73th Annual Meeting of the APS Division of Fluid Dynamics (November 22, 2020 — November 24, 2020)

P0004: Spectral Landscapes of Flow Instabilities in Brain Aneurysms

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Authors

• Thangam Natarajan, Department of Mechanical and Industrial Engineering, University of Toronto.
• Daniel MacDonald, Department of Mechanical and Industrial Engineering, University of Toronto.
• Lucas Temor, Department of Mechanical and Industrial Engineering, University of Toronto.
• Peter Coppin, Faculty of Design, OCAD University
• David Steinman, Department of Mechanical and Industrial Engineering, University of Toronto.

DOI: https://doi.org/10.1103/APS.DFD.2020.GFM.P0004

Rupture of a brain aneurysm is a devastating event, leading to death or permanent disability in the majority of cases. Roughly 1 in 30 adults harbors a brain aneurysm, and unruptured aneurysms are being detected more frequently due to the growing use of 3D medical imaging.  Our research focuses on the use of “patient-specific” computational fluid dynamics (CFD) to help doctors decide whether and how to treat an unruptured aneurysm, since the risk of treating can often outweigh the risk of rupture. This poster describes how our team and engineers and designers are using machine learning and perceptual-cognitive principles to make sense of the large amounts of clinical CFD data we generate, in order to identify which kinds of fluid dynamic features within the aneurysm sac may make it prone to rupture.