Skip to main content

Advertisement

SpringerLink
Log in

Numerical Validation of MR-Measurement-Integrated Simulation of Blood Flow in a Cerebral Aneurysm

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

Abstract

This study proposes magnetic resonance (MR)-measurement-integrated (MR-MI) simulation, in which the difference between the computed velocity field and the phase-contrast MRI measurement data is fed back to the numerical simulation. The computational accuracy and the fundamental characteristics, such as steady characteristics and transient characteristics, of the MR-MI simulation were investigated by a numerical experiment. We dealt with reproduction of three-dimensional steady and unsteady blood flow fields in a realistic cerebral aneurysm developed at a bifurcation. The MR-MI simulation reduced the error derived from the incorrect boundary conditions in the blood flow in the cerebral aneurysm. For the reproduction of steady and unsteady standard solutions, the error of velocity decreased to 13% and to 22% in one cardiac cycle, respectively, compared with the ordinary simulation without feedback. Moreover, the application of feedback shortened the computational convergence, and thus the convergent solution and periodic solution were obtained within less computational time in the MR-MI simulation than that in the ordinary simulation. The dividing flow ratio toward the two outlets after bifurcation was well estimated owing to the improvement of computational accuracy. Furthermore, the MR-MI simulation yielded wall shear stress distribution on the cerebral aneurysm of the standard solution accurately and in detail.

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

FIGURE 1
FIGURE 2
FIGURE 3
FIGURE 4
FIGURE 5
FIGURE 6
FIGURE 7
FIGURE 8
FIGURE 9
FIGURE 10
FIGURE 11
FIGURE 12

Similar content being viewed by others

References

  1. Castro, M. A., C. M. Putman, and J. R. Cebral. Computational fluid dynamics modeling of intracranial aneurysms: Effects of parent artery segmentation on intra-aneurysmal hemodynamics. Am J Neuroradiol 27:1703-1709, 2006.

    PubMed  CAS  Google Scholar 

  2. Castro, M. A., C. M. Putman, and J. R. Cebral. Patient-specific computational fluid dynamics modeling of anterior communicating artery aneurysms: A study of the sensitivity of intra-aneurysmal flow patterns to flow conditions in the carotid arteries. Am J Neuroradiol 27:2061-2068, 2006.

    PubMed  CAS  Google Scholar 

  3. Cebral, J. R., M. A. Castro, J. E. Burgess, R. S. Pergolizzi, M. J. Sheridan, and C. M. Putman. Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. Am J Neuroradiol 26:2550-2559, 2005.

    PubMed  Google Scholar 

  4. Ford, M. D., S. W. Lee, S. P. Lownie, D. W. Holdsworth, and D. A. Steinman. On the effect of parent-aneurysm angle on flow patterns in basilar tip aneurysms: Towards a surrogate geometric marker of intra-aneurismal hemodynamics. J Biomech 41:241-248, 2008. doi:10.1016/j.jbiomech.2007.09.032

    Article  PubMed  Google Scholar 

  5. Funamoto, K., T. Hayase, Y. Saijo, and T. Yambe. Transient and steady characteristics of ultrasonic-measurement-integrated simulation in three-dimensional blood flow analysis. Ann Biomed Eng 37:34-49, 2009. doi:10.1007/s10439-008-9600-2

    Article  PubMed  Google Scholar 

  6. Glor, F. P., J. J. M. Westenberg, J. Vierendeels, M. Danilouchkine, and P. Verdonck. Validation of the coupling of magnetic resonance imaging velocity measurements with computational fluid dynamics in a u bend. Artif Organs 26:622-635, 2002. doi:10.1046/j.1525-1594.2002.07085.x

    Article  PubMed  CAS  Google Scholar 

  7. Hassan, T., E. V. Timofeev, T. Saito, H. Shimizu, M. Ezura, T. Tominaga, A. Takahashi, and K. Takayama. Computational replicas: Anatomic reconstructions of cerebral vessels as volume numerical grids at three-dimensional angiography. Am J Neuroradiol 25:1356-1365, 2004.

    PubMed  Google Scholar 

  8. Hayase, T., and S. Hayashi. State estimator of flow as an integrated computational method with the feedback of online experimental measurement. J Fluid Eng-T Asme 119:814-822, 1997. doi:10.1115/1.2819503

    Article  CAS  Google Scholar 

  9. Hayase, T., J. A. C. Humphrey, and R. Greif. A consistently formulated quick scheme for fast and stable convergence using finite-volume iterative calculation procedures. J Comput Phys 98:108-118, 1992. doi:10.1016/0021-9991(92)90177-Z

    Article  Google Scholar 

  10. Isoda, H., M. Hirano, H. Takeda, T. Kosugi, M. T. Alley, M. Markl, N. J. Pelc, and H. Sakahara. Visualization of hemodynamics in a silicon aneurysm model using time-resolved, 3D, phase-contrast MRI. Am J Neuroradiol 27:1119-1122, 2006.

    PubMed  CAS  Google Scholar 

  11. Jamous, M. A., S. Nagahiro, K. T. Kitazato, K. Satoh, and J. Satomi. Vascular corrosion casts mirroring early morphological changes that lead to the formation of saccular cerebral aneurysm: An experimental study in rats. J Neurosurg 102:532-535, 2005.

    Article  PubMed  Google Scholar 

  12. Jou, L. D., G. Wong, B. Dispensa, M. T. Lawton, R. T. Higashida, W. L. Young, and D. Saloner. Correlation between lumenal geometry changes and hemodynamics in fusiform intracranial aneurysms. Am J Neuroradiol 26:2357-2363, 2005.

    PubMed  Google Scholar 

  13. Malek, A. M., S. L. Alper, and S. Izumo. Hemodynamic shear stress and its role in atherosclerosis. Jama-J Am Med Assoc 282:2035-2042, 1999. doi:10.1001/jama.282.21.2035

    Article  PubMed  CAS  Google Scholar 

  14. Mantha, A., C. Karmonik, G. Benndorf, C. Strother, and R. Metcalfe. Hemodynamics in a cerebral artery before and after the formation of an aneurysm. Am J Neuroradiol 27:1113-1118, 2006.

    PubMed  CAS  Google Scholar 

  15. Markl, M., F. P. Chan, M. T. Alley, K. L. Wedding, M. T. Draney, C. J. Elkins, D. W. Parker, R. Wicker, C. A. Taylor, R. J. Herfkens, and N. J. Pelc. Time-resolved three-dimensional phase-contrast MRI. J Magn Reson Imaging 17:499-506, 2003. doi:10.1002/jmri.10272

    Article  PubMed  Google Scholar 

  16. Marshall, I., S. Z. Zhao, P. Papathanasopoulou, P. Hoskins, and X. Y. Xu. MRI and CFD studies of pulsatile flow in healthy and stenosed carotid bifurcation models. J Biomech 37:679-687, 2004. doi:10.1016/j.jbiomech.2003.09.032

    Article  PubMed  Google Scholar 

  17. Meng, H., Z. J. Wang, Y. Hoi, L. Gao, E. Metaxa, D. D. Swartz, and J. Kolega. Complex hemodynamics at the apex of an arterial bifurcation induces vascular remodeling resembling cerebral aneurysm initiation. Stroke 38:1924-1931, 2007. doi:10.1161/STROKEAHA.106.481234

    Article  PubMed  Google Scholar 

  18. Moftakhar, R., B. Aagaard-Kienitz, K. Johnson, P. A. Turski, A. S. Turk, D. B. Niemann, D. Consigny, J. Grinde, O. Wieben, and C. A. Mistretta. Noninvasive measurement of intra-aneurysmal pressure and flow pattern using phase contrast with vastly undersampled isotropic projection imaging. Am J Neuroradiol 28:1710-1714, 2007. doi:10.3174/ajnr.A0648

    Article  PubMed  CAS  Google Scholar 

  19. Moyle, K. R., L. Antiga, and D. A. Steinman. Inlet conditions for image-based CFD models of the carotid bifurcation: Is it reasonable to assume fully developed flow? J Biomech Eng-T Asme 128:371-379, 2006. doi:10.1115/1.2187035

    Article  PubMed  Google Scholar 

  20. Myers, J. G., J. A. Moore, M. Ojha, K. W. Johnston, and C. R. Ethier. Factors influencing blood flow patterns in the human right coronary artery. Ann Biomed Eng 29:109-120, 2001. doi:10.1114/1.1349703

    Article  PubMed  CAS  Google Scholar 

  21. Papathanasopoulou, P., S. Z. Zhao, U. Kohler, M. B. Robertson, Q. Long, P. Hoskins, X. Y. Xu, and I. Marshall. MRI measurement of time-resolved wall shear stress vectors in a carotid bifurcation model, and comparison with CFD predictions. J Magn Reson Imaging 17:153-162, 2003. doi:10.1002/jmri.10243

    Article  PubMed  Google Scholar 

  22. Patankar, S. V. Numerical Heat Transfer and Fluid Flow. Washington DC/New York: Hemisphere Pub. Corp., 1980.

  23. Radaelli, A. G., L. Augsburger, J. R. Cebral, M. Ohta, D. A. Rüfenacht, R. Balossino, G. Benndorf, D. R. Hose, A. Marzo, R. Metcalfe, P. Mortier, F. Mut, P. Reymond, L. Socci, B. Verhegghe, and A. F. Frangi. Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model—a report on the virtual intracranial stenting challenge 2007. J Biomech 41:2069-2081, 2008. doi:10.1016/j.jbiomech.2008.04.035

    Article  PubMed  CAS  Google Scholar 

  24. Shojima, M., M. Oshima, K. Takagi, R. Torii, M. Hayakawa, K. Katada, A. Morita, and T. Kirino. Magnitude and role of wall shear stress on cerebral aneurysm - computational fluid dynamic study of 20 middle cerebral artery aneurysms. Stroke 35:2500-2505, 2004. doi:10.1161/01.STR.0000144648.89172.0f

    Article  PubMed  Google Scholar 

  25. Steinman, D. A., and C. A. Taylor. Flow imaging and computing: Large artery hemodynamics. Ann Biomed Eng 33:1704-1709, 2005. doi:10.1007/s10439-005-8772-2

    Article  PubMed  Google Scholar 

  26. Steinman, D. A., J. S. Milner, C. J. Norley, S. P. Lownie, and D. W. Holdsworth. Image-based computational simulation of flow dynamics in a giant intracranial aneurysm. Am J Neuroradiol 24:559-566, 2003.

    PubMed  Google Scholar 

  27. Tateshima, S., Y. Murayama, J. P. Villablanca, T. Morino, K. Nomura, K. Tanishita, and F. Vinuela. In vitro measurement of fluid-induced wall shear stress in unruptured cerebral aneurysms harboring blebs. Stroke 34:187-192, 2003. doi:10.1161/01.STR.0000046456.26587.8B

    Article  PubMed  Google Scholar 

  28. Ujiie, H., Y. Tamano, K. Sasaki, and T. Hori. Is the aspect ratio a reliable index for predicting the rupture of a saccular aneurysm? Neurosurgery 48:495-502, 2001. doi:10.1097/00006123-200103000-00007

    Article  PubMed  CAS  Google Scholar 

  29. Venugopal, P., D. Valentino, H. Schmitt, J. P. Villablanca, F. Vinuela, and G. Duckwiler. Sensitivity of patient-specific numerical simulation of cerebral aneurysm hemodynamics to inflow boundary conditions. J Neurosurg 106:1051-1060, 2007. doi:10.3171/jns.2007.106.6.1051

    Article  PubMed  Google Scholar 

  30. Zhao, S. Z., P. Papathanasopoulou, Q. Long, I. Marshall, and X. Y. Xu. Comparative study of magnetic resonance imaging and image-based computational fluid dynamics for quantification of pulsatile flow in a carotid bifurcation phantom. Ann Biomed Eng 31:962-971, 2003. doi:10.1114/1.1590664

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

The authors would like to express their thanks to Mr. Yasuhide Ohkura for his cooperation in obtaining the output of the information on blood flow from the PC MRI using Flova. All computations were performed using the supercomputer system at the Advanced Fluid Information Research Center, Institute of Fluid Science, Tohoku University. The authors are grateful to the staff of the AFI Research Center for their support in the computational work.

Author information

Authors and Affiliations

  1. Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan

    Kenichi Funamoto & Toshiyuki Hayase

  2. Graduate School of Engineering, Tohoku University, 6-6-01 Aoba, Aramaki, Aoba-ku, Sendai, 980-8579, Japan

    Yoshitsugu Suzuki

  3. Renaissance of Technology Corp., 1-4-10 Shinmiyakoda, Kita-ku, Hamamatsu, 431-2103, Japan

    Takashi Kosugi

  4. Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu, 431-3192, Japan

    Haruo Isoda

Authors
  1. Kenichi Funamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yoshitsugu Suzuki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Toshiyuki Hayase
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Takashi Kosugi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haruo Isoda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kenichi Funamoto.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Funamoto, K., Suzuki, Y., Hayase, T. et al. Numerical Validation of MR-Measurement-Integrated Simulation of Blood Flow in a Cerebral Aneurysm. Ann Biomed Eng 37, 1105–1116 (2009). https://doi.org/10.1007/s10439-009-9689-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-009-9689-y

Keywords

Search

Navigation