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Brain Advance Access published online on August 3, 2006

Brain, doi:10.1093/brain/awl183
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© The Author (2006). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received January 14, 2006
Revised June 2, 2006
Accepted June 9, 2006

Article

Characterizing physiological heterogeneity of infarction risk in acute human ischaemic stroke using MRI

Ona Wu 1 *, Søren Christensen 2, Niels Hjort 2, Rick M. Dijkhuizen 3, Thomas Kucinski 4, Jens Fiehler 4, Götz Thomalla 5, Joachim Röther 5, and Leif Østergaard 2

1 Center for Functionally Integrative Neuroscience, Department of Neuroradiology, Århus University Hospital, Århus C, Denmark; Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
2 Center for Functionally Integrative Neuroscience, Department of Neuroradiology, Århus University Hospital, Århus C, Denmark
3 Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
4 Department of Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
5 Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

* To whom correspondence should be addressed.
Ona Wu, E-mail: ona{at}pet.auh.dk


   Abstract

Viable tissues at risk of infarction in acute stroke patients have been hypothesized to be detectable as volumetric mismatches between lesions on perfusion-weighted (PWI) and diffusion-weighted magnetic resonance imaging (DWI). Because tissue response to ischaemic injury and to therapeutic intervention is tissue- and patient-dependent, changes in infarct progression due to treatment may be better detected with voxel-based methods than with volumetric mismatches. Acute DWI and PWI were combined using a generalized linear model (GLM) to predict infarction risk on a voxel-wise basis for patients treated either with non-thrombolytic (Group 1; n = 11) or with thrombolytic therapy (Group 2; n = 27). Predicted infarction risk for both groups was evaluated in four ipsilateral regions of interest: tissue acutely abnormal on DWI (Core), tissue acutely abnormal on PWI but normal on DWI that either infarcts (Recruited) or does not (Salvaged), and tissue normal on both DWI and PWI that does not infarct (Normal) by follow-up imaging ≥ 5 days. The performance of the models was significantly reduced for the thrombolysed group compared with the group receiving standard treatment, suggesting an alteration in natural progression of the ischaemic cascade. Average GLM-predicted infarction risk values in the four regions were different from one another for both groups. GLM-predicted infarction risk in Salvaged tissue was significantly higher (P = 0.02) for thrombolysed patients than for non-thrombolysed patients, suggesting that thrombolysis rescued tissue with higher infarction risk than typically measured in tissue that spontaneously recovered. The observed spatial heterogeneity of GLM-predicted infarction risk values probably reflects the varying degrees of tissue injury and salvageability that exist after stroke. MRI-based algorithms may therefore provide a more sensitive means for monitoring therapeutic effects on a voxel-wise basis.

Keywords: mathematical modelling; cerebral ischaemia; magnetic resonance imaging; thrombolytic therapy; outcome measures.
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