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Is MRI-Based CFD Able to Improve Clinical Treatment of Coarctations of Aorta?

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Abstract

Pressure drop associated with coarctation of the aorta (CoA) can be successfully treated surgically or by stent placement. However, a decreased life expectancy associated with altered aortic hemodynamics was found in long-term studies. Image-based computational fluid dynamics (CFD) is intended to support particular diagnoses, to help in choosing between treatment options, and to improve performance of treatment procedures. This study aimed to prove the ability of CFD to improve aortic hemodynamics in CoA patients. In 13 patients (6 males, 7 females; mean age 25 ± 14 years), we compared pre- and post-treatment peak systole hemodynamics [pressure drops and wall shear stress (WSS)] vs. virtual treatment as proposed by biomedical engineers. Anatomy and flow data for CFD were based on MRI and angiography. Segmentation, geometry reconstruction and virtual treatment geometry were performed using the software ZIBAmira, whereas peak systole flow conditions were simulated with the software ANSYS® Fluent®. Virtual treatment significantly reduced pressure drop compared to post-treatment values by a mean of 2.8 ± 3.15 mmHg, which significantly reduced mean WSS by 3.8 Pa. Thus, CFD has the potential to improve post-treatment hemodynamics associated with poor long-term prognosis of patients with coarctation of the aorta. MRI-based CFD has a huge potential to allow the slight reduction of post-treatment pressure drop, which causes significant improvement (reduction) of the WSS at the stenosis segment.

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Abbreviations

CoA:

Coarctation of the aorta

TCC:

Total cavopulmonary connections

MRI:

Magnetic resonance imaging

VEC-MRI:

Velocity-encoded MRI

WH:

Whole heart

CFD:

Computational fluid dynamics

WSS:

Wall shear stress

3D:

Three-dimensional

4D:

Four-dimensional

SD:

Standard deviation

DS:

Degree of stenosis

References

  1. Arbia, G., C. Corsini, M. Esmaily Moghadam, A. L. Marsden, G. Migliavacca, T. Y. Pennati, I. E. Hsia, and Modeling of Congenital Hearts Alliance (MOCHA) Investigators. Numerical blood flow simulation in surgical corrections: what we need for an accurate analysis? J. Surg. Res. 186(1):44–55, 2014.

    Article  PubMed  Google Scholar 

  2. Chiu, J. J., and S. Chien. Effects of disturbed flow on vascular endothelium: pathophysiological basis and clinical perspectives. Physiol. Rev. 91(1):327–387, 2011.

    Article  PubMed  Google Scholar 

  3. Cohen, M., V. Fuster, P. M. Steele, D. Driscoll, and D. C. McGoon. Coarctation of the aorta. Long-term follow-up and prediction of outcome after surgical correction. Circulation 80:840–845, 1989.

    Article  CAS  PubMed  Google Scholar 

  4. Corno, A. F., C. Vergara, C. Subramanian, R. A. Johnson, T. Passerini, A. Veneziani, L. Formaggia, N. Alphonso, A. Quarteroni, and J. C. Jarvis. Assisted Fontan procedure: animal and in vitro models and computational fluid dynamics study. Interact. Cardiovasc. Thoracic Surg. 10:679–684, 2010.

    Article  Google Scholar 

  5. DeCampli, W. M., I. R. Arqueta-Morales, E. Divo, and A. J. Kassab. Computational fluid dynamics in congenital heart disease. Cardiol. Young 22(6):800–808, 2012.

    Article  PubMed  Google Scholar 

  6. Forbes, T. J., D. W. Kim, W. Du, D. R. Turner, R. Holzer, Z. Amin, Z. Hijazi, A. Ghasemi, J. J. Rome, D. Nykanen, E. Zahn, C. Cowley, M. Hoyer, D. Waight, D. Gruenstein, A. Javois, S. Foerster, J. Kreutzer, N. Sullivan, A. Khan, C. Owada, D. Hagler, S. Lim, J. Canter, and T. Zellers. Comparison of surgical, stent, and balloon angioplasty treatment of native coarctation of the aorta: an observational study by the CCISC (Congenital Cardiovascular Interventional Study Consortium). J. Am. Coll. Cardiol. 58:2664–2674, 2011.

    Article  PubMed  Google Scholar 

  7. Goubergrits, L., U. Kertzscher, B. Schöneberg, E. Wellnhofer, Ch. Petz, and H.-Ch. Hege. CFD analysis in an anatomically realistic coronary artery model based on non-invasive 3D imaging: comparison of magnetic resonance imaging with computed tomography. Int. J. Cardiovasc. Imaging 24:411–421, 2008.

    Article  PubMed  Google Scholar 

  8. Goubergrits, L., R. Mevert, P. Yevtushenko, J. Schaller, U. Kertzscher, S. Meier, S. Schubert, E. Riesenkampff, and T. Kuehne. The impact of MRI-based inflow for the hemodynamic evaluation of aortic coarctation. Ann. Biomed. Eng. 41:2575–2587, 2013.

    Article  CAS  PubMed  Google Scholar 

  9. Goubergrits, L., E. Riesenkampff, P. Yevtushenko, J. Schaller, U. Kertzscher, A. Hennemuth, F. Berger, S. Schubert, and T. Kuehne. MRI-based computational fluid dynamics for diagnosis and treatment prediction: clinical validation study in patients with coarctation of aorta. In press, doi: 10.1002/jmri.24639, 2014.

  10. Humphrey, J. D. Vascular adaptation and mechanical homeostasis at tissue, cellular, and sub-cellular levels. Cell Biochem. Biophys. 50(2):53–78, 2008.

    Article  CAS  PubMed  Google Scholar 

  11. Itu, L., P. Sharma, and K. Ralovich. Non-invasive hemodynamic assessment of aortic coarctation: validation with in vivo measurements. Ann. Biomed. Eng. 41:669–681, 2013.

    Article  PubMed  Google Scholar 

  12. LaDisa, J. F., C. A. Taylor, and J. A. Feinstein. Aortic coarctation: recent developments in experimental and computational methods to assess treatments for this simple condition. Prog. Pediatr. Cardiol. 30(1):45–49, 2010.

    Article  PubMed Central  PubMed  Google Scholar 

  13. LaDisa, Jr., J. F., C. Alberto Figueroa, I. E. Vignon-Clementel, H. J. Kim, N. Xiao, L. M. Ellwein, F. P. Chan, J. A. Feinstein, and C. A. Taylor. Computational simulations for aortic coarctation: representative results from a sampling of patients. J. Biomech. Eng. 133(9):091008, 2011.

    Article  PubMed  Google Scholar 

  14. Lantz, J., and M. Karlsson. Large eddy simulation of LDL surface concentration in a subject specific human aorta. J. Biomech. 45:537–542, 2012.

    Article  PubMed  Google Scholar 

  15. Marsden, A. L. Simulation based planning of surgical interventions in pediatric cardiology. Phys. Fluids. 25(10):101303, 2013.

    Article  Google Scholar 

  16. Marsden, A. L. Optimization in cardiovascular modeling. Ann. Rev. Fluid Mech. 46:519–546, 2014.

    Article  Google Scholar 

  17. Marsden, A. L., I. E. Vignon-Clementel, F. P. Chan, J. A. Feinstein, and C. A. Taylor. Effects of exercise and respiration on hemodynamic efficiency in CFD simulations of the total cavopulmonary connection. Ann. Biomed. Eng. 35(2):250–263, 2007.

    Article  PubMed  Google Scholar 

  18. Midulla, M., R. Moreno, A. Baali, M. Chau, A. Negre-Salvayre, F. Nicoud, J. P. Pruvo, S. Haulon, and H. Rousseau. Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations. Eur. Radiol. 22(10):2094–2102, 2012.

    Article  PubMed  Google Scholar 

  19. Morbiducci, U., R. Ponzini, D. Gallo, C. Bignardi, and G. Rizzo. Inflow boundary conditions for image-based computational hemodynamics: impact of idealized versus measured velocity profiles in the human aorta. J. Biomech. 46(1):102–109, 2013.

    Article  PubMed  Google Scholar 

  20. Nordmeyer, S., E. Riesenkampff, G. Crelier, A. Khasheei, B. Schnackenburg, F. Berger, and T. Kuehne. Flow-sensitive four-dimensional cine magnetic resonance imaging for offline blood flow quantification in multiple vessels: a validation study. J. Magn. Reson. Imaging 32:677–683, 2010.

    Article  PubMed  Google Scholar 

  21. Olivieri, L. J., D. A. de Zélicourt, C. M. Haggerty, K. Ratnayaka, R. R. Cross, and A. P. Yoganathan. Hemodynamic modeling of surgically repaired coarctation of the aorta. Cardiovasc. Eng. Technol. 2(1):288–295, 2011.

    Article  PubMed Central  PubMed  Google Scholar 

  22. Prakash, S., and C. R. Ethier. Requirements for mesh resolution in 3-D computational hemodynamics. J. Biomech. Eng. 123(2):134–144, 2001.

    Article  CAS  PubMed  Google Scholar 

  23. Rourke, M. F., and T. B. Cartmill. Influence of aortic coarctation on pulsatile hemodynamics in the proximal aorta. Circulation 44(2):281–292, 1971.

    Article  Google Scholar 

  24. Ryval, J., A. G. Straatman, and D. A. Steinamn. Two-equation turbulence modeling of pulsatile flow in a stenosed tube. J. Biomech. Eng. 126(5):625, 2004.

    Article  CAS  PubMed  Google Scholar 

  25. Wang, C., K. Pekkan, D. De Zélicourt, M. Horner, A. Parihar, A. Kulkarni, and A. P. Yoganathan. Progress in the CFD modeling of flow instabilities in anatomical total cavopulmonary connections. Ann. Biomed. Eng. 11:1840–1856, 2007.

    Article  Google Scholar 

  26. Wellnhofer, E., J. Osman, U. Kertzscher, K. Affeld, E. Fleck, and L. Goubergrits. Flow simulation studies in coronary arteries—Impact of side-branches. Atherosclerosis 213:475–481, 2010.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This study was supported by the German Research Foundation (DFG).

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Authors and Affiliations

  1. Biofluid Mechanics Laboratory, Charité – Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany

    L. Goubergrits, P. Yevtushenko, J. Schaller & U. Kertzscher

  2. Department of Congenital Heart Disease and Pediatric Cardiology, Deutsches Herzzentrum Berlin, Augustenburger Platz 1, 13353, Berlin, Germany

    L. Goubergrits, E. Riesenkampff, F. Berger & T. Kuehne

  3. Non-Invasive Cardiac Imaging in Congenital Heart Disease Unit, Charité – Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany

    T. Kuehne

Authors
  1. L. Goubergrits
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  2. E. Riesenkampff
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  3. P. Yevtushenko
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  4. J. Schaller
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  5. U. Kertzscher
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  6. F. Berger
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  7. T. Kuehne
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Correspondence to L. Goubergrits.

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Associate Editor Diego Gallo oversaw the review of this article.

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Goubergrits, L., Riesenkampff, E., Yevtushenko, P. et al. Is MRI-Based CFD Able to Improve Clinical Treatment of Coarctations of Aorta?. Ann Biomed Eng 43, 168–176 (2015). https://doi.org/10.1007/s10439-014-1116-3

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  • DOI: https://doi.org/10.1007/s10439-014-1116-3

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