Abstract #4125

Perfusion And Permeability Imaging as Diagnostic And Prognostic Biomarkers of Cavernous Angioma with Symptomatic Hemorrhage

Je Yeong Sone¹, Yan Li^1,2, Nicholas Hobson¹, Sharbel G. Romanos¹, Abhinav Srinath¹, Seán B. Lyne¹, Abdallah Shkoukani¹, Julián Carrión-Penagos¹, Agnieszka Stadnik¹, Kristina Piedad¹, Rhonda Lightle¹, Thomas Moore¹, Ying Li¹, Dehua Bi^1,3, Timothy Carroll⁴, Yuan Ji³, Romuald Girard¹, and Issam A. Awad¹

¹Neurovascular Surgery Program, Section of Neurosurgery, Department of Surgery, University of Chicago Medicine and Biological Sciences, Chicago, IL, United States, ²Bioinformatics Core, Center for Research Informatics, The University of Chicago, Chicago, IL, United States, ³Department of Public Health Sciences, The University of Chicago, Chicago, IL, United States, ⁴Department of Diagnostic Radiology, University of Chicago Medicine and Biological Sciences, Chicago, IL, United States

A cavernous angioma with symptomatic hemorrhage (CASH) is more likely to rebleed for several years while conventional MRI signatures of hemorrhage may disappear after a few weeks. We aimed to investigate whether perfusion or permeability derivations of dynamic contrast-enhanced quantitative perfusion-MRI (DCEQP) can distinguish a lesion that had bled earlier or predict subsequent lesional bleeding/growth after DCEQP. Machine learning and Bayesian model selection showed that perfusion imaging may distinguish cases with CASH 3–12 months prior to the scan (diagnostic biomarker) while a combination of permeability and perfusion derivations may predict bleeding/growth in the subsequent year (prognostic biomarker).

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