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Abstract #0756

Fully Automated DWI-PWI Mismatch Quantification in Acute Stroke

Kartheeban Nargenthiraja1, Lars Riisgaard Ribe1, Kristina Dupont Hougaard, 12, Josef Alawneh3, Tae-Hee Cho4, Susanne Siemonsen5, Josep Puig Alcantara6, Niels Hjort1, Salvador Pedraza6, Jens Fiehler5, Norbert Nighoghossian4, Jean-Claude Baron3, Leif stergaard1, Kim Mouridsen1

1Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark; 2Department of Neurology, Aarhus University Hospital, Aarhus C, Denmark; 3Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom; 4Hopital Neurologique Pierre Wertheimer Creatis, Insa/UCBL, CNRS UMR5220 - INSERM U1044, Lyon I, France; 5Department of Neuroradiology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany; 6Department of Radiology-IDI, University Hospital Dr Josep Trueta of Girona, Spain

The identification of perfusion-diffusion (PWI-DWI) mismatch tissue in acute stroke is highly subjective. We present an algorithm which performs automatic mismatch segmentation based on PWI and DWI images, and compare the mismatch masks to manually outlined masks performed by four experts in 168 patients. PWI lesion outlining was performed on fitted TTP maps by subsequent morphological grayscale reconstruction, normalization, thresholding, connected component analysis, and level-set smoothing. DWI lesion outlining was performed on B=1000 images by morphological grayscale reconstruction, and level-set smoothing. Volumes of automatic masks show good agreement with volumes of masks where three or more experts agreed (R2=0.93)