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Abstract #2454

Automated perfusion lesion delineation in stroke: comparison with experts and alternative automated strategies

Dave Saraswat1,2, Jiun-Yiing Hu1,2, Ivana Galinovic1, Jochen Fiebach1, and Ahmed Khalil1,3,4

1Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany, 2International Graduate Program Medical Neurosciences, Charité – Universitätsmedizin Berlin, Berlin, Germany, 3Berlin School of Mind & Brain, Humboldt Universität zu Berlin, Berlin, Germany, 4Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

This study aimed to validate an in-house script that detects perfusion lesions in dynamic susceptibility contrast magnetic resonance images of acute stroke patients and compare its performance with commercially available software. Perfusion lesions were estimated from time-to-maximum and mean transit time maps of 94 stroke patients using our algorithm, Perfscape/Neuroscape, PMA, and Stroketool. These automatically delineated lesions were volumetrically and spatially compared with those delineated by a trained expert. Our algorithm performs comparably to other programs on the market and overestimates lesion volumes to a lesser extent; however, it is currently limited by its reliance on manual input.

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