DWI intensity values predict FLAIR lesions in acute ischemic stroke

• Published in: PloS one Vol. 9; no. 3; p. e92295
• Main Authors: Madai, Vince I, Galinovic, Ivana, Grittner, Ulrike, Zaro-Weber, Olivier, Schneider, Alice, Martin, Steve Z, von Samson-Himmelstjerna, Federico C, Stengl, Katharina L, Mutke, Matthias A, Moeller-Hartmann, Walter, Ebinger, Martin, Fiebach, Jochen B, Sobesky, Jan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21-03-2014; Public Library of Science (PLoS)
• Subjects: Aged; Aged, 80 and over; Automation; Biology and Life Sciences; Biomarkers; Correlation; Correlation analysis; Councils; Diffusion Magnetic Resonance Imaging - methods; Driving while intoxicated; Epidemiology; Female; Humans; Ischemia; Lesions; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Medical research; Medicine and Health Sciences; Middle Aged; Neurology; NMR; Nuclear magnetic resonance; Patients; Performance prediction; Regression analysis; Regression models; Retrospective Studies; Stroke; Stroke - diagnosis; Thrombolysis; Time Factors; Germany
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0092295

In acute stroke, the DWI-FLAIR mismatch allows for the allocation of patients to the thrombolysis window (<4.5 hours). FLAIR-lesions, however, may be challenging to assess. In comparison, DWI may be a useful bio-marker owing to high lesion contrast. We investigated the performance of a relative DWI signal intensity (rSI) threshold to predict the presence of FLAIR-lesions in acute stroke and analyzed its association with time-from-stroke-onset.
In a retrospective, dual-center MR-imaging study we included patients with acute stroke and time-from-stroke-onset ≤12 hours (group A: n = 49, 1.5T; group B: n = 48, 3T). DW- and FLAIR-images were coregistered. The largest lesion extent in DWI defined the slice for further analysis. FLAIR-lesions were identified by 3 raters, delineated as regions-of-interest (ROIs) and copied on the DW-images. Circular ROIs were placed within the DWI-lesion and labeled according to the FLAIR-pattern (FLAIR+ or FLAIR-). ROI-values were normalized to the unaffected hemisphere. Adjusted and nonadjusted receiver-operating-characteristics (ROC) curve analysis on patient level was performed to analyze the ability of a DWI- and ADC-rSI threshold to predict the presence of FLAIR-lesions. Spearman correlation and adjusted linear regression analysis was performed to assess the relationship between DWI-intensity and time-from-stroke-onset.
DWI-rSI performed well in predicting lesions in FLAIR-imaging (mean area under the curve (AUC): group A: 0.84; group B: 0.85). An optimal mean DWI-rSI threshold was identified (A: 162%; B: 161%). ADC-maps performed worse (mean AUC: A: 0.58; B: 0.77). Adjusted regression models confirmed the superior performance of DWI-rSI. Correlation coefficents and linear regression showed a good association with time-from-stroke-onset for DWI-rSI, but not for ADC-rSI.
An easily assessable DWI-rSI threshold identifies the presence of lesions in FLAIR-imaging with good accuracy and is associated with time-from-stroke-onset in acute stroke. This finding underlines the potential of a DWI-rSI threshold as a marker of lesion age.