CFD and PIV analysis of hemodynamics in a growing intracranial aneurysm

Hemodynamics is thought to be a fundamental factor in the formation, progression, and rupture of cerebral aneurysms. Understanding these mechanisms is important to improve their rupture risk assessment and treatment. In this study, we analyze the blood flow field in a growing cerebral aneurysm using experimental particle image velocimetry (PIV) and computational fluid dynamics (CFD) techniques. Patient-specific models were constructed from longitudinal 3D computed tomography angiography images acquired at 1-y intervals. Physical silicone models were constructed from the computed tomography angiography images using rapid prototyping techniques, and pulsatile flow fields were measured with PIV. Corresponding CFD models were created and run under matching flow conditions. Both flow fields were aligned, interpolated, and compared qualitatively by inspection and quantitatively by defining similarity measures between the PIV and CFD vector fields. Results showed that both flow fields were in good agreement. Specifically, both techniques provided consistent representations of the main intra-aneurysmal flow structures and their change during the geometric evolution of the aneurysm. Despite differences observed mainly in the near wall region, and the inherent limitations of each technique, the information derived is consistent and can be used to study the role of hemodynamics in the natural history of intracranial aneurysms.

[1]  Kazuo Tanishita,et al.  Intra-aneurysmal blood flow based on patient-specific CT angiogram , 2010 .

[2]  Alejandro F. Frangi,et al.  Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity , 2005, IEEE Transactions on Medical Imaging.

[3]  K. Katada,et al.  Magnitude and Role of Wall Shear Stress on Cerebral Aneurysm: Computational Fluid Dynamic Study of 20 Middle Cerebral Artery Aneurysms , 2004, Stroke.

[4]  C. Putman,et al.  Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. , 2005, AJNR. American journal of neuroradiology.

[5]  R. Löhner,et al.  Fast numerical solutions of patient‐specific blood flows in 3D arterial systems , 2010, International journal for numerical methods in biomedical engineering.

[6]  A. Ropper,et al.  Outcome 1 year after SAH from cerebral aneurysm. Management morbidity, mortality, and functional status in 112 consecutive good-risk patients. , 1984, Journal of neurosurgery.

[7]  M. Lawton,et al.  Correlation between lumenal geometry changes and hemodynamics in fusiform intracranial aneurysms. , 2005, AJNR. American journal of neuroradiology.

[8]  D. Sujudi,et al.  Identification of Swirling Flow in 3-D Vector Fields , 1995 .

[9]  Daniel J. Valentino,et al.  Effects of segmentation on patient-specific numerical simulation of cerebral aneurysm hemodynamics , 2006, SPIE Medical Imaging.

[10]  J P Villablanca,et al.  Intra-aneurysmal hemodynamics during the growth of an unruptured aneurysm: in vitro study using longitudinal CT angiogram database. , 2007, AJNR. American journal of neuroradiology.

[11]  D. Wiebers,et al.  Impact of Unruptured Intracranial Aneurysms on Public Health in the United States , 1992, Stroke.

[12]  Hongyu Li,et al.  Similarity Measure for Vector Field Learning , 2006, ISNN.

[13]  T Kirino,et al.  Risk of rupture from incidental cerebral aneurysms. , 2000, Journal of neurosurgery.

[14]  D. Holdsworth,et al.  PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models. , 2008, Journal of biomechanical engineering.

[15]  Ronald Peikert,et al.  A higher-order method for finding vortex core lines , 1998 .

[16]  S. Juvela,et al.  Natural history of unruptured intracranial aneurysms: a long-term follow-up study. , 1993, Journal of neurosurgery.

[17]  C M Putman,et al.  Hemodynamics and Bleb Formation in Intracranial Aneurysms , 2010, American Journal of Neuroradiology.

[18]  F. Viñuela,et al.  Intraaneurysmal flow dynamics study featuring an acrylic aneurysm model manufactured using a computerized tomography angiogram as a mold. , 2001, Journal of neurosurgery.

[19]  C. Putman,et al.  Hemodynamics of Cerebral Aneurysms. , 2009, Annual review of fluid mechanics.

[20]  F Viñuela,et al.  Embolization of incidental cerebral aneurysms by using the Guglielmi detachable coil system. , 1998, Journal of neurosurgery.

[21]  D. Nichols,et al.  Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment , 2003, The Lancet.

[22]  M. Hennerici,et al.  Transcranial Doppler ultrasound for the assessment of intracranial arterial flow velocity--Part 1. Examination technique and normal values. , 1987, Surgical neurology.

[23]  J. Torner,et al.  Aneurysmal rebleeding: a preliminary report from the Cooperative Aneurysm Study. , 1983, Neurosurgery.

[24]  A. Algra,et al.  Prevalence and risk of rupture of intracranial aneurysms: a systematic review. , 1998, Stroke.

[25]  D. Holdsworth,et al.  Image-based computational simulation of flow dynamics in a giant intracranial aneurysm. , 2003, AJNR. American journal of neuroradiology.

[26]  Ronald Peikert,et al.  The "Parallel Vectors" operator-a vector field visualization primitive , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[27]  Alastair J. Martin,et al.  Aneurysm Growth Occurs at Region of Low Wall Shear Stress: Patient-Specific Correlation of Hemodynamics and Growth in a Longitudinal Study , 2008, Stroke.

[28]  A. Valencia,et al.  Blood flow dynamics in patient-specific cerebral aneurysm models: the relationship between wall shear stress and aneurysm area index. , 2008, Medical engineering & physics.

[29]  K. Furie,et al.  Functional Recovery After Rehabilitation for Cerebellar Stroke , 2001, Stroke.