medical Imaging 32(1), 130–138 (2013)

    Article  Google Scholar 

  8. Lamata, P., Sinclair, M., Kerfoot, E., Lee, A., Crozier, A., Blazevic, B., Land, S., Lewandowski, A., Barber, D., Niederer, S., Smith, N.: An automatic service for the personalization of ventricular cardiac meshes. Journal of the Royal Society Interface 11(91) (2014)

    Google Scholar 

  9. Land, S., Niederer, S., Lamata, P., Smith, N.: Improving the stability of cardiac mechanical simulations. IEEE Transactions on Biomedical Engineering (2015, in press)

    Google Scholar 

  10. Land, S., Niederer, S., Smith, N.: Efficient computational methods for strongly coupled cardiac electromechanics. IEEE Transactions on Biomedical Engineering 59(5), 1219–1228 (2012)

    Article  Google Scholar 

  11. Mcmurray, J., et al.: Esc guidelines for the diagnosis and treatment of acute and chronic heart failure 2012. European Journal of Heart Failure 14(8), 803–869 (2012)

    Article  Google Scholar 

  12. Okamoto, R.J., Moulton, M.J., Peterson, S.J., Li, D., Pasque, M.K., Guccione, J.M.: Epicardial suction: a new approach to mechanical testing of the passive ventricular wall. J. Biomech. Eng. 122(5), 479–487 (2000)

    Article  Google Scholar 

  13. Omens, J.H., MacKenna, D.A., McCulloch, A.D.: Measurement of strain and analysis of stress in resting rat left ventricular myocardium. Journal of Biomechanics 26(6), 665–676 (1993)

    Article  Google Scholar 

  14. Usyk, T., Mazhari, R., McCulloch, A.: Effect of laminar orthotropic myofiber architecture on regional stress and strain in the canine left ventricle. Journal of Elasticity and the Physical Science of Solids 61(1–3), 143–164 (2000)

    Article  MATH  Google Scholar 

  15. Wang, V.Y., Lam, H., Ennis, D.B., Cowan, B.R., Young, A.A., Nash, M.P.: Modelling passive diastolic mechanics with quantitative mri of cardiac structure and function. Medical Image Analysis 13(5), 773–784 (2009)

    Article  Google Scholar 

  16. Xi, J., Shi, W., Rueckert, D., Razavi, R., Smith, N., Lamata, P.: Understanding the need of ventricular pressure for the estimation of diastolic biomarkers. Biomechanics and Modeling in Mechanobiology 13(4), 747–57 (2014)

    Article  Google Scholar 

  17. Xi, J., Lamata, P., Niederer, S., Land, S., Shi, W., Zhuang, X., Ourselin, S., Duckett, S.G., Shetty, A.K., Rinaldi, C.A., Rueckert, D., Razavi, R., Smith, N.P.: The estimation of patient-specific cardiac diastolic functions from clinical measurements. Medical Image Analysis 17(2), 133–146 (2013)

    Article  Google Scholar 

  18. Zile, M., Baicu, C., Gaasch, W.: Diastolic heart failure - abnormalities in active relaxation and passive stiffness of the left ventricle. New England Journal of Medicine 350(19), 1953–1959+2018 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pablo Lamata .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Land, S., Niederer, S., Lamata, P. (2015). Estimation of Diastolic Biomarkers: Sensitiviy to Fibre Orientation. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges. STACOM 2014. Lecture Notes in Computer Science(), vol 8896. Springer, Cham. https://doi.org/10.1007/978-3-319-14678-2_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14678-2_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14677-5

  • Online ISBN: 978-3-319-14678-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics