Synchrotron microtomography of coiled aneurysm phantoms: improving accuracy of porous medium models for coil embolization of intracranial aneurysms

ORAL

Abstract

Cerebral aneurysms are often embolized with coils to reduce blood flow into the aneurysmal sac, promoting the development of a thrombus to reduce the risk of rupture. Computational analysis of the hemodynamics inside the aneurysm, before and after treatment, is a useful tool to better understand the effect of endovascular treatment on thrombus formation. The current standard is to model the coil mass as an isotropic homogeneous porous medium. This study proposes a new anisotropic porous model created by homogenization of the exact coil geometry obtained from Synchrotron X-ray Microtomography. Silicon phantoms built from patient-specific aneurysms were treated with embolic coils and microtomography of these models was performed at ESRF (Grenoble, France). The coil geometries were integrated with the vessel lumen reconstruction for CFD analysis. The results of standard homogeneous isotropic and novel heterogeneous anisotropic models are compared to the flow simulations around the actual coil geometries. The homogenization-based coil model was found to be more accurate (closer to the coil-resolved simulations) for the prediction of flow in the aneurysmal sac (+70% improvement in RSME compared to isotropic porous media) and wall shear stress at the neck of the aneurysm (+64%).

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Presenters

  • Michael C. Barbour

    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA

Authors

  • Michael C. Barbour

    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA

  • Fanette Chassagne

    • Department of Mechanical Engineering, University of Washington
    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
    • University of Washington, Department of Mechanical Engineering

  • Laurel Morgan Miller Marsh

    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA

  • Venkat Keshav Chivukula

    • Department of Mechanical Engineering, University of Washington
    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
    • University of Washington, Department of Mechanical Engineering
    • University of Washington

  • Christian Geindreau

    • Laboratoire 3SR, Université Grenoble Alpes, Grenoble, France

  • Sabine Rolland du Roscoat

    • Laboratoire 3SR, Université Grenoble Alpes, Grenoble, France

  • Cory M. Kelly

    • Department of Neurological Surgery, University of Washington, Seattle, WA, USA

  • Samuel H. Levy

    • Department of Neurological Surgery, University of Washington, Seattle, WA, USA

  • Michael R Levitt

    • Department of Neurological Surgery, University of Washington, Seattle, WA, USA
    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA, Department of Neurological Surgery, University of Washington, Seattle, WA, USA

  • Louis J. Kim

    • Department of Neurological Surgery, University of Washington
    • Department of Neurological Surgery, University of Washington, Seattle, WA, USA
    • Department of Neurological Surgery, University of Washington, Seattle, WA, USA, Department of Radiology, University of Washington, Seattle, WA, USA

  • Alberto Osuna Aliseda

    • University of Washington
    • Department of Mechanical Engineering, University of Washington
    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA, Department of Neurological Surgery, University of Washington, Seattle, WA, USA
    • Mechanical Engineering Department, University of Washington
    • Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
    • Mechanical Engineering, University of Washington, Seattle, USA