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6548 Forest Park Pkwy, St. Louis, MO 63112, USA

https://mems.washu.edu/
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  • Vitaliy L. Rayz, PhD
  • Weldon School of Biomedical Engineering, Purdue University, 
  • Radiology and Imaging Sciences, Indiana University School of Medicine

 

Blood flow regulates vascular function and remodeling and governs transport through the circulation. Hemodynamics plays an important role in cerebrovascular diseases, including intracranial atherosclerotic disease and cerebral aneurysms, and contributes to intracranial pressure regulation and cerebrospinal fluid motion. Reliable quantification of relevant flow metrics can therefore provide valuable information for assessing disease progression and planning treatment. Image-based computational fluid dynamics (CFD) is commonly used to simulate subject-specific flow fields, but its reliability depends on modeling assumptions and uncertainties in vascular geometries and boundary conditions derived from medical imaging. Alternatively, flow velocities can be measured in vivo with three-directional phase-contrast MRI velocimetry (4D Flow MRI), although limited spatiotemporal resolution and measurement noise can affect the accuracy of derived flow metrics. In this talk we will discuss the capabilities and limitations of current imaging and modeling approaches for subject-specific analysis of cerebral flow dynamics. We will demonstrate how image-based CFD has been used to investigate associations between hemodynamics and cerebral aneurysm growth, examine the accuracy and uncertainty of MRI-based flow quantification, and present a physics-guided deep-learning approach for denoising and super-resolution of 4D flow MRI. Finally, we will discuss how flow modeling can guide the design of drug-delivery and intravascular chemofiltration systems.

 

  • Anna Christ

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