Advertisement

European Radiology

, Volume 26, Issue 10, pp 3588–3597 | Cite as

Four-dimensional flow MRI for evaluation of post-stenotic turbulent flow in a phantom: comparison with flowmeter and computational fluid dynamics

  • Jihoon Kweon
  • Dong Hyun YangEmail author
  • Guk Bae Kim
  • Namkug Kim
  • MunYoung Paek
  • Aurelien F. Stalder
  • Andreas Greiser
  • Young-Hak Kim
Cardiac

Abstract

Objectives

To validate 4D flow MRI in a flow phantom using a flowmeter and computational fluid dynamics (CFD) as reference.

Methods

Validation of 4D flow MRI was performed using flow phantoms with 75 % and 90 % stenosis. The effect of spatial resolution on flow rate, peak velocity and flow patterns was investigated in coronal and axial scans. The accuracy of flow rate with 4D flow MRI was evaluated using a flowmeter as reference, and the peak velocity and flow patterns obtained were compared with CFD analysis results.

Results

4D flow MRI accurately measured the flow rate in proximal and distal regions of the stenosis (percent error ≤3.6 % in axial scanning with 1.6-mm resolution). The peak velocity of 4D flow MRI was underestimated by more than 22.8 %, especially from the second half of the stenosis. With 1-mm isotropic resolution, the maximum thickness of the recirculating flow region was estimated within a 1-mm difference, but the turbulent velocity fluctuations mostly disappeared in the post-stenotic region.

Conclusion

4D flow MRI accurately measures the flow rates in the proximal and distal regions of a stenosis in axial scan but has limitations in its estimation of peak velocity and turbulent characteristics.

Key points

4D flow MRI accurately measures the flow rate in axial scan.

The peak velocity was underestimated by 4D flow MRI.

4D flow MRI demonstrates the principal pattern of post-stenotic flow.

Keywords

4D flow MRI Pathological constriction Dimensional measurement accuracy Computational fluid dynamics 

Abbreviations

CFD

Computational fluid dynamics

PC-MRI

Phase contrast magnetic resonance imaging

SNR

Signal-to-noise ratio

Notes

Acknowledgments

Dong Hyun Yang and Young-Hak Kim contributed equally to this article. The scientific guarantor of this publication is Young-Hak Kim. MY Paek, AF Stalder and A Greiser A are employees of Siemens Healthcare. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1058711) as well as by a grant from the Korea Healthcare Technology R&D Project, the Ministry of Health and Welfare, Republic of Korea (HI12C0630). The study was supported by a grant (2014-7204) from the Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea. No complex statistical methods were necessary for this paper. This study is a phantom study, therefore, institutional review board approval and informed consent were not required. Methodology: experimental, performed at one institution.

References

  1. 1.
    Hope TA, Markl M, Wigström L, Alley MT, Miller DC, Herfkens RJ (2007) Comparison of flow patterns in ascending aortic aneurysms and volunteers using four‐dimensional magnetic resonance velocity mapping. J Magn Reson Imaging 26:1471–1479CrossRefPubMedGoogle Scholar
  2. 2.
    Markl M, Kilner PJ, Ebbers T (2011) Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. J Cardiovasc Magn Reson 13:1–22CrossRefGoogle Scholar
  3. 3.
    Reiter G, Reiter U, Kovacs G et al (2008) Magnetic resonance–derived 3-dimensional blood flow patterns in the main pulmonary artery as a marker of pulmonary hypertension and a measure of elevated mean pulmonary arterial pressure. Circ: Cardiovasc Imaging 1:23–30Google Scholar
  4. 4.
    Bächler P, Pinochet N, Sotelo J et al (2013) Assessment of normal flow patterns in the pulmonary circulation by using 4D magnetic resonance velocity mapping. Magn Reson Imaging 31:178–188CrossRefPubMedGoogle Scholar
  5. 5.
    Geiger J, Hirtler D, Burk J et al (2014) Postoperative pulmonary and aortic 3D haemodynamics in patients after repair of transposition of the great arteries. Eur Radiol 24:200–208CrossRefPubMedGoogle Scholar
  6. 6.
    Harloff A, Albrecht F, Spreer J et al (2009) 3D blood flow characteristics in the carotid artery bifurcation assessed by flow‐sensitive 4D MRI at 3T. Magn Reson Med 61:65–74CrossRefPubMedGoogle Scholar
  7. 7.
    van der Hulst AE, Westenberg JJ, Kroft LJ et al (2010) Tetralogy of fallot: 3D velocity-encoded MR imaging for evaluation of right ventricular valve flow and diastolic function in patients after correction 1. Radiology 256:724–734CrossRefPubMedGoogle Scholar
  8. 8.
    Markl M, Chan FP, Alley MT et al (2003) Time‐resolved three‐dimensional phase‐contrast MRI. J Magn Reson Imaging 17:499–506CrossRefPubMedGoogle Scholar
  9. 9.
    Kilner PJ, Manzara CC, Mohiaddin RH et al (1993) Magnetic resonance jet velocity mapping in mitral and aortic valve stenosis. Circulation 87:1239–1248CrossRefPubMedGoogle Scholar
  10. 10.
    Caruthers SD, Lin SJ, Brown P et al (2003) Practical value of cardiac magnetic resonance imaging for clinical quantification of aortic valve stenosis comparison with echocardiography. Circulation 108:2236–2243CrossRefPubMedGoogle Scholar
  11. 11.
    Khodarahmi I, Shakeri M, Kotys‐Traughber M, Fischer S, Sharp MK, Amini AA (2014) In vitro validation of flow measurement with phase contrast MRI at 3 tesla using stereoscopic particle image velocimetry and stereoscopic particle image velocimetry‐based computational fluid dynamics. J Magn Reson Imaging 39:1477–1485CrossRefPubMedGoogle Scholar
  12. 12.
    Tang C, Blatter DD, Parker DL (1993) Accuracy of phase‐contrast flow measurements in the presence of partial‐volume effects. J Magn Reson Imaging 3:377–385CrossRefPubMedGoogle Scholar
  13. 13.
    Stalder A, Russe M, Frydrychowicz A, Bock J, Hennig J, Markl M (2008) Quantitative 2D and 3D phase contrast MRI: optimized analysis of blood flow and vessel wall parameters. Magn Reson Med 60:1218–1231CrossRefPubMedGoogle Scholar
  14. 14.
    Sherwin S, Blackburn HM (2005) Three-dimensional instabilities and transition of steady and pulsatile axisymmetric stenotic flows. J Fluid Mech 533:297–327CrossRefGoogle Scholar
  15. 15.
    Vreman A (2004) An eddy-viscosity subgrid-scale model for turbulent shear flow: algebraic theory and applications. Phys Fluids (1994-present) 16:3670–3681CrossRefGoogle Scholar
  16. 16.
    Kim J, Kim D, Choi H (2001) An immersed-boundary finite-volume method for simulations of flow in complex geometries. J Comput Phys 171:132–150CrossRefGoogle Scholar
  17. 17.
    Ståhlberg F, Søndergaard L, Thomsen C, Henriksen O (1992) Quantification of complex flow using MR phase imaging—a study of parameters influencing the phase/velocity relation. Magn Reson Imaging 10:13–23CrossRefPubMedGoogle Scholar
  18. 18.
    Elkins CJ, Alley MT (2007) Magnetic resonance velocimetry: applications of magnetic resonance imaging in the measurement of fluid motion. Exp Fluids 43:823–858CrossRefGoogle Scholar
  19. 19.
    Oshinski JN, Ku DN, Pettigrew RI (1995) Turbulent fluctuation velocity: the most significant determinant of signal loss in stenotic vessels. Magn Reson Med 33:193–199CrossRefPubMedGoogle Scholar
  20. 20.
    O'Brien KR, Cowan BR, Jain M, Stewart RA, Kerr AJ, Young AA (2008) MRI phase contrast velocity and flow errors in turbulent stenotic jets. J Magn Reson Imaging 28:210–218CrossRefPubMedGoogle Scholar
  21. 21.
    Kadbi M, Negahdar M, Traughber M, Martin P, Stoddard MF, Amini AA (2014) 4D UTE flow: a phase‐contrast MRI technique for assessment and visualization of stenotic flows., Magnetic Resonance in MedicineGoogle Scholar
  22. 22.
    Dyverfeldt P, Sigfridsson A, Kvitting JPE, Ebbers T (2006) Quantification of intravoxel velocity standard deviation and turbulence intensity by generalizing phase‐contrast MRI. Magn Reson Med 56:850–858CrossRefPubMedGoogle Scholar
  23. 23.
    Binter C, Knobloch V, Manka R, Sigfridsson A, Kozerke S (2013) Bayesian multipoint velocity encoding for concurrent flow and turbulence mapping. Magn Reson Med 69:1337–1345CrossRefPubMedGoogle Scholar
  24. 24.
    Hope MD, Hope TA, Meadows AK et al (2010) Bicuspid aortic valve: four-dimensional MR evaluation of ascending aortic systolic flow patterns 1. Radiology 255:53–61CrossRefPubMedGoogle Scholar
  25. 25.
    Dyvorne H, Knight-Greenfield A, Jajamovich G et al (2014) Abdominal 4D flow MR imaging in a breath hold: combination of spiral sampling and dynamic compressed sensing for highly accelerated acquisition., RadiologyGoogle Scholar

Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Jihoon Kweon
    • 1
  • Dong Hyun Yang
    • 2
    Email author
  • Guk Bae Kim
    • 2
  • Namkug Kim
    • 2
  • MunYoung Paek
    • 3
  • Aurelien F. Stalder
    • 4
  • Andreas Greiser
    • 4
  • Young-Hak Kim
    • 1
  1. 1.Department of Cardiology and Heart Institute, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulSouth Korea
  2. 2.Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulSouth Korea
  3. 3.Siemens HealthcareSeoulKorea
  4. 4.Siemens HealthcareErlangenGermany

Personalised recommendations