Automated DWI-FLAIR mismatch assessment in stroke using DWI only.
Authors
Affiliations (21)
Affiliations (21)
- IMA-BRAIN, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris (IPNP), Université Paris Cité, Paris, France.
- Neuroradiology Department, Hôpital Sainte Anne, GHU-Paris Psychiatrie et Neurosciences, Paris, France.
- Department of Neurosciences, Experimental Neurology, KU Leuven - University of Leuven, Leuven, Belgium.
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium.
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
- Department of Neurology, Medical Park Berlin Humboldtmühle, Berlin, Germany.
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom.
- Hospices Civils de Lyon, Department of Neurology and Stroke Center, Lyon University, Lyon, France.
- Université Claude Bernard Lyon 1, Bron, France.
- Department of Radiology (CDI) and IDIBAPS, Hospital Clinic, Barcelona, Spain.
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark.
- Stroke Division, University of Melbourne, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia.
- CIC, Innovation Technologique, Université de Lorraine, INSERM 1433, Nancy, France.
- Department of Neurology, Foch Hospital, Versailles Saint-Quentin-en-Yvelines University, Suresnes, France.
- Diagnostic and Interventional Neuroradiology Department, CHRU de Tours, Tours, Centre Val de Loire, France.
- CIC-IT 1415, INSERM 1253 iBrain, Tours, Centre Val de Loire, France.
- Stroke Team, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris (IPNP), Université Paris Cité, Paris, France.
- Neurology Department, Hôpital Sainte Anne, GHU-Paris Psychiatrie et Neurosciences, Paris, France.
Abstract
In Acute Ischemic Stroke (AIS), mismatch between Diffusion-Weighted Imaging (DWI) and Fluid-Attenuated Inversion-Recovery (FLAIR) helps identify patients who can benefit from thrombolysis when stroke onset time is unknown (15% of AIS). However, visual assessment has suboptimal observer agreement. Our study aims to develop and validate a Deep-Learning model for predicting DWI-FLAIR mismatch using solely DWI data. This retrospective study included AIS patients from ETIS registry (derivation cohort, 2018-2024) and WAKE-UP trial (validation cohort, 2012-2017). DWI-FLAIR mismatch was rated visually. We trained a model to predict manually-labeled FLAIR visible areas (FVA) matching the DWI lesion on baseline and early follow-up MRIs, using only DWI as input. FVA-index was defined as the volume of predicted regions. Area under the ROC curve (AUC) and optimal FVA-index cutoff to predict DWI-FLAIR mismatch in the derivation cohort were computed. Validation was performed using baseline MRIs of the validation cohort. The derivation cohort included 3605 MRIs in 2922 patients and the validation cohort 844 MRIs in 844 patients. FVA-index demonstrated strong predictive value for DWI-FLAIR mismatch in baseline MRIs from the derivation (<i>n</i> = 2453, AUC = 0.85, 95%CI: 0.84-0.87) and validation cohort (<i>n</i> = 844, AUC = 0.86, 95%CI: 0.84-0.89). With an optimal FVA-index cutoff at 0.5, we obtained a kappa of 0.54 (95%CI: 0.48-0.59), 70% sensitivity (378/537, 95%CI: 66-74%) and 88% specificity (269/307, 95%CI: 83-91%) in the validation cohort. The model accurately predicts DWI-FLAIR mismatch in AIS patients with unknown stroke onset. It could aid readers when visual rating is challenging, or FLAIR unavailable.