Mapping a Reliable Stroke Onset Time Course Using Signal Intensity on DWI Scans. Issue 4 (1st April 2019)

• Record Type: Journal Article
• Authors: Chen, Michael M.; Chen, Patrick M.; Hailey, Lovella; Mortin, Melissa; Rapp, Karen; Agrawal, Kunal; Huisa, Branko; Modir, Royya; Meyer, Dawn M.; Hemmen, Thomas; Meyer, Brett C.
• Is Part Of: Journal of neuroimaging. Volume 29:Issue 4(2019)
• Page Start: 476
• Page End: 480
• Publication Date: 2019-04-01
• Subjects: Stroke -- cerebrovascular disease -- MRI -- DWI -- last known well time; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/jon.12616
• Languages: English
• ISSNs: 1051-2284

Abstract

ABSTRACT: BACKGROUND AND PURPOSE: Identifying 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. METHODS: We 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. RESULTS: Seventy‐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). CONCLUSIONS: There 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.