Acta Neurochirurgica

, Volume 152, Issue 8, pp 1391–1398

Temporal variations of wall shear stress parameters in intracranial aneurysms—importance of patient-specific inflow waveforms for CFD calculations

  • Christof Karmonik
  • Christopher Yen
  • Orlando Diaz
  • Richard Klucznik
  • Robert G. Grossman
  • Goetz Benndorf
Experimental Research



To assess reliability of wall shear stress (WSS) calculations using computational fluid dynamics (CFD) dependent on inflow in internal carotid artery aneurysms (ICA).

Materials and methods

Six unruptured ICA aneurysms were studied. 3D computational meshes were created from 3D digital subtraction angiographic images (Axiom Artis dBA, Siemens Medical Solutions). Transient CFD simulations (Fluent, ANSYS Inc.) were performed for two inflow conditions: (1) idealized averaged waveform from normal subjects (ID) and (2) patient-specific waveform (PS) measured with 2D phase contrast magnetic resonance imaging. Stability of calculation was assessed by comparing mean WSS (<WSS>), temporal wall shear stress magnitude variation (ΔWSS), and oscillatory shear index (OSI, a measure of variation in the WSS direction) on the aneurysmal wall for both conditions.


For all cases, mean relative difference (PS−ID) of WSS (<WSS>) was −15% (range −32% to 11%). Mean ΔWSS difference was −29.3% ( −100% to 67%). Mean OSI difference was 7.5% (−12% to 40%). Large variations in histograms of these parameters were noted.


For accurate calculations of WSS parameters, patient-specific information on physiological flow may be necessary. Results obtained with averaged or idealized flow waveforms may have to be interpreted with caution.


Cerebral aneurysms Computational fluid dynamics Magnetic resonance angiography Digital subtraction angiography 


  1. 1.
    Acevedo-Bolton G, Jou LD, Dispensa BP, Lawton MT, Higashida RT, Martin AJ, Young WL, Saloner D (2006) Estimating the hemodynamic impact of interventional treatments of aneurysms: numerical simulation with experimental validation: technical case report. Neurosurgery 59:E429–E430, author reply E429–430PubMedCrossRefGoogle Scholar
  2. 2.
    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 27:1703–1709PubMedGoogle Scholar
  3. 3.
    Castro MA, Putman CM, Cebral JR (2006) 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. AJNR Am J Neuroradiol 27:2061–2068PubMedGoogle Scholar
  4. 4.
    Castro MA, Putman CM, Cebral JR (2006) Patient-specific computational modeling of cerebral aneurysms with multiple avenues of flow from 3D rotational angiography images. Acad Radiol 13:811–821PubMedCrossRefGoogle Scholar
  5. 5.
    Cebral JR, Castro MA, Burgess JE, Pergolizzi RS, Sheridan MJ, Putman CM (2005) Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. AJNR Am J Neuroradiol 26:2550–2559PubMedGoogle Scholar
  6. 6.
    Cebral JR, Lohner R (2005) Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique. IEEE Trans Med Imaging 24:468–476PubMedCrossRefGoogle Scholar
  7. 7.
    Cebral JR, Pergolizzi RS Jr, Putman CM (2007) Computational fluid dynamics modeling of intracranial aneurysms: qualitative comparison with cerebral angiography. Acad Radiol 14:804–813PubMedCrossRefGoogle Scholar
  8. 8.
    Dempere-Marco L, Oubel E, Castro M, Putman C, Frangi A, Cebral J (2006) CFD analysis incorporating the influence of wall motion: application to intracranial aneurysms. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv 9:438–445Google Scholar
  9. 9.
    Ford MD, Alperin N, Lee SH, Holdsworth DW, Steinman DA (2005) Characterization of volumetric flow rate waveforms in the normal internal carotid and vertebral arteries. Physiol Meas 26:477–488PubMedCrossRefGoogle Scholar
  10. 10.
    Ford MD, Lee SW, Lownie SP, Holdsworth DW, Steinman DA (2008) 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 41:241–248PubMedCrossRefGoogle Scholar
  11. 11.
    Ford MD, Nikolov HN, Milner JS, Lownie SP, Demont EM, Kalata W, Loth F, Holdsworth DW, Steinman DA (2008) PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models. J Biomech Eng 130:021015PubMedCrossRefGoogle Scholar
  12. 12.
    Ford MD, Stuhne GR, Nikolov HN, Habets DF, Lownie SP, Holdsworth DW, Steinman DA (2005) Virtual angiography for visualization and validation of computational models of aneurysm hemodynamics. IEEE Trans Med Imaging 24:1586–1592PubMedCrossRefGoogle Scholar
  13. 13.
    Funamoto K, Hayase T, Saijo Y, Yambe T (2008) Numerical experiment for ultrasonic-measurement-integrated simulation of three-dimensional unsteady blood flow. Ann Biomed EngGoogle Scholar
  14. 14.
    He XJ, Ku DN (1996) Pulsatile flow in the human left coronary artery bifurcation: average conditions. Journal of Biomechanical Engineering-Transactions of the Asme 118:74–82CrossRefGoogle Scholar
  15. 15.
    Hecht N, Woitzik J, Dreier JP, Vajkoczy P (2009) Intraoperative monitoring of cerebral blood flow by laser speckle contrast analysis. Neurosurg Focus 27:E11PubMedCrossRefGoogle Scholar
  16. 16.
    Hoi Y, Woodward SH, Kim M, Taulbee DB, Meng H (2006) Validation of CFD simulations of cerebral aneurysms with implication of geometric variations. J Biomech Eng 128:844–851PubMedCrossRefGoogle Scholar
  17. 17.
    Imai Y, Sato K, Ishikawa T, Yamaguchi T (2008) Inflow into saccular cerebral aneurysms at arterial bends. Ann Biomed Eng 36(9):1489–1495PubMedCrossRefGoogle Scholar
  18. 18.
    Jou LD, Lee DH, Morsi H, Mawad ME (2008) Wall shear stress on ruptured and unruptured intracranial aneurysms at the internal carotid artery. AJNR Am J Neuroradiol 29:1761–1767PubMedCrossRefGoogle Scholar
  19. 19.
    Jou LD, Mawad ME (2009) Growth rate and rupture rate of unruptured intracranial aneurysms: a population approach. Biomed Eng Online 8:11PubMedCrossRefGoogle Scholar
  20. 20.
    Jou LD, Wong G, Dispensa B, Lawton MT, Higashida RT, Young WL, Saloner D (2005) Correlation between lumenal geometry changes and hemodynamics in fusiform intracranial aneurysms. AJNR Am J Neuroradiol 26:2357–2363PubMedGoogle Scholar
  21. 21.
    Karmonik C, Benndorf G, Klucznik R, Haykal H, Strother CM (2006) Wall shear stress variations in basilar tip aneurysms investigated with computational fluid dynamics. Conf Proc IEEE Eng Med Biol Soc 1:3214–3217PubMedGoogle Scholar
  22. 22.
    Karmonik C, Klucznik R, Benndorf G (2008) Blood flow in cerebral aneurysms: comparison of phase contrast magnetic resonance and computational fluid dynamics—preliminary experience. Rofo 180:209–215PubMedGoogle Scholar
  23. 23.
    Karmonik C, Klucznik R, Benndorf G (2008) Comparison of velocity patterns in an AComA aneurysm measured with 2D phase contrast MRI and simulated with CFD. Technol Health Care 16:119–128PubMedGoogle Scholar
  24. 24.
    Karmonik C, Yen C, Grossman RG, Klucznik R, Benndorf G (2009) Intra-aneurysmal flow patterns and wall shear stresses calculated with computational flow dynamics in an anterior communicating artery aneurysm depend on knowledge of patient-specific inflow rates. Acta Neurochir (Wien) 151(5):479–485CrossRefGoogle Scholar
  25. 25.
    Kim M, Taulbee DB, Tremmel M, Meng H (2008) Comparison of two stents in modifying cerebral aneurysm hemodynamics. Ann Biomed Eng 36:726–741PubMedCrossRefGoogle Scholar
  26. 26.
    Liou TM, Li YC, Juan WC (2007) Numerical and experimental studies on pulsatile flow in aneurysms arising laterally from a curved parent vessel at various angles. J Biomech 40:1268–1275PubMedCrossRefGoogle Scholar
  27. 27.
    Malek AM, Izumo S (1995) Control of endothelial cell gene expression by flow. J Biomech 28:1515–1528PubMedCrossRefGoogle Scholar
  28. 28.
    Mantha A, Karmonik C, Benndorf G, Strother C, Metcalfe R (2006) Hemodynamics in a cerebral artery before and after the formation of an aneurysm. AJNR Am J Neuroradiol 27:1113–1118PubMedGoogle Scholar
  29. 29.
    Meng H, Wang Z, Kim M, Ecker RD, Hopkins LN (2006) Saccular aneurysms on straight and curved vessels are subject to different hemodynamics: implications of intravascular stenting. AJNR Am J Neuroradiol 27:1861–1865PubMedGoogle Scholar
  30. 30.
    Mitsos AP, Kakalis NM, Ventikos YP, Byrne JV (2008) Haemodynamic simulation of aneurysm coiling in an anatomically accurate computational fluid dynamics model: technical note. Neuroradiology 50:341–347PubMedCrossRefGoogle Scholar
  31. 31.
    Ortega J, Hartman J, Rodriguez J, Maitland D (2008) Post-treatment hemodynamics of a basilar aneurysm and bifurcation. Ann Biomed Eng 36(9):1531–1546PubMedCrossRefGoogle Scholar
  32. 32.
    Radaelli AG, Augsburger L, Cebral JR, Ohta M, Rufenacht DA, Balossino R, Benndorf G, Hose DR, Marzo A, Metcalfe R, Mortier P, Mut F, Reymond P, Socci L, Verhegghe B, Frangi AF (2008) Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model—a report on the Virtual Intracranial Stenting Challenge 2007. J Biomech 41:2069–2081PubMedCrossRefGoogle Scholar
  33. 33.
    Sato K, Imai Y, Ishikawa T, Matsuki N, Yamaguchi T (2008) The importance of parent artery geometry in intra-aneurysmal hemodynamics. Med Eng Phys 30:774–782PubMedCrossRefGoogle Scholar
  34. 34.
    Sforza DM, Putman CM, Cebral JR (2009) Hemodynamics of cerebral aneurysms. Annu Rev Fluid Mech 41:91–107PubMedCrossRefGoogle Scholar
  35. 35.
    Shimogonya Y, Ishikawa T, Imai Y, Matsuki N, Yamaguchi T (2009) Can temporal fluctuation in spatial wall shear stress gradient initiate a cerebral aneurysm? A proposed novel hemodynamic index, the gradient oscillatory number (GON). J Biomech 42:550–554PubMedCrossRefGoogle Scholar
  36. 36.
    Valencia A, Morales H, Rivera R, Bravo E, Galvez M (2007) Blood flow dynamics in patient-specific cerebral aneurysm models: the relationship between wall shear stress and aneurysm area index. Med Eng Phys 30(3):329–340PubMedCrossRefGoogle Scholar
  37. 37.
    Venugopal P, Valentino D, Schmitt H, Villablanca JP, Vinuela F, Duckwiler G (2007) Sensitivity of patient-specific numerical simulation of cerebal aneurysm hemodynamics to inflow boundary conditions. J Neurosurg 106:1051–1060PubMedCrossRefGoogle Scholar
  38. 38.
    Zhao M, Amin-Hanjani S, Ruland S, Curcio AP, Ostergren L, Charbel FT (2007) Regional cerebral blood flow using quantitative MR angiography. AJNR Am J Neuroradiol 28:1470–1473PubMedCrossRefGoogle Scholar
  39. 39.
    Zhao M, Charbel FT, Alperin N, Loth F, Clark ME (2000) Improved phase-contrast flow quantification by three-dimensional vessel localization. Magn Reson Imaging 18:697–706PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Christof Karmonik
    • 1
    • 2
  • Christopher Yen
    • 1
  • Orlando Diaz
    • 3
  • Richard Klucznik
    • 3
  • Robert G. Grossman
    • 1
  • Goetz Benndorf
    • 4
  1. 1.Department of NeurosurgeryThe Methodist Hospital Neurological InstituteHoustonUSA
  2. 2.Weil Medical College of Cornell UniversityNew YorkUSA
  3. 3.Department of RadiologyThe Methodist Hospital Neurological InstituteHoustonUSA
  4. 4.Department of RadiologyBaylor College of MedicineHoustonUSA

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