title: Can MRI quantification help evaluate stroke age?
abstract: BACKGROUND
  Diffusion-weighted imaging (DWI) fluid-attenuated inversion recovery (FLAIR) mismatch has a proven ability to estimate stroke-to-magnetic resonance imaging (MRI) delay. We evaluated the possibility of enhancing this estimation by quantifying MRI (DWI and FLAIR) signals, and compared this approach to the visual evaluation of DWI-FLAIR mismatch.
  
  
  METHODS
  This retrospective study included 194 patients presenting an ischemic stroke in the middle cerebral artery territory that had been explored with 3T MRI within 12h. According to the study design, written informed consent was waived and patient information was anonymized and de-identified prior to analysis. DWI-FLAIR mismatch was visually estimated by two radiologists and a quantification of MRI signals based on a manual segmentation of stroke lesion volume was performed. Using their receiver operating curve and area under the curve (AUC), we identified the variables of MRI quantification that were predictive of stroke-to-MRI delay, then compared their performance against visual classification.
  
  
  RESULTS
  The quantitative variables identified as predictive of stroke-to-MRI delay were: 1st quartile, 3rd quartile and median values of B0; 1st quartile, 3rd quartile, median and relative values of B1000; 1st quartile and relative values of the apparent diffusion coefficient. FLAIR was not found to be predictive. The AUC values of these variables ranged between 0618±0.053 and 0.683±0.048. The relative value of B1000 appeared to be the best predictive quantitative variable, with predictive values comparable to visual classification.
  
  
  CONCLUSIONS
  The quantification of MRI signal may be a helpful tool for stroke dating but cannot outperform the visual estimation of stroke lesion age.
authors.affiliation: CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France. Electronic address: semeriau@chu-reims.fr.
authors.forename: Samuel
authors.initials: S
authors.lastname: Emeriau
authors.affiliation: CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France.
authors.forename: Azzedine
authors.initials: A
authors.lastname: Benaïssa
authors.affiliation: CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Toubas
authors.affiliation: CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France.
authors.forename: Francis
authors.initials: F
authors.lastname: Pombourcq
authors.affiliation: CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France.
authors.forename: Laurent
authors.initials: L
authors.lastname: Pierot
mesh_terms: D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D020768:Middle Cerebral Artery / Q000503:physiopathology; D012189:Retrospective Studies; D020521:Stroke / Q000175:diagnosis* / Q000473:pathology* / Q000503:physiopathology
keywords: Acute stroke; Magnetic resonance imaging; Prognosis; Quantitative evaluation; Therapeutic thrombolysis