Anke Wouters1,2,3, Patrick Dupont4, Soren Christensen5, Bo Norrving6, Rico Laage7, Götz Thomalla8, Stephanie Kemp5, Maarten Lansberg5, Vincent Thijs9, Gregory W Albers5, Robin Lemmens1,2,3. 1. Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), KU Leuven - University of Leuven, Leuven, Belgium. 2. Center for Brain & Disease Research, Laboratory of Neurobiology, VIB, Leuven, Belgium. 3. Department of Neurology, University Hospitals Leuven, Leuven, Belgium. 4. Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium. 5. Stanford Stroke Center, Stanford University Medical Center, Palo Alto, USA. 6. Department of Clinical Sciences, Section of Neurology, Lund University, Lund, Sweden. 7. Guided Development GmbH, Heidelberg, Germany. 8. Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 9. 9Florey Institute of Neuroscience and Mental Health, Heidelberg, Australia.
Abstract
INTRODUCTION: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. PATIENTS AND METHODS: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. RESULTS: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79-0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69-0.95). DISCUSSION: After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. CONCLUSION: In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.
INTRODUCTION: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. PATIENTS AND METHODS: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. RESULTS: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79-0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69-0.95). DISCUSSION: After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. CONCLUSION: In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.
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Authors: S Stampfl; P A Ringleb; S Haehnel; A Rocco; C Herweh; C Hametner; M Pham; M Moehlenbruch; M Bendszus; S Rohde Journal: AJNR Am J Neuroradiol Date: 2012-12-20 Impact factor: 3.825
Authors: E Bernd Ringelstein; Vincent Thijs; Bo Norrving; Angel Chamorro; Franz Aichner; Martin Grond; Jeff Saver; Rico Laage; Armin Schneider; Frank Rathgeb; Gerhard Vogt; Gabriele Charissé; Jochen B Fiebach; Stefan Schwab; Wolf R Schäbitz; Rainer Kollmar; Marc Fisher; Miroslav Brozman; David Skoloudik; Franz Gruber; Joaquin Serena Leal; Roland Veltkamp; Martin Köhrmann; Jörg Berrouschot Journal: Stroke Date: 2013-08-20 Impact factor: 7.914