Related Experiment Video
Updated: Mar 27, 2026
A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Can MRI quantification help evaluate stroke age?
Samuel Emeriau1, Azzedine Benaïssa1, Olivier Toubas1
1CHU de Reims, Reims University, Hôpital Maison-Blanche, Department of Neuroradiology, 45, rue Cognacq-Jay, 51092 Reims cedex, France.
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.
Materials And 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.
Insights
Quantifying MRI signals can help estimate stroke timing, but visual assessment of diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) mismatch remains more accurate for determining stroke-to-MRI delay.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) mismatch is established for estimating stroke-to-magnetic resonance imaging (MRI) delay.
- This study investigated enhancing stroke dating accuracy by quantifying MRI signals (DWI and FLAIR) compared to visual mismatch assessment.
Purpose of the Study:
- To evaluate the efficacy of quantitative MRI signal analysis in predicting stroke-to-MRI delay.
- To compare the performance of quantitative MRI signal analysis against the visual estimation of DWI-FLAIR mismatch.
Main Methods:
- Retrospective analysis of 194 ischemic stroke patients (middle cerebral artery territory) within 12 hours of 3T MRI.
- Visual estimation of DWI-FLAIR mismatch by two radiologists.
- Manual segmentation for quantitative MRI signal analysis (DWI and FLAIR).
Main Results:
- Quantitative variables including B0, B1000, and apparent diffusion coefficient (ADC) values were predictive of stroke-to-MRI delay.
- FLAIR signal quantification was not found to be predictive.
- The relative B1000 value showed the best predictive performance among quantitative measures, comparable to visual classification.
Conclusions:
- Quantitative MRI signal analysis can be a useful adjunct for estimating stroke onset.
- Visual estimation of DWI-FLAIR mismatch currently remains superior to quantitative methods for stroke age determination.
