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Prediction of hemorrhagic transformation in acute ischemic stroke using texture analysis of postcontrast T1‐weighted MR images
Author(s) -
Kassner Andrea,
Liu Fang,
Thornhill Rebecca E.,
Tomlinson George,
Mikulis David J.
Publication year - 2009
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.21940
Subject(s) - medicine , receiver operating characteristic , stroke (engine) , acute stroke , contrast (vision) , texture (cosmology) , nuclear medicine , radiology , artificial intelligence , image (mathematics) , mechanical engineering , tissue plasminogen activator , computer science , engineering
Abstract Purpose: To test the hypothesis that texture analysis of postcontrast T1‐weighted MR images will predict hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) with better accuracy than visual evidence of contrast‐enhancement (VE). Materials and Methods: Thirty‐four AIS patients were examined within 3.5 ± 1.5 h after stroke. T1‐weighted MR images were acquired 19 ± 7 min postcontrast injection. HT was determined by follow‐up imaging at 24–72 h. Postcontrast images were evaluated for VE. Four second‐order textural features were extracted ( f1 , f2 , f3 , and f9 ) for each patient. Receiver operating characteristic (ROC) curves were constructed for VE and for textural features, with HT as the outcome measure. Results: The f2 for HT patients (n = 12) was significantly lower than in non‐HT patients (1058 ± 356 versus 1568 ± 527; P = 0.005); the converse was true for f3 (0.67 ± 0.12 versus 0.54 ± 0.13; P = 0.007). ROC analysis indicated that the f2 and f3 textural features were the only two significant predictors of HT ( P = 0.0018 and P = 0.0042). The addition of VE to either f2 or f3 did not result in a significant improvement in accuracy. Conclusion: Texture analysis of postcontrast T1‐weighted images may be superior to visual evidence of enhancement for the prediction of HT. J. Magn. Reson. Imaging 2009;30:933–941. © 2009 Wiley‐Liss, Inc.

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