Skip to main content

Model-Based Estimation of 4D Relative Pressure Map from 4D Flow MR Images

  • Conference paper
Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges (STACOM 2013)

Abstract

We propose a new framework for 4D relative pressure map computations from 4D flow MRI that uses enhanced geometric models for the blood vessels and flow-aware surface and volumetric tags. The enhanced geometric modeling provides better accuracy compared to a simple voxelized mask, while tagging of inlets and outlets allows imposing physiologically meaningful boundary conditions, contributing to more accurate pressure computations. An integrated software suite for semi-automatic processing of 4D flow MR images, preparation and computation of the flow parameters is presented. This enables a fast and intuitive workflow, with accurate final results, ready in minutes.

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

Access this chapter

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 49.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bock, J., Frydrychowicz, A., Lorenz, R., Hirtler, D., Barker, A.J., Johnson, K.M., Arnold, R., Burkhardt, H., Hennig, J., Markl, M.: In vivo noninvasive 4D pressure difference mapping in the human aorta: Phantom comparison and application in healthy volunteers and patients. Magnetic Resonance in Medicine 66(4), 1079–1088 (2011)

    Article  Google Scholar 

  2. Busch, J., Giese, D., Wissmann, L., Kozerke, S.: Reconstruction of divergence-free velocity fields from cine 3d phase-contrast flow measurements. Magnetic Resonance in Medicine 69(1), 200–210 (2013)

    Article  Google Scholar 

  3. Currie, P.J., Seward, J.B., Reeder, G.S., Vlietstra, R.E., Bresnahan, D.R., Bresnahan, J.F., Smith, H.C., Hagler, D.J., Tajik, A.J.: Continuous-wave Doppler echocardiographic assessment of severity of calcific aortic stenosis: a simultaneous Doppler-catheter correlative study in 100 adult patients. Circulation 71(6), 1162–1169 (1985)

    Article  Google Scholar 

  4. Dwight, R.P.: Bayesian inference for data assimilation using least-squares finite element methods. In: IOP Conf. Mat. Sci. Eng. (2010)

    Google Scholar 

  5. Ebbers, T., Farnebck, G.: Improving computation of cardiovascular relative pressure fields from velocity mri. Journal of Magnetic Resonance Imaging 30(1), 54–61 (2009)

    Article  Google Scholar 

  6. Ebbers, T., Wigstrm, L., Bolger, A.F., Engvall, J., Karlsson, M.: Estimation of relative cardiovascular pressures using time-resolved three-dimensional phase contrast mri. Magnetic Resonance in Medicine 45(5), 872–879 (2001)

    Article  Google Scholar 

  7. Fung, Y.: Biomechanics: Circulation. Springer (2010)

    Google Scholar 

  8. Gulsun, M.A., Jolly, M.P., Guehring, J., Guetter, C., Littmann, A., Greiser, A., Markl, M., Stalder, A.: A novel 4D flow tool for comprehensive blood flow analysis. In: Proceedings of ISMRM (2012)

    Google Scholar 

  9. Itu, L., Sharma, P., Gulsun, M., Mihalef, V., Kamen, A., Greiser, A.: Determination of time-varying pressure field from phase contrast MRI data. Journal of Cardiovascular Magnetic Resonance 14(suppl. 1), W36 (2012)

    Google Scholar 

  10. Krittian, S.B., Lamata, P., Michler, C., Nordsletten, D.A., Bock, J., Bradley, C.P., Pitcher, A., Kilner, P.J., Markl, M., Smith, N.P.: A finite-element approach to the direct computation of relative cardiovascular pressure from time-resolved MR velocity data. Medical Image Analysis 16(5), 1029–1037 (2012)

    Article  Google Scholar 

  11. Markl, M., Harloff, A., Bley, T.A., Zaitsev, M., Jung, B., Weigang, E., Langer, M., Hennig, J., Frydrychowicz, A.: Time-resolved 3D MR velocity mapping at 3T: Improved navigator-gated assessment of vascular anatomy and blood flow. Journal of Magnetic Resonance Imaging 25(4), 824–831 (2007)

    Article  Google Scholar 

  12. Markl, M., Kilner, P., Ebbers, T.: Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance 13(1), 7 (2011)

    Article  Google Scholar 

  13. Meier, S., Hennemuth, A., Friman, O., Bock, J., Markl, M., Preusser, T.: Non-invasive 4d blood flow and pressure quantification in central blood vessels via pc-mri. In: Computing in Cardiology, pp. 903–906 (2010)

    Google Scholar 

  14. Tafti, P.D., Delgado-Gonzalo, R., Stalder, A.F., Unser, M.: Variational enhancement and denoising of flow field images. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, March 30-April 2, pp. 1061–1064 (2011)

    Google Scholar 

  15. Tyszka, J.M., Laidlaw, D.H., Asa, J.W., Silverman, J.M.: Three-dimensional, time-resolved (4d) relative pressure mapping using magnetic resonance imaging. Journal of Magnetic Resonance Imaging 12(2), 321–329 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mihalef, V. et al. (2014). Model-Based Estimation of 4D Relative Pressure Map from 4D Flow MR Images. 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 2013. Lecture Notes in Computer Science, vol 8330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54268-8_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-54268-8_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54267-1

  • Online ISBN: 978-3-642-54268-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics