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Abstract #0783

Super-resolution assessment of relative pressure in intracranial atherosclerosis using ML-enhanced 4D Flow MRI

Patrick Winter1,2, David Marlevi3,4, Maria Aristova2, Edward Ferdian5, Jonas Schollenberger6, Alireza Vali2, Jackson Moore2, Michael Markl2, Ramez Abdallah2, Sameer Ansari2, C Alberto Figuerora6, David Nordsletten6, Alistair Young6, and Susanne Schnell1,2
1Department of Medical Physics, University of Greifswald, Greifswald, Germany, 2Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, 3Dept Molecular Medicine and Surgery, Karolinska Institutet, Solna, Sweden, 4Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States, 55Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand, 6Department of Anatomy and Medical Imaging, University of Michigan, Ann Arbor, MI, United States

Synopsis

Keywords: Stroke, Atherosclerosis, intracranial atherosclerotic disease, stenosis, pressure differencesIn vivo measurements of intracranial pressure differences using 4D flow are useful to assess health risks associated with intracranial atherosclerotic disease (ICAD). In the clinical routine, approximations of the Navier-Stokes equation are used to derive relative pressure values, which can be inaccurate in intracranial vessels. Recently we presented an algorithm using a virtual work-energy formulation(vWERP). While this technique yields more accurate pressure estimations in intracranial settings, still systematic errors due to insufficient spatial resolution were observed. Here, we apply artificial intelligence-based super resolution for more accurate assessments of pressure values near the stenosis in a cohort of ICAD patients.

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