• Michael M Chen, Patrick M Chen, Lovella Hailey, Melissa Mortin, Karen Rapp, Kunal Agrawal, Branko Huisa, Royya Modir, Dawn M Meyer, Thomas Hemmen, and Brett C Meyer.
• Department of Neurosciences, University of San Diego Health, Stroke Center, San Diego, CA.
• J Neuroimaging. 2019 Jul 1; 29 (4): 476-480.

Background And PurposeIdentifying a last known well (LKW) time surrogate for acute stroke is vital to increase stroke treatment. Diffusion-weighted imaging (DWI) signal intensity initially increases from onset of stroke but mapping a reliable time course to the signal intensity has not been demonstrated.MethodsWe retrospectively reviewed stroke code patients between 1/2016 and 6/2017 from the prospective; Institutional review board (IRB) approved University of California San Diego Stroke Registry. Patients who had magnetic resonance imaging of brain from onset, with or without intervention, are included. All ischemic strokes were confirmed and timing from onset to imaging was calculated. Raw DWI intensity is measured using IMPAX software and compared to contralateral side for control for a relative DWI intensity (rDWI). LKW and magnetic resonance imaging (MRI) time were collected by chart review. Correlation is assessed using Pearson correlation coefficient between DWI intensity, rDWI, and time to MRI imaging. 1.5T, 3T, and combined modalities were examined.ResultsSeventy-eight patients were included in this analysis. Overall, there was statistically significant positive correlation (.53, P < .001) between DWI intensity and LKW time irrespective of scanner strength. Using 1.5T analyses, there was good correlation (.46, P < .001). 3T MRI analysis further showed comparatively stronger positive correlation (.66, P < .001).ConclusionsThere is good correlation between DWI intensity and minutes from onset to MRI. This suggests a time-dependent DWI intensity response and supports the potential use of DWI intensity measurements to extrapolate an LKW time. Further studies are being pursued to increase both experience and generalizability.© 2019 by the American Society of Neuroimaging.

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