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Research Papers

Numerical Simulations of Flow in Cerebral Aneurysms: Comparison of CFD Results and In Vivo MRI Measurements

[+] Author and Article Information
Vitaliy L. Rayz

Radiology Service, VA Medical Center - San Francisco, 4150 Clement Street, San Francisco, CA 94121vlrayz@gmail.com

Loic Boussel

Radiology Service, VA Medical Center - San Francisco, 4150 Clement Street, San Francisco, CA 94121; Créatis-LRMN (LB, PCD), UMR CNRS 5515, INSERM U630, Lyon, Franceloic.boussel@gmail.com

Gabriel Acevedo-Bolton

Radiology Service, VA Medical Center - San Francisco, 4150 Clement Street, San Francisco, CA 94121acevbolt2@yahoo.com

Alastair J. Martin

Department of Radiology, University of California San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143amartin@radiology.ucsf.edu

William L. Young

Department of Anesthesia and Perioperative Care, and Department of Neurological Surgery and Neurology, University of California San Francisco, 1001 Potrero Avenue, San Francisco, CA 94110youngw@anesthesia.ucsf.edu

Michael T. Lawton

Department of Neurological Surgery, University of California San Francisco, 1001 Potrero Avenue, San Francisco, CA 94110lawtonm@neurosurg.ucsf.edu

Randall Higashida

Department of Neurological Surgery, University of California San Francisco, 1001 Potrero Avenue, San Francisco, CA 94110randall.higashida@radiology.ucsf.edu

David Saloner

Department of Radiology, University of California San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143; Vascular Imaging Research Center, VA Medical Center - San Francisco, 4150 Clement Street, San Francisco, CA 94121saloner@radmail.ucsf.edu

J Biomech Eng 130(5), 051011 (Aug 29, 2008) (9 pages) doi:10.1115/1.2970056 History: Received May 03, 2007; Revised October 23, 2007; Published August 29, 2008

Computational fluid dynamics (CFD) methods can be used to compute the velocity field in patient-specific vascular geometries for pulsatile physiological flow. Those simulations require geometric and hemodynamic boundary values. The purpose of this study is to demonstrate that CFD models constructed from patient-specific magnetic resonance (MR) angiography and velocimetry data predict flow fields that are in good agreement with in vivo measurements and therefore can provide valuable information for clinicians. The effect of the inlet flow rate conditions on calculated velocity fields was investigated. We assessed the internal consistency of our approach by comparing CFD predictions of the in-plane velocity field to the corresponding in vivo MR velocimetry measurements. Patient-specific surface models of four basilar artery aneurysms were constructed from contrast-enhanced MR angiography data. CFD simulations were carried out in those models using patient-specific flow conditions extracted from MR velocity measurements of flow in the inlet vessels. The simulation results computed for slices through the vasculature of interest were compared with in-plane velocity measurements acquired with phase-contrast MR imaging in vivo. The sensitivity of the flow fields to inlet flow ratio variations was assessed by simulating five different inlet flow scenarios for each of the basilar aneurysm models. In the majority of cases, altering the inlet flow ratio caused major changes in the flow fields predicted in the aneurysm. A good agreement was found between the flow fields measured in vivo using the in-plane MR velocimetry technique and those predicted with CFD simulations. The study serves to demonstrate the consistency and reliability of both MR imaging and numerical modeling methods. The results demonstrate the clinical relevance of computational models and suggest that realistic patient-specific flow conditions are required for numerical simulations of the flow in aneurysmal blood vessels.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Patient-specific model construction. (a) CE-MRA maximum intensity image of the cerebral arteries; (b) 3D surface constructed for numerical modeling coregistered with MR slices to ensure that the surface represents the actual lumenal geometry.

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Figure 2

Patient-specific pulse measured with MRV for four basilar aneurysm patients. Solid and dashed lines show average velocities measured in the right and left vertebral, respectively.

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Figure 3

Orientation and position of the 2D slice in the CFD model. This cross-section matches the in-plane MRI velocity slice acquired in vivo.

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Figure 4

Flow streamlines (top row) and wall shear stress distribution (bottom row) predicted with CFD for five inlet flow scenarios. (a) Left vertebral (LV), 98%; right vertebral (RV), 2%. (b) LV, 75%; RV, 25%. (c) LV, 50%; RV, 50%. (d) LV, 25%; RV, 75%. (e) LV, 2%; RV, 98%.

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Figure 5

Flow fields predicted with CFD in three basilar aneurysm models for three inlet flow ratio scenarios. (a) LV, 98%; RV, 2%. (b) LV, 50%; RV, 50%. (c) LV, 2%; RV, 98%.

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Figure 6

Comparison of CFD results and in vivo phase-contrast MRI in-plane velocimetry. (a) PC-MRI in-plane magnitude image. (b) PC-MRI in-plane phase image (velocity). (c) CFD velocity field. (d) CFD velocity fields averaged over a 5 mm slice.

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Figure 7

Comparison of CFD results and in vivo phase-contrast MRI in-plane velocimetry for three basilar aneurysm patients. Top row: PC-MRI in-plane phase image (velocity); bottom row: CFD velocity field averaged over a 5 mm slice.

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Figure 8

A change in the position of a 2D slice through the CFD data may result in a different image of the flow field. (a) 2D slice matching the PC-MRI plane. (b) 2D slice obtained by a 10 deg rotation and a 1 mm offset of the original plane.

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