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Identifying lesion growth with MR imaging in acute ischemic stroke
Authors:Bristow Michael S  Poulin Brett W  Simon Jessica E  Hill Michael D  Kosior Jayme C  Coutts Shelagh B  Frayne Richard  Mitchell J Ross  Demchuk Andrew M
Institution:Department of Radiology, University of Calgary, Calgary, Alberta, Canada. msbristo@ucalgary.ca
Abstract:PURPOSE: To determine whether different MR diffusion- and perfusion-weighted imaging (DWI and PWI) parameters are important in distinguishing lesion growth from the acute lesion and from oligemia. MATERIALS AND METHODS: MR DWI and PWI were acquired from thirteen patients. We defined three regions: (i) LESION - intersection of acute and final lesions, (ii) GROWTH - portion of final lesion not part of acute lesion, and (iii) OLIGEMIA - region of perfusion abnormality not part of either the acute or final lesions. We used logistic regression modeling to distinguish GROWTH from LESION and from OLIGEMIA on a voxel-wise basis using DWI- and PWI-based parameters. Final models were selected based on the Wald statistic and validated by cross-validation using the mean (+/- standard deviation) area under the curve (AUC) from receiver operating characteristic analysis. RESULTS: The final model for differentiating GROWTH from LESION included DWI, the apparent diffusion coefficient (ADC), cerebral blood flow (CBF) and tissue type (AUC = 0.939 +/- 0.028). The final model for differentiating GROWTH from OLIGEMIA included DWI, ADC, CBF, and time-to-peak (AUC = 0.793 +/- 0.106). CONCLUSION: Different MR parameters are important in differentiating lesion growth from acute lesion and from oligemia in acute ischemic stroke.
Keywords:diffusion weighted MRI  perfusion weighted MRI  acute stroke  logistic regression
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