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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