Skip to main content
Log in

Impact of aneurysmal geometry on intraaneurysmal flow: a computerized flow simulation study

  • Interventional Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Introduction

This study was performed to assess the effect of aneurysm geometry on parameters that may have an impact on the natural history of intracranial aneurysms, such as intraaneurysmal flow pressure and shear stress.

Methods

Flow was simulated in 21 randomly selected aneurysms using finite volume modeling. Ten aneurysms were classified as side-wall aneurysms, with either single-sided or circumferential involvement of the parent artery wall, and 11 as bifurcation aneurysms (symmetric or asymmetric), with an axis either perpendicular or parallel to the parent artery. The flow patterns were classified as either jet or vortex types (with regular or irregular vortex flow). Pressures and shear stresses were characterized as evenly or unevenly distributed over the aneurysm wall and neck.

Results

All side-wall and four of the bifurcation aneurysms with a perpendicular axis had a vortex type flow pattern and seven bifurcation aneurysms with a parallel axis (four symmetric and two asymmetric) had a jet flow pattern. Jet type flow was associated with an uneven pressure distribution in seven out of seven aneurysms. Vortex type flow resulted in an even pressure distribution in five out of six aneurysms with an irregular flow pattern and six out of eight with a regular flow pattern. No firm relationship could be established between any geometrical type and shear stress distribution. Only 1 of 14 aneurysms with a perpendicular axis, but 4 of 7 aneurysms with a parallel axis, had ruptured.

Conclusion

Aneurysm geometry does have an impact on flow conditions. Aneurysms with a main axis parallel to the parent artery have a tendency to have a jet flow pattern and uneven distribution of unsteady pressure. These aneurysms may have a higher rate of rupture as than those with a main axis perpendicular to the parent artery.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. ISUIA Investigators (1998) Unruptured intracranial aneurysms – risk of rupture and risks of surgical intervention. International Study of Unruptured Intracranial Aneurysms Investigators. N Engl J Med 339(24):1725–1733

    Google Scholar 

  2. ISUIA Investigators (2003) Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment. Lancet 362:103–110

    Google Scholar 

  3. Graves VB et al (1992) Flow dynamics of lateral carotid artery aneurysms and their effects on coils and balloons: an experimental study in dogs. AJNR Am J Neuroradiol 13(1):189–196

    PubMed  CAS  Google Scholar 

  4. Kerber CW et al (1996) Flow dynamics in a fatal aneurysm of the basilar artery. AJNR Am J Neuroradiol 17(8):1417–1421

    PubMed  CAS  Google Scholar 

  5. Strother CM (1995) In vitro study of haemodynamics in a giant saccular aneurysm model: influence of flow dynamics in the parent vessel and effects of coil embolisation. Neuroradiology 37(2):159–161

    Article  PubMed  CAS  Google Scholar 

  6. Tateshima S et al (2001) Intraaneurysmal flow dynamics study featuring an acrylic aneurysm model manufactured using a computerized tomography angiogram as a mold. J Neurosurg 95(6):1020–1027

    PubMed  CAS  Google Scholar 

  7. Valencia A (2004) Flow dynamics in models of intracranial terminal aneurysms. Mech Chem Biosyst 1(3):221–231

    PubMed  Google Scholar 

  8. Valencia AA et al (2006) Blood flow dynamics in saccular aneurysm models of the basilar artery. J Biomech Eng 128(4):516–526

    Article  PubMed  Google Scholar 

  9. Foutrakis GN, Yonas H, Sclabassi RJ (1997) Finite element methods in the simulation and analysis of intracranial blood flow. Neurol Res 19(2):174–186

    PubMed  CAS  Google Scholar 

  10. Chong BW et al (1994) Blood flow dynamics in the vertebrobasilar system: correlation of a transparent elastic model and MR angiography. AJNR Am J Neuroradiol 15(4):733–745

    PubMed  CAS  Google Scholar 

  11. Jou LD et al (2003) Computational approach to quantifying hemodynamic forces in giant cerebral aneurysms. AJNR Am J Neuroradiol 24(9):1804–1810

    PubMed  Google Scholar 

  12. Castro MA, Putman CM, Cebral JR (2006) Computational fluid dynamics modeling of intracranial aneurysms: effects of parent artery segmentation on intra-aneurysmal hemodynamics. AJNR Am J Neuroradiol 27(8):1703–1709

    PubMed  CAS  Google Scholar 

  13. Cebral JR, Lohner R (2005) Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique. IEEE Trans Med Imaging 24(4):468–476

    Article  PubMed  Google Scholar 

  14. Burleson AC, Strother CM, Turitto VT (1995) Computer modeling of intracranial saccular and lateral aneurysms for the study of their hemodynamics. Neurosurgery 37(4):774–782, discussion 782–784

    Article  PubMed  CAS  Google Scholar 

  15. San Millán Ruiz D et al (2006) The perianeurysmal environment: influence on saccular aneurysm shape and rupture. AJNR Am J Neuroradiol 27:504–512

    PubMed  Google Scholar 

  16. Satoh T et al (2005) Influence of perianeurysmal environment on the deformation and bleb formation of the unruptured cerebral aneurysm: assessment with fusion imaging of 3D MR cisternography and 3D MR angiography. AJNR Am J Neuroradiol 26(8):2010–2018

    PubMed  Google Scholar 

  17. Satoh T et al (2005) Visualization of aneurysmal contours and perianeurysmal environment with conventional and transparent 3D MR cisternography. AJNR Am J Neuroradiol 26(2):313–318

    PubMed  Google Scholar 

  18. Hassan T et al (2005) A proposed parent vessel geometry-based categorization of saccular intracranial aneurysms: computational flow dynamics analysis of the risk factors for lesion rupture. J Neurosurg 103(4):662–680

    Article  PubMed  Google Scholar 

  19. Ujiie H et al (1999) Effects of size and shape (aspect ratio) on the hemodynamics of saccular aneurysms: a possible index for surgical treatment of intracranial aneurysms. Neurosurgery 45(1):119–129, discussion 129–130

    Article  PubMed  CAS  Google Scholar 

  20. Paal G et al (2007) Flow in simplified and real models of intracranial aneurysms. Int J Heat Fluid Flow 28:653–664

    Article  Google Scholar 

  21. Cebral JR et al (2005) Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. AJNR Am J Neuroradiol 26(10):2550–2559

    PubMed  Google Scholar 

  22. Cebral J (2007) Personalized computational modeling of stented cerebral aneurysms. Paper presented at the 4th International Intracranial Stent Meeting, Kyoto, Japan, 18–20 April 2007

  23. Cebral JR et al (2005) Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity. IEEE Trans Med Imaging 24(4):457–467

    Article  PubMed  Google Scholar 

  24. Foutrakis GN, Yonas H, Sclabassi RJ (1999) Saccular aneurysm formation in curved and bifurcating arteries. AJNR Am J Neuroradiol 20(7):1309–1317

    PubMed  CAS  Google Scholar 

  25. Kerber CW, Heilman CB (1983) Flow in experimental berry aneurysms: method and model. AJNR Am J Neuroradiol 4(3):374–377

    PubMed  CAS  Google Scholar 

  26. Shojima M et al (2005) Role of the bloodstream impacting force and the local pressure elevation in the rupture of cerebral aneurysms. Stroke 36(9):1933–1938

    Article  PubMed  Google Scholar 

  27. Jou LD et al (2005) Correlation between lumenal geometry changes and hemodynamics in fusiform intracranial aneurysms. AJNR Am J Neuroradiol 26(9):2357–2363

    PubMed  Google Scholar 

  28. Hassan T et al (2004) Computational replicas: anatomic reconstructions of cerebral vessels as volume numerical grids at three-dimensional angiography. AJNR Am J Neuroradiol 25(8):1356–1365

    PubMed  Google Scholar 

  29. Shojima M et al (2004) Magnitude and role of wall shear stress on cerebral aneurysm: computational fluid dynamic study of 20 middle cerebral artery aneurysms. Stroke 35(11):2500–2505

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported in part by a grant from the Hungarian National Science and Research Foundation (no. T 047150 OPR) and by research support from GE Amersham Healthcare Hungary.

Conflict of interest statement

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Istvan Szikora.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Szikora, I., Paal, G., Ugron, A. et al. Impact of aneurysmal geometry on intraaneurysmal flow: a computerized flow simulation study. Neuroradiology 50, 411–421 (2008). https://doi.org/10.1007/s00234-007-0350-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00234-007-0350-x

Keywords

Navigation