Advertisement

Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image-based CFD

  • Katharina Vellguth
  • Jan Brüning
  • Leonid Goubergrits
  • Lennart Tautz
  • Anja Hennemuth
  • Ulrich Kertzscher
  • Franziska Degener
  • Marcus Kelm
  • Simon Sündermann
  • Titus Kuehne
Original Article
  • 108 Downloads

Abstract

Purpose

Severe mitral valve regurgitation can either be treated by a replacement or a repair of the valve. The latter is recommended due to lower perioperative mortality and better long-term survival. On the other hand, recurrence rates after mitral valve repair are high compared to those after replacements and the repair intervention can cause induced mitral valve stenosis. So far, there are no methods to predict the hemodynamic outcome of a chosen treatment or to compare different treatment options in advance. To overcome this, diastolic mitral valve hemodynamics are simulated using computational fluid dynamics after different virtual treatments of the valve.

Methods

The left ventricular geometry of one patient was reconstructed using trans-esophageal echocardiography and computed tomography data. Pre-op hemodynamics are simulated using a referenced wall model to avoid expansive modeling of wall motion. Subsequently, the flow structures are compared to in vivo measurements. After manipulating the patient-specific geometry in order to mimic a restrictive mitral annuloplasty as well as a MitraClip intervention, hemodynamics results are calculated.

Results

Good agreements exist between calculated pre-op hemodynamics and in vivo measurements. The virtual annuloplasty did not result in any remarkable change of hemodynamics. Neither the pressure drop nor the velocity field showed strong differences. In contrast, the virtual MitraClip intervention led to a complete change in blood flow structures as well as an elevated pressure drop across the valve.

Conclusion

The presented approach allows fast simulation of the diastolic hemodynamic situation before and after treatment of a mitral valve insufficiency. However, this approach is limited to the early diastolic phase of the cardiac cycle and needs to be validated using a larger sample size.

Keywords

Mitral valve insufficiency Patient specific Hemodynamic Virtual treatment planning CFD 

Notes

Compliance with ethical standards

Funding

This work is part of the BMBF VIP+ project DSSMitral (funded by the German Federal Ministry of Education and Research under grant 03VP00851).

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 Helsinki declaration 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.
    Acker MA, Parides MK, Perrault LP, Moskowitz AJ, Gelijns AC, Voisine P, Smith PK, Hung JW, Blackstone EH, Puskas JD, Argenziano M, Gammie JS, Mack M, Ascheim DD, Bagiella E, Moquete EG, Ferguson TB, Horvath KA, Geller NL, Miller MA, Woo YJ, D’Alessandro DA, Ailawadi G, Dagenais F, Gardner TJ, O’Gara PT, Michler RE, Kron IL (2014) Mitral-valve repair versus replacement for severe ischemic mitral regurgitation. N Engl J Med 370(1):23–32 (PMID: 24245543)CrossRefPubMedGoogle Scholar
  2. 2.
    Al-Wakeel N, Fernandes JF, Amiri A, Siniawski H, Goubergrits L, Berger F, Kuehne T (2015) Hemodynamic and energetic aspects of the left ventricle in patients with mitral regurgitation before and after mitral valve surgery. J Magn Reson Imaging 42(6):1705–1712CrossRefPubMedGoogle Scholar
  3. 3.
    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):296–304Google Scholar
  4. 4.
    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):2739–2791CrossRefPubMedGoogle 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):44–51CrossRefPubMedGoogle 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):1153–1161CrossRefPubMedGoogle Scholar
  7. 7.
    Bothe W, Miller DC, Doenst T (2013) Sizing for mitral annuloplasty: where does science stop and voodoo begin? Ann Thorac Surg 95(4):1475–1483CrossRefPubMedGoogle Scholar
  8. 8.
    Cheng Y, Oertel H, Schenkel T (2005) Fluid-structure coupled cfd simulation of the left ventricular flow during filling phase. Ann Biomed Eng 33(5):567–576CrossRefPubMedGoogle Scholar
  9. 9.
    Chnafa C, Mendez S, Nicoud F (2014) Image-based large-eddy simulation in a realistic left heart. Comput Fluids 94(Supplement C):173–187CrossRefGoogle Scholar
  10. 10.
    Chnafa C, Mendez S, Nicoud F (2016) Image-based simulations show important flow fluctuations in a normal left ventricle: what could be the implications? Ann Biomed Eng 44(11):3346–3358CrossRefPubMedGoogle Scholar
  11. 11.
    Doost SN, Ghista D, Su B, Zhong L, Morsi YS (2016) Heart blood flow simulation: a perspective review. BioMed Eng OnLine 15(1):101CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Drach A, Khalighi AH, Sacks MS (2018) A comprehensive pipeline for multi-resolution modeling of the mitral valve: validation, computational efficiency, and predictive capability. Int J Numer Methods Biomed Eng 34(2):e2921 (CNM-May-17-0128.R1)CrossRefGoogle Scholar
  13. 13.
    Gillinov A, Wierup PN, Blackstone EH, Bishay ES, Cosgrove DM, White J, Lytle BW, McCarthy PM (2001) Is repair preferable to replacement for ischemic mitral regurgitation? J Thorac Cardiovasc Surg 122(6):1125–1141CrossRefPubMedGoogle Scholar
  14. 14.
    Goldstein D, Moskowitz AJ, Gelijns AC, Ailawadi G, Parides MK, Perrault LP, Hung JW, Voisine P, Dagenais F, Gillinov AM, Thourani V, Argenziano M, Gammie JS, Mack M, Demers P, Atluri P, Rose EA, OSullivan K, Williams DL, Bagiella E, Michler RE, Weisel RD, Miller MA, Geller NL, Taddei-Peters WC, Smith PK, Moquete E, Overbey JR, Kron IL, OGara PT, Acker MA (2016) Two-year outcomes of surgical treatment of severe ischemic mitral regurgitation. N Engl J Med 374(4):344–353 (PMID: 26550689)CrossRefPubMedGoogle Scholar
  15. 15.
    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):609–661CrossRefPubMedGoogle Scholar
  16. 16.
    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
  17. 17.
    Kheradvar A, Assadi R, Falahatpisheh A, Sengupta PP (2012) Assessment of transmitral vortex formation in patients with diastolic dysfunction. J Am Soc Echocardiogr 25(2):220–227CrossRefPubMedGoogle Scholar
  18. 18.
    Kheradvar A, Falahatpisheh A (2012) The effects of dynamic saddle annulus and leaflet length on transmitral flow pattern and leaflet stress of a bileaflet bioprosthetic mitral valve. J Heart Valve Dis 21(2):225–233PubMedGoogle Scholar
  19. 19.
    Kunzelman K, Reimink MS, Verrier ED, Cochran RP (1996) Replacement of mitral valve posterior chordae tendineae with expanded polytetrafluoroethylene suture: a finite element study. J Card Surg 11(2):136–145CrossRefPubMedGoogle Scholar
  20. 20.
    Lantz J, Henriksson L, Persson A, Karlsson M, Ebbers T (2016) Patient-specific simulation of cardiac blood flow from high-resolution computed tomography. J Biomech Eng 138(12):121004CrossRefGoogle Scholar
  21. 21.
    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 Coll Cardiol 51(17):1692–1701CrossRefPubMedGoogle Scholar
  22. 22.
    Mittal R, Seo JH, Vedula V, Choi YJ, Liu H, Huang HH, Jain S, Younes L, Abraham T, George RT (2016) Computational modeling of cardiac hemodynamics: current status and future outlook. J Comput Phys 305:1065–1082CrossRefGoogle Scholar
  23. 23.
    Neugebauer M, Tautz L, Hüllebrand M, Sündermann S, Degener F, Kuehne T, Falk V, Hennemuth A (2018) Virtual downsizing for decision support in mitral valve repair. In: Proceedings of CARS 2018 (Accepted)Google Scholar
  24. 24.
    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):1005–1011CrossRefPubMedGoogle Scholar
  25. 25.
    Pedrizzetti G, Domenichini F (2015) Left ventricular fluid mechanics: the long way from theoretical models to clinical applications. Ann Biomed Eng 43(1):2640CrossRefGoogle Scholar
  26. 26.
    Peskin CS (1972) Flow patterns around heart valves: a numerical method. J Comput Phys 10(2):252–271CrossRefGoogle Scholar
  27. 27.
    Schenkel T, Malve M, Reik M, Markl M, Jung B, Oertel H (2009) Mri-based cfd analysis of flow in a human left ventricle: methodology and application to a healthy heart. Ann Biomed Eng 37(3):503–515CrossRefPubMedGoogle Scholar
  28. 28.
    Sun W, Martin C, Pham T (2014) Computational modeling of cardiac valve function and intervention. Annu Rev Biomed Eng 16(1):53–76 PMID: 24819475CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Tautz L, Hüllebrand M, Vellguth K, Sündermann S, Degener F, Kuehne T, Falk V, Hennemuth A (2018) Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image based CFD. In: Proceedings of CARS 2018 (Accepted)Google Scholar
  30. 30.
    Votta E, Le TB, Stevanella M, Fusini L, Caiani EG, Redaelli A, Sotiropoulos F (2013) Toward patient-specific simulations of cardiac valves: state-of-the-art and future directions. J Biomech 46(2):217–228 (special Issue: Biofluid Mechanics)CrossRefPubMedGoogle Scholar
  31. 31.
    Zoghbi WA, Chambers JB, Dumesnil JG, Foster E, Gottdiener JS, Grayburn PA, Khandheria BK, Levine RA, Marx GR, Miller FA, Nakatani S, Quiones 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):975–1014CrossRefPubMedGoogle Scholar

Copyright information

© CARS 2018

Authors and Affiliations

  • Katharina Vellguth
    • 1
  • Jan Brüning
    • 1
  • Leonid Goubergrits
    • 1
  • Lennart Tautz
    • 1
  • Anja Hennemuth
    • 1
  • Ulrich Kertzscher
    • 1
  • Franziska Degener
    • 1
    • 2
  • Marcus Kelm
    • 1
    • 2
  • Simon Sündermann
    • 2
  • Titus Kuehne
    • 1
    • 2
  1. 1.Charité – Universitätsmedizin BerlinBerlinGermany
  2. 2.German Heart Institute Berlin – DHZBBerlinGermany

Personalised recommendations