Document Detail


Quantitative measurements of relative fluid-attenuated inversion recovery (FLAIR) signal intensities in acute stroke for the prediction of time from symptom onset.
MedLine Citation:
PMID:  23047272     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In acute stroke magnetic resonance imaging, a 'mismatch' between visibility of an ischemic lesion on diffusion-weighted imaging (DWI) and missing corresponding parenchymal hyperintensities on fluid-attenuated inversion recovery (FLAIR) data sets was shown to identify patients with time from symptom onset ≤4.5 hours with high specificity. However, moderate sensitivity and suboptimal interpreter agreement are limitations of a visual rating of FLAIR lesion visibility. We tested refined image analysis methods in patients included in the previously published PREFLAIR study using refined visual analysis and quantitative measurements of relative FLAIR signal intensity (rSI) from a three-dimensional, segmented stroke lesion volume. A total of 399 patients were included. The rSI of FLAIR lesions showed a moderate correlation with time from symptom onset (r=0.382, P<0.001). A FLAIR rSI threshold of <1.0721 predicted symptom onset ≤4.5 hours with slightly increased specificity (0.85 versus 0.78) but also slightly decreased sensitivity (0.47 versus 0.58) as compared with visual analysis. Refined visual analysis differentiating between 'subtle' and 'obvious' FLAIR hyperintensities and classification and regression tree algorithms combining information from visual and quantitative analysis also did not improve diagnostic accuracy. Our results raise doubts whether the prediction of stroke onset time by visual image judgment can be improved by quantitative rSI measurements.
Authors:
Bastian Cheng; Mathias Brinkmann; Nils D Forkert; Andras Treszl; Martin Ebinger; Martin Köhrmann; Ona Wu; Dong-Wha Kang; David S Liebeskind; Thomas Tourdias; Oliver C Singer; Soren Christensen; Marie Luby; Steven Warach; Jens Fiehler; Jochen B Fiebach; Christian Gerloff; Götz Thomalla;
Publication Detail:
Type:  Journal Article; Multicenter Study; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2012-10-10
Journal Detail:
Title:  Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism     Volume:  33     ISSN:  1559-7016     ISO Abbreviation:  J. Cereb. Blood Flow Metab.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-01-02     Completed Date:  2013-02-21     Revised Date:  2013-07-23    
Medline Journal Info:
Nlm Unique ID:  8112566     Medline TA:  J Cereb Blood Flow Metab     Country:  United States    
Other Details:
Languages:  eng     Pagination:  76-84     Citation Subset:  IM    
Affiliation:
Klinik und Poliklinik für Neurologie, Kopf- und Neurozentrum, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany. b.cheng@uke.uni-hamburg.de
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MeSH Terms
Descriptor/Qualifier:
Aged
Algorithms
Blood Volume / physiology
Brain / blood supply*
Cerebrovascular Circulation / physiology*
Data Interpretation, Statistical
Diffusion Magnetic Resonance Imaging*
Female
Humans
Image Interpretation, Computer-Assisted
Male
Microvessels / physiology
Predictive Value of Tests
Sensitivity and Specificity
Stroke / diagnosis*
Symptom Assessment / methods*
Time Factors
Grant Support
ID/Acronym/Agency:
K24 NS072272/NS/NINDS NIH HHS
Investigator
Investigator/Affiliation:
Steven Warach / ; Gregory Albers / ; Stephen Davis / ; Geoffrey Donnan / ; Marc Fisher / ; Anthony Furlan / ; James Grotta / ; Werner Hacke / ; Dong- Wha Kang / ; Chelsea Kidwell / ; Walter Koroshetz / ; Kennedy R Lees / ; Michael Lev / ; David S Liebeskind / ; A Gregory Sorensen / ; Vincent Thijs / ; Götz Thomalla / ; Joanna Wardlaw / ; Max Wintermark /

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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