Related Experiment Video
Updated: May 5, 2026
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Automated DWI-FLAIR mismatch assessment in stroke using DWI only
Joseph Benzakoun1,2,3, Lauranne Scheldeman3,4, Anke Wouters3,4
1IMA-BRAIN, INSERM U1266, Institute of Psychiatry and Neuroscience of Paris (IPNP), Université Paris Cité, Paris, France.
Introduction:
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.
Patients And Methods:
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.
Results:
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 (n = 2453, AUC = 0.85, 95%CI: 0.84-0.87) and validation cohort (n = 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.
Discussion And Conclusion:
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.
