Computational Modeling of Flow-Altering Surgeries in Basilar Aneurysms


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.

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  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 7.

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

  8. 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.

  9. 9.

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

  10. 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.

  11. 11.

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

  12. 12.

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

  13. 13.

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

  14. 14.

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

  15. 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.

  16. 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.

  17. 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.

  18. 18.

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

  19. 19.

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

  20. 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.

  21. 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.

  22. 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.

  23. 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.

  24. 24.

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

  25. 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.

  26. 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.

  27. 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.

  28. 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.

  29. 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.

  30. 30.

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

  31. 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.

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We acknowledge Grant support from the NIHHL115267 (VLR).

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Correspondence to V. L. Rayz.

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Associate Editor Kent Leach oversaw the review of this article.

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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).

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