Skip to main content

Computational Modeling of Flow-Altering Surgeries in Basilar Aneurysms

Annals of Biomedical Engineering volume 43, pages 1210–1222 (2015)Cite this article

Abstract

In cases where surgeons consider different interventional options for flow alterations in the setting of pathological basilar artery hemodynamics, a virtual model demonstrating the flow fields resulting from each of these options can assist in making clinical decisions. In this study, image-based computational fluid dynamics (CFD) models were used to simulate the flow in four basilar artery aneurysms in order to evaluate postoperative hemodynamics that would result from flow-altering interventions. Patient-specific geometries were constructed using MR angiography and velocimetry data. CFD simulations carried out for the preoperative flow conditions were compared to in vivo phase-contrast MRI measurements (4D Flow MRI) acquired prior to the interventions. The models were then modified according to the procedures considered for each patient. Numerical simulations of the flow and virtual contrast transport were carried out in each case in order to assess postoperative flow fields and estimate the likelihood of intra-aneurysmal thrombus deposition following the procedures. Postoperative imaging data, when available, were used to validate computational predictions. In two cases, where the aneurysms involved vital pontine perforator arteries branching from the basilar artery, idealized geometries of these vessels were incorporated into the CFD models. The effect of interventions on the flow through the perforators was evaluated by simulating the transport of contrast in these vessels. The computational results were in close agreement with the MR imaging data. In some cases, CFD simulations could help determine which of the surgical options was likely to reduce the flow into the aneurysm while preserving the flow through the basilar trunk. The study demonstrated that image-based computational modeling can provide guidance to clinicians by indicating possible outcome complications and indicating expected success potential for ameliorating pathological aneurysmal flow, prior to a procedure.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

References

  1. Bederson, J. B., I. A. Awad, D. O. Wiebers, D. Piepgras, E. C. Haley, Jr., T. Brott, G. Hademenos, D. Chyatte, R. Rosenwasser, and C. Caroselli. Recommendations for the management of patients with unruptured intracranial aneurysms: a statement for healthcare professionals from the stroke council of the american heart association. Stroke 31:2742–2750, 2000.

    Article  CAS  PubMed  Google Scholar 

  2. Bockman, M. D., A. P. Kansagra, S. C. Shadden, E. C. Wong, and A. L. Marsden. Fluid mechanics of mixing in the vertebrobasilar system: comparison of simulation and mri. Cadiovasc. Eng. Technol. 3:450–461, 2012.

    Article  Google Scholar 

  3. Boussel, L., V. Rayz, C. McCulloch, A. Martin, G. Acevedo-Bolton, M. Lawton, R. Higashida, W. S. Smith, W. L. Young, and D. Saloner. Aneurysm growth occurs at region of low wall shear stress: patient-specific correlation of hemodynamics and growth in a longitudinal study. Stroke 39:2997–3002, 2008.

    Article  PubMed Central  PubMed  Google Scholar 

  4. 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.

    CAS  PubMed  Google Scholar 

  5. Cebral, J. R., M. A. Castro, S. Appanaboyina, C. M. Putman, D. Millan, and A. F. Frangi. Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity. IEEE Trans. Med. Imaging. 24:457–467, 2005.

    Article  PubMed  Google Scholar 

  6. Cebral, J. R., S. Hendrickson, and C. M. Putman. Hemodynamics in a lethal basilar artery aneurysm just before its rupture. AJNR Am. J. Neuroradiol. 30:95–98, 2009.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Hademenos, G., and T. Massoud. The Physics of Cerebralvascular Diseases. New York: Springer, 1998.

    Google Scholar 

  8. Hassan, T., M. Ezura, E. V. Timofeev, T. Tominaga, T. Saito, A. Takahashi, K. Takayama, and T. Yoshimoto. Computational simulation of therapeutic parent artery occlusion to treat giant vertebrobasilar aneurysm. Am. J. Neuroradiol. 25:63–68, 2004.

    PubMed  Google Scholar 

  9. Humphrey, J. D., and S. Na. Elastodynamics and arterial wall stress. Ann. Biomed. Eng. 30:509–523, 2002.

    Article  CAS  PubMed  Google Scholar 

  10. Jou, L. D., G. Wong, B. Disensa, 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 

  11. Kodama, N., and J. Suzuki. Surgical treatment of giant aneurysms. Neurosurg. Rev. 5:155–160, 1982.

    Article  CAS  PubMed  Google Scholar 

  12. Lawton, M. T., and R. F. Spetzler. Surgical strategies for giant intracranial aneurysms. Acta Neurochir. Suppl. 72:141–156, 1999.

    CAS  PubMed  Google Scholar 

  13. Lawton, M. T., and R. F. Spetzler. Surgical strategies for giant intracranial aneurysms. Acta Neurochir. Suppl. 72:141–156, 1999.

    CAS  PubMed  Google Scholar 

  14. Ma, B., R. E. Harbaugh, and M. L. Raghavan. Three-dimensional geometrical characterization of cerebral aneurysms. Ann. Biomed. Eng. 32:264–273, 2004.

    Article  PubMed  Google Scholar 

  15. 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.

    CAS  PubMed  Google Scholar 

  16. Metcalfe, R. W. The promise of computational fluid dynamics as a tool for delineating therapeutic options in the treatment of aneurysms. Am. J. Neuroadiol. 24:553–554, 2003.

    Google Scholar 

  17. Peerless, S., M. Wallace, and C. Drake. Giant intracranial aneurysms. In: Neurological Surgery. A Comprehensive Reference Guide to the Diagnosis and Management of Neurological Problems, edited by J. Youmans. Philadelphia: W.B. Saunders, 1990, pp. 1742–1763.

    Google Scholar 

  18. Pia, H. W., and J. Zierski. Giant cerebral aneurysms. Neurosurg. Rev. 5:117–148, 1982.

    Article  CAS  PubMed  Google Scholar 

  19. Raghavan, M. L., B. Ma, and R. E. Harbaugh. Quantified aneurysm shape and rupture risk. J. Neurosurg. 102:355–362, 2005.

    Article  PubMed  Google Scholar 

  20. Rayz, V. L., L. Boussel, G. Acevedo-Bolton, A. J. Martin, W. L. Young, M. T. Lawton, R. Higashida, and D. Saloner. Numerical simulations of flow in cerebral aneurysms: comparison of CFD results and in vivo MRI measurements. J. Biomech. Eng. 130:051011, 2008.

    Article  PubMed  Google Scholar 

  21. Rayz, V. L., L. Boussel, L. Ge, J. R. Leach, A. J. Martin, M. T. Lawton, C. McCulloch, and D. Saloner. Flow residence time and regions of intraluminal thrombus deposition in intracranial aneurysms. Ann. Biomed. Eng. 38:3058–3069, 2010.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  22. Rayz, V. L., L. Boussel, M. T. Lawton, G. Acevedo-Bolton, L. Ge, W. L. Young, R. T. Higashida, and D. Saloner. Numerical modeling of the flow in intracranial aneurysms: prediction of regions prone to thrombus formation. Ann. Biomed. Eng. 36:1793–1804, 2008.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Rinkel, G. J. E., M. Djibuti, A. Algra, and J. van Gijn. Prevalence and risk of rupture of intracranial aneurysms. A systematic review. Stroke. 29:251–256, 1998.

    Article  CAS  PubMed  Google Scholar 

  24. Schievink, W. I. Intracranial aneurysms. N. Engl. J. Med. 336:28–40, 1997.

    Article  CAS  PubMed  Google Scholar 

  25. 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. Neuroadiol. 24:559–566, 2003.

    Google Scholar 

  26. Sughrue, M. E., D. Saloner, V. L. Rayz, and M. T. Lawton. Giant intracranial aneurysms: evolution of management in a contemporary surgical series. Neurosurgery 69(6):1261–1271, 2011.

    Article  PubMed Central  PubMed  Google Scholar 

  27. Taylor, C. A., M. T. Draney, J. P. Ku, D. Parker, B. N. Steele, K. Wang, and C. K. Zarins. Predictive medicine: computational techniques in therapeutic decision-making. Comput. Aided Surg. 4:231–247, 1999.

    Article  CAS  PubMed  Google Scholar 

  28. Utter, B., and J. S. Rossmann. Numerical simulation of saccular aneurysm hemodynamics: influence of morphology on rupture risk. J. Biomech. 40:2716–2722, 2007.

    Article  PubMed  Google Scholar 

  29. Valencia, A., A. Zarate, M. Galvez, and L. Badilla. Non-newtonian blood flow dynamics in a right internal carotid artery with a saccular aneurysm. Int. J. Numer. Method Fluids 50:751–764, 2006.

    Article  Google Scholar 

  30. Wardlaw, J., and P. White. The detection and management of unruptured intracranial aneurysms. Brain 123:205–221, 2000.

    Article  PubMed  Google Scholar 

  31. Zeng, Z., M. J. Durka, D. F. Kallmes, Y. Ding, and A. M. Robertson. Can aspect ratio be used to categorize intra-aneurysmal hemodynamics?—A study of elastase induced aneurysms in rabbit. J. Biomech. 44:2809–2816, 2011.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

We acknowledge Grant support from the NIHHL115267 (VLR).

Author information

Affiliations

  1. Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA

    V. L. Rayz, J. R. Leach, G. Acevedo-Bolton & D. Saloner

  2. Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA

    A. Abla & M. T. Lawton

  3. Department of Radiology, Louis Pradel Hospital, Créatis-LRMN, Lyon, France

    L. Boussel

Authors
  1. V. L. Rayz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Abla
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. L. Boussel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. R. Leach
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. G. Acevedo-Bolton
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. D. Saloner
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. T. Lawton
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. L. Rayz.

Additional information

Associate Editor Kent Leach oversaw the review of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (WMV 1403 kb)

Supplementary material 2 (WMV 872 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rayz, V.L., Abla, A., Boussel, L. et al. Computational Modeling of Flow-Altering Surgeries in Basilar Aneurysms. Ann Biomed Eng 43, 1210–1222 (2015). https://doi.org/10.1007/s10439-014-1170-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-014-1170-x

Keywords

  • Image-based computational modeling
  • Computational fluid dynamics
  • Basilar artery aneurysm
  • Magnetic resonance imaging
  • Indirect aneurysm occlusion