Skip to main content
Log in

Image-Based Simulations Show Important Flow Fluctuations in a Normal Left Ventricle: What Could be the Implications?

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

Intra-cardiac flow has been explored for decades but there is still no consensus on whether or not healthy left ventricles (LV) may harbour turbulent-like flow despite its potential physiological and clinical relevance. The purpose of this study is to elucidate if a healthy LV could harbour flow instabilities, using image-based computational fluid dynamics (CFD). 35 cardiac cycles were simulated in a patient-specific left heart model obtained from cardiovascular magnetic resonance (CMR). The model includes the valves, atrium, ventricle, papillary muscles and ascending aorta. We computed phase-averaged flow patterns, fluctuating kinetic energy (FKE) and associated frequency components. The LV harbours disturbed flow during diastole with cycle-to-cycle variations. However, phase-averaged velocity fields much resemble those of CMR measurements and usually reported CFD results. The peak FKE value occurs during the E wave deceleration and reaches 25% of the maximum phase-averaged flow kinetic energy. Highest FKE values are predominantly located in the basal region and their frequency content reach more than 200 Hz. This study suggests that high-frequency flow fluctuations in normal LV may be common, implying deficiencies in the hypothesis usually made when computing cardiac flows and highlighting biases when deriving quantities from velocity fields measured with CMR.

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

Access this article

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

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  1. Barré, D., M. Kraushaar, G. Staffelbach, V. Moureau, and L. Y. M. Gicquel. Compressible and low Mach number LES of a swirl experimental burner. Comptes Rendus Mécanique 341:277–287, 2013.

    Article  Google Scholar 

  2. Baya Toda, H., O. Cabrit, K. Truffin, G. Bruneaux, and F. Nicoud. Assessment of subgrid-scale models with a large-eddy simulation-dedicated experimental database: the pulsatile impinging jet in turbulent cross-flow. Phys. Fluids 26:075108, 2014.

    Article  Google Scholar 

  3. Carlsson, M., E. Heiberg, J. Toger, and H. Arheden. Quantification of left and right ventricular kinetic energy using four-dimensional intracardiac magnetic resonance imaging flow measurements. AJP Hear. Circ. Physiol. 302:H893–H900, 2012.

    Article  CAS  Google Scholar 

  4. Celik, I. B., Z. N. Cehreli, and I. Yavuz. Index of resolution quality for large eddy simulations. J. Fluids Eng. 127:949, 2005.

    Article  Google Scholar 

  5. Charonko, J. J., R. Kumar, K. Stewart, W. C. Little, and P. P. Vlachos. Vortices formed on the mitral valve tips aid normal left ventricular filling. Ann. Biomed. Eng. 41:1049–1061, 2013.

    Article  PubMed  Google Scholar 

  6. Cheng, C. P., D. Parker, and C. A. Taylor. Quantification of Wall shear stress in large blood vessels using Lagrangian interpolation functions with cine phase-contrast magnetic resonance imaging. Ann. Biomed. Eng. 30:1020–1032, 2002.

    Article  PubMed  Google Scholar 

  7. Chien, S. Shear dependence of effective cell volume as a determinant of blood viscosity. Science (80-) 168:977–979, 1970.

    Article  CAS  Google Scholar 

  8. Chnafa, C. Using image-based large-eddy simulations to investigate the intracardiac flow and its turbulent nature. Montpellier: University of Montpellier, 2014.

    Google Scholar 

  9. Chnafa, C., S. Mendez, R. Moreno, and F. Nicoud. Using image-based CFD to investigate the intracardiac turbulence. In: Modeling the Heart and the Circulatory System, edited by A. Quarteroni. New-York: Springer, 2015, pp. 97–117.

    Google Scholar 

  10. Chnafa, C., S. Mendez, and F. Nicoud. Image-based large-eddy simulation in a realistic left heart. Comput. Fluids 94:173–187, 2014.

    Article  Google Scholar 

  11. Collins, S. P., P. Arand, C. J. Lindsell, W. F. Peacock, and A. B. Storrow. Prevalence of the third and fourth heart sound in asymptomatic adults. Congest. Hear. Fail. 11:242–247, 2005.

    Article  Google Scholar 

  12. Davies, P. F., A. Remuzzi, E. J. Gordon, C. F. Dewey, and M. A. Gimbrone. Turbulent fluid shear stress induces vascular endothelial cell turnover in vitro. Proc. Natl. Acad. Sci. USA 83:2114–2117, 1986.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Domenichini, F., G. Pedrizzetti, and B. Baccani. Three-dimensional filling flow into a model left ventricle. J. Fluid Mech. 539:179, 2005.

    Article  Google Scholar 

  14. Domenichini, F., G. Querzoli, A. Cenedese, and G. Pedrizzetti. Combined experimental and numerical analysis of the flow structure into the left ventricle. J. Biomech. 40:1988–1994, 2007.

    Article  CAS  PubMed  Google Scholar 

  15. Dyverfeldt, P., M. Bissell, A. J. Barker, A. F. Bolger, C.-J. Carlhäll, T. Ebbers, C. J. Francios, A. Frydrychowicz, J. Geiger, D. Giese, M. D. Hope, P. J. Kilner, S. Kozerke, S. Myerson, S. Neubauer, O. Wieben, and M. Markl. 4D flow cardiovascular magnetic resonance consensus statement. J. Cardiovasc. Magn. Reson. 17:72, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Dyverfeldt, P., M. D. Hope, E. E. Tseng, and D. Saloner. Magnetic resonance measurement of turbulent kinetic energy for the estimation of irreversible pressure loss in aortic stenosis. JACC Cardiovasc. Imaging 6:64–71, 2013.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Dyverfeldt, P., J.-P. E. Kvitting, C. J. Carlhäll, G. Boano, A. Sigfridsson, U. Hermansson, A. F. Bolger, J. Engvall, and T. Ebbers. Hemodynamic aspects of mitral regurgitation assessed by generalized phase-contrast MRI. J. Magn. Reson. Imaging 33:582–588, 2011.

    Article  PubMed  Google Scholar 

  18. Dyverfeldt, P., J. P. E. Kvitting, A. Sigfridsson, J. Engvall, A. F. Bolger, and T. Ebbers. Assessment of fluctuating velocities in disturbed cardiovascular blood flow: in vivo feasibility of generalized phase-contrast MRI. J. Magn. Reson. Imaging 28:655–663, 2008.

    Article  PubMed  Google Scholar 

  19. Falahatpisheh, A., and A. Kheradvar. High-speed particle image velocimetry to assess cardiac fluid dynamics in vitro: from performance to validation. Eur. J. Mech. B/Fluids 35:2–8, 2012.

    Article  Google Scholar 

  20. Glower, D. D., R. L. Murrah, C. O. Olsen, J. W. Davis, and J. S. Rankin. Mechanical correlates of the third heart sound. J. Am. Coll. Cardiol. 19:450–457, 1992.

    Article  CAS  PubMed  Google Scholar 

  21. Hendabadi, S., J. Bermejo, Y. Benito, R. Yotti, F. Fernández-Avilés, J. C. Del Álamo, and S. C. Shadden. Topology of blood transport in the human left ventricle by novel processing of doppler echocardiography. Ann. Biomed. Eng. 41:2603–2616, 2013.

    Article  PubMed  Google Scholar 

  22. Hult, P., T. Fjällbrant, B. Wranne, and P. Ask. Detection of the third heart sound using a tailored wavelet approach. Med. Biol. Eng. Comput. 42:253–258, 2004.

    Article  CAS  PubMed  Google Scholar 

  23. Kanski, M., P. M. Arvidsson, J. Töger, R. Borgquist, E. Heiberg, M. Carlsson, and H. Arheden. Left ventricular fluid kinetic energy time curves in heart failure from cardiovascular magnetic resonance 4D flow data. J. Cardiovasc. Magn. Reson. 17:111, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Khalafvand, S. S., E. Y. K. Ng, L. Zhong, and T. K. Hung. Fluid-dynamics modelling of the human left ventricle with dynamic mesh for normal and myocardial infarction: preliminary study. Comput. Biol. Med. 42:863–870, 2012.

    Article  CAS  PubMed  Google Scholar 

  25. Kheradvar, A., and M. Gharib. On mitral valve dynamics and its connection to early diastolic flow. Ann. Biomed. Eng. 37:1–13, 2009.

    Article  PubMed  Google Scholar 

  26. Kilner, P. J., G. Z. Yang, A. J. Wilkes, R. H. Mohiaddin, D. N. Firmin, and M. H. Yacoub. Asymmetric redirection of flow through the heart. Nature 404:759–761, 2000.

    Article  CAS  PubMed  Google Scholar 

  27. Kono, T., H. Rosman, M. Alam, P. D. Stein, H. N. Sabbah, D. Stein, and N. Wbbah. Hemodynamic correlates of the third heart sound during the evolution of chronic heart failure. Am. J. Med. 21:419–423, 1992.

    Google Scholar 

  28. Le, T. B., and F. Sotiropoulos. On the three-dimensional vortical structure of early diastolic flow in a patient-specific left ventricle. Eur. J. Mech. B/Fluids 35:20–24, 2012.

    Article  PubMed  Google Scholar 

  29. Long, Q., R. Merrifield, X. Y. Xu, P. Kilner, D. N. Firmin, and G.-Z. Yang. Subject-specific computational simulation of left ventricular flow based on magnetic resonance imaging. Proc. Inst. Mech. Eng. H 222:475–485, 2008.

    Article  CAS  PubMed  Google Scholar 

  30. Lu, P. C., H. C. Lai, and J. S. Liu. A reevaluation and discussion on the threshold limit for hemolysis in a turbulent shear flow. J. Biomech. 34:1361–1364, 2001.

    Article  CAS  PubMed  Google Scholar 

  31. Mann, D. L., D. P. Zipes, P. Libby, and R. O. Bonow. Braunwald’s Heart Disease: A Textbook of Cardiovascular Medicine. Philadelphia: Elsevier, p. 2136, 2014.

    Google Scholar 

  32. Markl, M., P. J. Kilner, and T. Ebbers. Comprehensive 4D velocity mapping of the heart and great vessels by cardiovascular magnetic resonance. J. Cardiovasc. Magn. Reson. 13:7, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Mendez, S., E. Gibaud, and F. Nicoud. An unstructured solver for simulations of deformable particles in flows at arbitrary Reynolds numbers. J. Comput. Phys. 256:465–483, 2014.

    Article  Google Scholar 

  34. Mihalef, V., R. I. Ionasec, P. Sharma, B. Georgescu, I. Voigt, M. Suehling, and D. Comaniciu. Patient-specific modelling of whole heart anatomy, dynamics and haemodynamics from four-dimensional cardiac CT images. Interface Focus 1:286–296, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Nicoud, F., H. B. Toda, O. Cabrit, S. Bose, and J. Lee. Using singular values to build a subgrid-scale model for large eddy simulations. Phys. Fluids 23:1–35, 2011.

    Article  Google Scholar 

  36. Olesen, S. P., D. E. Clapham, and P. F. Davies. Haemodynamic shear stress activates a K+ current in vascular endothelial cells. Nature 331:168–170, 1988.

    Article  CAS  PubMed  Google Scholar 

  37. Pasipoularides, A. Diastolic filling vortex forces and cardiac adaptations: probing the epigenetic nexus. Hell. J. Cardiol. 53:458–469, 2012.

    Google Scholar 

  38. Pasipoularides, A. Mechanotransduction mechanisms for intraventricular diastolic vortex forces and myocardial deformations: part 1. J. Cardiovasc. Transl. Res. 8:76–87, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Pedrizzetti, G., and F. Domenichini. Left ventricular fluid mechanics: the long way from theoretical models to clinical applications. Ann. Biomed. Eng. 43:26–40, 2015.

    Article  PubMed  Google Scholar 

  40. Pedrizzetti, G., F. Domenichini, and G. Tonti. On the left ventricular vortex reversal after mitral valve replacement. Ann. Biomed. Eng. 38:769–773, 2010.

    Article  PubMed  Google Scholar 

  41. Pedrizzetti, G., G. La Canna, O. Alfieri, and G. Tonti. The vortex—an early predictor of cardiovascular outcome? Nat. Rev. Cardiol. 11:545–553, 2014.

    Article  PubMed  Google Scholar 

  42. Pham, D. L., C. Xu, and J. L. Prince. Current methods in medical image segmentation. Annu. Rev. Biomed. Eng. 2:315–337, 2000.

    Article  CAS  PubMed  Google Scholar 

  43. Pope, S. B. Turbulent Flows. Cambridge: Cambridge University Press, 2000. doi:10.1088/0957-0233/12/11/705.

    Book  Google Scholar 

  44. Pope, S. B. Ten questions concerning the large-eddy simulation of turbulent flows. N. J. Phys. 6:35, 2004.

    Article  Google Scholar 

  45. Querzoli, G., S. Fortini, and A. Cenedese. Effect of the prosthetic mitral valve on vortex dynamics and turbulence of the left ventricular flow. Phys. Fluids 22:1–10, 2010.

    Article  Google Scholar 

  46. Sabbah, H. N., and P. D. Stein. Turbulent blood flow in humans: its primary role in the production of ejection murmurs. Circ. Res. 38:513–525, 1976.

    Article  CAS  PubMed  Google Scholar 

  47. Saber, N. R., N. B. Wood, A. D. Gosman, R. D. Merrifield, G. Z. Yang, C. L. Charrier, P. D. Gatehouse, and D. N. Firmin. Progress towards patient-specific computational flow modeling of the left heart via combination of magnetic resonance imaging with computational fluid dynamics. Ann. Biomed. Eng. 31:42–52, 2003.

    Article  PubMed  Google Scholar 

  48. Schenkel, T., M. Malve, M. Reik, M. Markl, B. Jung, and H. Oertel. MRI-Based CFD analysis of flow in a human left ventricle: methodology and application to a healthy heart. Ann. Biomed. Eng. 37:503–515, 2009.

    Article  PubMed  Google Scholar 

  49. Töger, J., M. Kanski, M. Carlsson, S. J. Kovács, G. Söderlind, H. Arheden, and E. Heiberg. Vortex ring formation in the left ventricle of the heart: analysis by 4D Flow MRI and Lagrangian Coherent Structures. Ann. Biomed. Eng. 2012. doi:10.1007/s10439-012-0615-3.

    PubMed  Google Scholar 

  50. Valen-Sendstad, K., and D. A. Steinman. Mind the gap: impact of computational fluid dynamics solution strategy on prediction of intracranial aneurysm hemodynamics and rupture status indicators. Am. J. Neuroradiol. 35:536–543, 2014.

    Article  CAS  PubMed  Google Scholar 

  51. Vedula, V., J.-H. Seo, A. C. Lardo, and R. Mittal. Effect of trabeculae and papillary muscles on the hemodynamics of the left ventricle. Theor. Comput. Fluid Dyn. 2015. doi:10.1007/s00162-015-0349-6.

    Google Scholar 

  52. Watanabe, H., S. Sugiura, and T. Hisada. The looped heart does not save energy by maintaining the momentum of blood flowing in the ventricle. Am. J. Physiol. Heart Circ. Physiol. 294:H2191–H2196, 2008.

    Article  CAS  PubMed  Google Scholar 

  53. Zajac, J., J. Eriksson, P. Dyverfeldt, A. F. Bolger, T. Ebbers, and C.-J. Carlhäll. Turbulent kinetic energy in normal and myopathic left ventricles. J. Magn. Reson. Imaging 41:1021–1029, 2015.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to express their gratitude to MD Dr. D. Coisne for many fruitful discussions. Dr. R. Moreno from the Rangueil University Hospital, Toulouse (France) is acknowledged for the CMR exams. Dr. V. Moureau and Dr. G. Lartigue from the CORIA lab, and the SUCCESS scientific group are acknowledged for providing the YALES2 code, which served as a basis for the development of YALES2BIO. This work was performed using HPC resources from GENCI-CINES (Grants 2014- and 2015-c2014037194).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. Chnafa.

Additional information

Associate Editor Umberto Morbiducci oversaw the review of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (AVI 1562 kb)

Supplementary material 2 (PDF 1223 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chnafa, C., Mendez, S. & Nicoud, F. Image-Based Simulations Show Important Flow Fluctuations in a Normal Left Ventricle: What Could be the Implications?. Ann Biomed Eng 44, 3346–3358 (2016). https://doi.org/10.1007/s10439-016-1614-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-016-1614-6

Keywords

Navigation