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Abstract #0590

Tissue Outcome Prediction in Ischaemic Stroke with Diffusion, Perfusion and pH Sensitive CEST Imaging at Three Different Time Points

Jacob Levman 1 , George Harston 2 , Yee Kai Tee 1 , Thomas W Okell 3 , Nicholas Blockley 3 , Michael Chappell 1 , Peter Jezzard 3 , James Kennedy 2 , and Stephen Payne 1

1 Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, England, United Kingdom, 2 Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Oxford, England, United Kingdom, 3 Department of Clinical Neurosciences, Oxford Centre for Functional MRI of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, England, United Kingdom

This study assessed MRI modalities for predicting tissue outcome in acute stroke subjects. Diffusion, perfusion and pH sensitive MR images were acquired at 4, 6 and 24 hours post stroke. Follow-up imaging was performed at 7 and 28 days. Receiver operating characteristic curve analysis was performed to evaluate each modalitys ability to predict tissue outcome as assessed by follow-up fluid attenuated inversion recovery (FLAIR) imaging. A demonstration of machine learning combining the three acute modalities was able to predict an additional 6% of FLAIR assessed tissue damage that was not suspicious based on diffusion characteristics alone.

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