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User-dependent variability in mitral valve segmentation and its impact on CFD-computed hemodynamic parameters

  • Katharina VellguthEmail author
  • Jan Brüning
  • Lennart Tautz
  • Franziska Degener
  • Isaac Wamala
  • Simon Sündermann
  • Ulrich Kertzscher
  • Titus Kuehne
  • Anja Hennemuth
  • Volkmar Falk
  • Leonid Goubergrits
Original Article

Abstract

Purpose

While novel tools for segmentation of the mitral valve are often based on automatic image processing, they mostly require manual interaction by a proficient user. Those segmentations are essential for numerical support of mitral valve treatment using computational fluid dynamics, where the reconstructed geometry is incorporated into a simulation domain. To quantify the uncertainty and reliability of hemodynamic simulations, it is crucial to examine the influence of user-dependent variability in valve segmentation.

Methods

Previously, the inter-user variability of landmarks in mitral valve segmentation was investigated. Here, the inter-user variability of geometric parameters of the mitral valve, projected orifice area (OA) and projected annulus area (AA), is investigated for 10 mitral valve geometries, each segmented by three users. Furthermore, the propagation of those variations into numerically calculated hemodynamics, i.e., the blood flow velocity, was investigated.

Results

Among the three geometric valve parameters, AA was least user-dependent. Almost all deviations to the mean were below 10%. Larger variations were observed for OA. Variations observed for the numerically calculated hemodynamics were in the same order of magnitude as those of geometric parameters. No correlation between variation of geometric parameters and variation of calculated hemodynamic parameters was found.

Conclusion

Errors introduced due to the user-dependency were of the same size as the variations of calculated hemodynamics. The variation was thereby of the same scale as deviations in clinical measurements of blood flow velocity using Doppler echocardiography. Since no correlation between geometric and hemodynamic uncertainty was found, further investigation of the complex relationship between anatomy, leaflet shape and flow is necessary.

Keywords

Mitral valve Patient specific Hemodynamic Virtual treatment planning CFD Image segmentation Uncertainty 

Notes

Funding

This work is part of the BMBF VIP+ project DSSMitral (funded by the German Federal Ministry of Education and Research under Grant No. 03VP00851) and the EurValve project (funded by the European Union’s Horizon 2020 research program under Grant No. 689617).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Al-Maisary S, Engelhardt S, Graser B, Wolf I, Karck M, De Simone R (2017) Computer-based comparison of different methods for selecting mitral annuloplasty ring size. J Cardiothorac Surg 12(1):1–7CrossRefGoogle Scholar
  2. 2.
    Bach DS (2010) Echo/doppler evaluation of hemodynamics after aortic valve replacement: principles of interrogation and evaluation of high gradients. JACC Cardiovasc Imaging 3(3):296–304CrossRefGoogle Scholar
  3. 3.
    Baumgartner H, Falk V, Bax JJ, De Bonis M, Hamm C, Holm PJ, Iung B, Lancellotti P, Lansac E, Rodriguez Muñoz D, Rosenhek R, Sjögren J, Tornos Mas P, Vahanian A, Walther T, Wendler O, Windecker S, Zamorano JL (2017) 2017 ESC/EACTS guidelines for the management of valvular heart disease. Eur Heart J 38(36):2739–2791CrossRefGoogle Scholar
  4. 4.
    Bolling SF, Li S, Brien SMO, Brennan JM, Prager RL, Gammie JS, Surgery C, Arbor A, Clinical D (2010) Predictors of mitral valve repair: clinical and surgeon factors. Ann Thorac Surg 90(6):1904–1912CrossRefGoogle Scholar
  5. 5.
    Bonis MD, Ferrara D, Taramasso M, Calabrese MC, Verzini A, Buzzatti N, Alfieri O (2012) Mitral replacement or repair for functional mitral regurgitation in dilated and ischemic cardiomyopathy: Is it really the same? Ann Thorac Surg 94(1):44–51CrossRefGoogle Scholar
  6. 6.
    Borger MA, Alam A, Murphy PM, Doenst T, David TE (2006) Chronic ischemic mitral regurgitation: Repair, replace or rethink? Ann Thorac Surg 81(3):1153–1161CrossRefGoogle Scholar
  7. 7.
    Brüning J, Hellmeier F, Yevtushenko P, Kühne T, Goubergrits L (2018) Uncertainty quantification for non-invasive assessment of pressure drop across a coarctation of the aorta using CFD. Cardiovasc Eng Technol 8:582–596CrossRefGoogle Scholar
  8. 8.
    Chan KL, Chen S-Y, Mesana T, Lam BK (2017) Development of mitral stenosis after mitral valve repair: importance of mitral valve area. Can J Cardiol 33(12):1701–1707CrossRefGoogle Scholar
  9. 9.
    Hellmeier F, Nordmeyer S, Yevtushenko P, Bruening J, Berger F, Kuehne T, Goubergrits L, Kelm M (2018) Hemodynamic evaluation of a biological and mechanical aortic valve prosthesis using patient-specific MRI-based CFD. Artif Organs 42(1):49–57CrossRefGoogle Scholar
  10. 10.
    Iung B, Baron G, Tornos P, Gohlke-Bärwolf C, Butchart EG, Vahanian A (2007) Valvular heart disease in the community: a European experience. Curr Probl Cardiol 32(11):609–661CrossRefGoogle Scholar
  11. 11.
    Kainuma S, Taniguchi K, Daimon T, Sakaguchi T, Funatsu T, Kondoh H, Miyagawa S, Takeda K, Shudo Y, Masai T, Fujita S, Nishino M, Sawa Y (2011) Does stringent restrictive annuloplasty for functional mitral regurgitation cause functional mitral stenosis and pulmonary hypertension? Circulation 124(11 suppl 1):S97–S106CrossRefGoogle Scholar
  12. 12.
    Karimi S, Dabagh M, Vasava P, Dadvar M, Dabir B, Jalali P (2014) Effect of rheological models on the hemodynamics within human aorta: CFD study on ct image-based geometry. J Non-Newton Fluid Mech 207(Supplement C):42–52CrossRefGoogle Scholar
  13. 13.
    Khodarahmi I, Shakeri M, Kotys-Traughber M, Fischer S, Sharp MK, Amini A (2012) Accuracy of flow measurement with phase contrast MRI in a stenotic phantom: Where should flow be measured? J Cardiovasc Magn Reson 14(1):P219CrossRefGoogle Scholar
  14. 14.
    Magne J, Sénéchal M, Mathieu P, Dumesnil JG, Dagenais F, Pibarot P (2008) Restrictive annuloplasty for ischemic mitral regurgitation may induce functional mitral stenosis. J Am College Cardiol 51(17):1692–1701CrossRefGoogle Scholar
  15. 15.
    Neugebauer M, Glöckler M, Goubergrits L, Kelm M, Kuehne T, Hennemuth A (2016) Interactive virtual stent planning for the treatment of coarctation of the aorta. Int J Comput Assist Radiol Surg 11(1):133–144CrossRefGoogle Scholar
  16. 16.
    Nkomo VT, Gardin JM, Skelton TN, Gottdiener JS, Scott CG, Enriquez-Sarano M (2006) Burden of valvular heart diseases: a population-based study. Lancet 368(9540):1005–1011CrossRefGoogle Scholar
  17. 17.
    Quiñones MA, Otto CM, Stoddard M, Waggoner A, Zoghbi WA (2002) Recommendations for quantification of Doppler echocardiography: a report from the Doppler Quantification Task Force of the Nomenclature and Standards Committee of the American Society of Echocardiography. J Am Soc Echocardiogr Off Publ Am Soc Echocardiogr 15(2):167–184CrossRefGoogle Scholar
  18. 18.
    Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52(3–4):591–611.  https://doi.org/10.1093/biomet/52.3-4.591 CrossRefGoogle Scholar
  19. 19.
    Stevanella M, Maffessanti F, Conti CA, Votta E, Arnoldi A, Lombardi M, Parodi O, Caiani EG, Redaelli A (2011) Mitral valve patient-specific finite element modeling from cardiac MRI: application to an annuloplasty procedure. Cardiovasc Eng Technol 2(2):66–76CrossRefGoogle Scholar
  20. 20.
    Tautz L, Neugebauer M, Hüllebrand M, Vellguth K, Degener F, Sündermann S, Wamala I, Goubergrits L, Kuehne T, Falk V, Hennemuth A (2018) Extraction of open-state mitral valve geometry from CT volumes. Int J Comput Assist Radiol Surg 13:1741–1754CrossRefGoogle Scholar
  21. 21.
    Taylor CA (2014) Method and system for patient-specific modeling of blood flow, US Patent 8,734,357Google Scholar
  22. 22.
    Taylor CA, Fonte TA, Min JK (2013) Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve. J Am College Cardiol 61(22):2233–2241CrossRefGoogle Scholar
  23. 23.
    Vellguth K, Brüning J, Goubergrits L, Tautz L, Hennemuth A, Kertzscher U, Degener F, Kelm M, Sündermann S, Kuehne T (2018) Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image-based CFD. Int J Comput Assist Radiol Surg 13(11):1795–1805CrossRefGoogle Scholar
  24. 24.
    Vellguth K, Tautz L, Hennemuth A, Degener F, Wamala I, Sündermann S. CT segmented mitral valve geometries. open data on Zenodo.org.  https://doi.org/10.5281/zenodo.2702813
  25. 25.
    Wenk JF, Zhang Z, Cheng G, Malhotra D, Acevedo-Bolton G, Burger M, Suzuki T, Saloner DA, Wallace AW, Guccione JM, Ratcliffe MB (2010) First finite element model of the left ventricle with mitral valve: insights into ischemic mitral regurgitation. Ann Thorac Surg 89(5):1546–1553CrossRefGoogle Scholar
  26. 26.
    Wentland A, Wieben O, Korosec F, Haughton V (2010) Accuracy and reproducibility of phase-contrast MR imaging measurements for CSF flow. Am J Neuroradiol 31(7):1331–1336CrossRefGoogle Scholar
  27. 27.
    Zoghbi WA, Chambers JB, Dumesnil JG, Foster E, Gottdiener JS, Grayburn PA, Khandheria BK, Levine RA, Marx GR, Miller FA, Nakatani S, Quiñones MA, Rakowski H, Rodriguez LL, Swaminathan M, Waggoner AD, Weissman NJ, Zabalgoitia M (2009) Recommendations for evaluation of prosthetic valves with echocardiography and doppler ultrasound. J Am Soc Echocardiogr 22(9):975–1014CrossRefGoogle Scholar

Copyright information

© CARS 2019

Authors and Affiliations

  • Katharina Vellguth
    • 1
    Email author
  • Jan Brüning
    • 1
  • Lennart Tautz
    • 1
    • 4
  • Franziska Degener
    • 1
    • 2
  • Isaac Wamala
    • 2
  • Simon Sündermann
    • 1
  • Ulrich Kertzscher
    • 1
  • Titus Kuehne
    • 1
    • 2
    • 3
  • Anja Hennemuth
    • 1
    • 4
  • Volkmar Falk
    • 1
    • 2
    • 3
  • Leonid Goubergrits
    • 1
  1. 1.Charité – Universitätsmedizin BerlinBerlinGermany
  2. 2.German Heart Institute Berlin – DHZBBerlinGermany
  3. 3.DZHK (German Centre for Cardiovascular Research), partner site BerlinBerlinGermany
  4. 4.Fraunhofer MEVISBremenGermany

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