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Abstract #5040

Predicting the rate of stroke evolution in canines using MR-derived time-to-peak perfusion maps

Robert King1,2, Matthew Gounis2, and Mohammed Salman Shazeeb1,2,3

1Worcester Polytechnic Institute, Worcester, MA, United States, 2University of Massachusetts Medical School, Worcester, MA, United States, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States

Mechanical thrombectomy for the treatment of ischemic stroke shows high rates of recanalization; however, some patients still have poor clinical outcome. The canine large vessel occlusion model has been developed to better understand new treatments. This model has a drawback of inconsistent rates of stroke growth. Here, MRI perfusion based time-to-peak maps were used to predict the rate of infarct growth as validated by ADC-derived maps. Classification of canines into either fast or slow evolvers was reliably shown with this method of analysis, allowing for a better understanding of new therapeutics and potentially for better patient selection for thrombectomy.

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