Skip to main content
SpringerLink
Log in

Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise

  • Regular Paper
  • Published:
Journal of Visualization Aims and scope Submit manuscript

Abstract

This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels.

Graphical abstract

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Atkinson KE (2008) An introduction to numerical analysis. Wiley, London

    Google Scholar 

  • Bächler P et al (2013) Caval blood flow distribution in patients with Fontan circulation: quantification by using particle traces from 4D flow MR imaging. Radiology 267:67–75

    Article  Google Scholar 

  • Brown RW, Cheng Y-CN, Haacke EM, Thompson MR, Venkatesan R (2014) Magnetic resonance imaging: physical principles and sequence design. Wiley, London

    Book  Google Scholar 

  • Casas B, Lantz J, Dyverfeldt P, Ebbers T (2016) 4D flow MRI-Based pressure loss estimation in stenotic flows: evaluation using numerical simulations. Magn Reson Med 75:1808–1821

    Article  Google Scholar 

  • Chen C-M, Biswas A, Shen H-W (2015) Uncertainty modeling and error reduction for pathline computation in time-varying flow fields. In: 2015 IEEE Pacific visualization symposium (PacificVis). IEEE, pp 215–222

  • Cibis M, Jarvis K, Markl M, Rose M, Rigsby C, Barker AJ, Wentzel JJ (2015) The effect of resolution on viscous dissipation measured with 4D flow MRI in patients with Fontan circulation: evaluation using computational fluid dynamics. J Biomech 48:2984–2989

    Article  Google Scholar 

  • d’Udekem Y et al (2006) The Fontan procedure: contemporary techniques have improved long-term outcomes. Am Heart Association, Dallas

    Google Scholar 

  • Deal BJ, Jacobs ML (2012) Management of the failing Fontan circulation. Heart 98:1098–1104

    Article  Google Scholar 

  • Duncan BW, Desai S (2003) Pulmonary arteriovenous malformations after cavopulmonary anastomosis. Ann Thorac Surg 76:1759–1766

    Article  Google Scholar 

  • Dyverfeldt P et al (2015) 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 17:72

    Article  Google Scholar 

  • Ferstl F, Bürger K, Westermann R (2016) Streamline variability plots for characterizing the uncertainty in vector field ensembles. IEEE Trans Vis Comput Graph 22:767–776

    Article  Google Scholar 

  • Frydrychowicz A, Arnold R, Harloff A, Schlensak C, Hennig J, Langer M, Markl M (2008) In vivo 3-dimensional flow connectivity mapping after extracardiac total cavopulmonary connection. Circulation 118:e16–e17

    Article  Google Scholar 

  • Gewillig M (2005) The Fontan circulation. Heart 91:839–846

    Article  Google Scholar 

  • Ha H et al (2016) Assessment of turbulent viscous stress using ICOSA 4D Flow MRI for prediction of hemodynamic blood damage. Sci Rep 6:39773

    Article  Google Scholar 

  • Ha H, Lantz J, Ziegler M, Casas B, Karlsson M, Dyverfeldt P, Ebbers T (2017) Estimating the irreversible pressure drop across a stenosis by quantifying turbulence production using 4D flow MRI. Sci Rep 7:46618

    Article  Google Scholar 

  • Haggerty CM et al (2014) Fontan hemodynamics from 100 patient-specific cardiac magnetic resonance studies: a computational fluid dynamics analysis. J Thorac Cardiovasc Surg 148:1481–1489

    Article  Google Scholar 

  • Hazinski MF (1999) Manual of pediatric critical care, vol 974. Mosby Incorporated, Maryland Heights

    Google Scholar 

  • Hoffman JI, Kaplan S, Liberthson RR (2004) Prevalence of congenital heart disease. Am Heart J 147:425–439

    Article  Google Scholar 

  • Jarvis K et al (2016) Evaluation of blood flow distribution asymmetry and vascular geometry in patients with Fontan circulation using 4-D flow MRI. Pediatr Radiol 46:1507–1519

    Article  Google Scholar 

  • Kelly Jarvis SS, van Ooij P, Barker A, Carr J, Robinson JD, Rigsby C, Markl M (2014) Probabilistic flow connectivity mapping with 4D flow MRI data for the assessment of blood mixing in Fontan circulation. Proc Int Soc Mag Reson Med p:3857

    Google Scholar 

  • Khiabani RH et al (2015) Exercise capacity in single-ventricle patients after Fontan correlates with haemodynamic energy loss in TCPC. Heart 101:139–143

    Article  Google Scholar 

  • Kim S-J, Bae E-J, Lee J-Y, Lim H-G, Lee C, Lee C-H (2009) Inclusion of hepatic venous drainage in patients with pulmonary arteriovenous fistulas. Ann Thorac Surg 87:548–553

    Article  Google Scholar 

  • Kweon J et al (2016) Four-dimensional flow MRI for evaluation of post-stenotic turbulent flow in a phantom: comparison with flowmeter and computational fluid dynamics. Eur Radiol 26:3588–3597

    Article  Google Scholar 

  • Markl M et al (2011) Time-resolved three-dimensional magnetic resonance velocity mapping of cardiovascular flow paths in volunteers and patients with Fontan circulation. Eur J Cardiothorac Surg 39:206–212

    Article  Google Scholar 

  • Morbiducci U, Ponzini R, Rizzo G, Biancolini ME, Iannaccone F, Gallo D, Redaelli A (2012) Synthetic dataset generation for the analysis and the evaluation of image-based hemodynamics of the human aorta. Med Biol Eng Comput 50:145–154

    Article  Google Scholar 

  • Ono M, Boethig D, Goerler H, Lange M, Westhoff-Bleck M, Breymann T (2006) Clinical outcome of patients 20 years after Fontan operation—effect of fenestration on late morbidity. Eur J Cardiothorac Surg 30:923–929

    Article  Google Scholar 

  • Ooij P et al (2015) A methodology to detect abnormal relative wall shear stress on the full surface of the thoracic aorta using four-dimensional flow MRI. Magn Reson Med 73:1216–1227

    Article  Google Scholar 

  • Pandurangi UM, Shah MJ, Murali R, Cherian KM (1999) Rapid onset of pulmonary arteriovenous malformations after cavopulmonary anastomosis. Ann Thorac Surg 68:237–239

    Article  Google Scholar 

  • Pike NA, Vricella LA, Feinstein JA, Black MD, Reitz BA (2004) Regression of severe pulmonary arteriovenous malformations after Fontan revision and “hepatic factor” rerouting. Ann Thorac Surg 78:697–699

    Article  Google Scholar 

  • Roldán-Alzate A, Frydrychowicz A, Niespodzany E, Landgraf BR, Johnson KM, Wieben O, Reeder SB (2013) In vivo validation of 4D flow MRI for assessing the hemodynamics of portal hypertension. J Magn Reson Imaging 37:1100–1108

    Article  Google Scholar 

  • Roldán-Alzate A, García-Rodríguez S, Anagnostopoulos PV, Srinivasan S, Wieben O, François CJ (2015) Hemodynamic study of TCPC using in vivo and in vitro 4D Flow MRI and numerical simulation. J Biomech 48:1325–1330

    Article  Google Scholar 

  • Shinohara T, Yokoyama T (2001) Pulmonary arteriovenous malformation in patients with total cavopulmonary shunt: what role does lack of hepatic venous blood flow to the lungs play? Pediatr Cardiol 22:343–346

    Article  Google Scholar 

  • Srivastava D et al (1995) Hepatic venous blood and the development of pulmonary arteriovenous malformations in congenital heart disease. Circulation 92:1217–1222

    Article  Google Scholar 

  • Sundareswaran KS et al (2012) Visualization of flow structures in Fontan patients using 3-dimensional phase contrast magnetic resonance imaging. J Thorac Cardiovasc Surg 143:1108–1116

    Article  Google Scholar 

  • Tang E et al (2014) Geometric characterization of patient-specific total cavopulmonary connections and its relationship to hemodynamics. JACC Cardiovasc Imaging 7:215–224

    Article  Google Scholar 

  • Wei ZA, Tree M, Trusty PM, Wu W, Singh-Gryzbon S, Yoganathan A (2018) The advantages of viscous dissipation rate over simplified power loss as a Fontan hemodynamic metric. Ann Biomed Eng 46:404–416

    Article  Google Scholar 

  • Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31:1116–1128

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI18C0022) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (NRF-2016R1A1A1 A05921207) and a grant (2018-0404) from the Asan Institute for Life Sciences, Asan Medical Centre, Seoul, Korea. This study was also supported by NRF (Grant Number: 2018R1D1A1A02043249) and 2018 Research Grant from Kangwon National University (D1001179-01-01).

Author information

Author notes

  1. Namkug Kim and Dong Hyun Yang have contributed equally to this work.

Authors and Affiliations

  1. Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, 24341, South Korea

    Hojin Ha

  2. Department of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Poongnap-dong, Songpa-gu, Seoul, 138-736, South Korea

    Heejun Kang

  3. Asan Institute of Life Science, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Poongnap-dong, Songpa-gu, Seoul, 138-736, South Korea

    Hyungkyu Huh & Jaeyoung Kwon

  4. Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-dong, Pohang, 790-784, South Korea

    Woorak Choi & Sang Joon Lee

  5. Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Poongnap-dong, Songpa-gu, Seoul, 138-736, South Korea

    Hyun Jung Koo, Kyoung Jin Park, Young Chul Cho, Namkug Kim & Dong Hyun Yang

  6. Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Poongnap-dong, Songpa-gu, Seoul, 138-736, South Korea

    Namkug Kim

Authors
  1. Hojin Ha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heejun Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hyungkyu Huh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Woorak Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hyun Jung Koo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jaeyoung Kwon
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kyoung Jin Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Young Chul Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Sang Joon Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Namkug Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Dong Hyun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dong Hyun Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ha, H., Kang, H., Huh, H. et al. Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise. J Vis 22, 245–257 (2019). https://doi.org/10.1007/s12650-018-0536-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12650-018-0536-9

Keywords

Search

Navigation