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MR diffusion-weighted imaging and outcome prediction after ischemic stroke.

P J Hand1, J M Wardlaw, C S Rivers

  • 1Division of Clinical Neurosciences, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK.

Neurology
|March 10, 2006
PubMed
Summary

Diffusion-weighted imaging (DWI) does not predict stroke outcomes in a broad patient range. Age and stroke severity are key predictors, suggesting DWI may not reduce trial sample sizes for functional outcome prediction.

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Area of Science:

  • Neurology
  • Radiology
  • Clinical Trials

Background:

  • Diffusion-weighted imaging (DWI) detects acute ischemic stroke lesions early.
  • DWI's utility in predicting stroke outcomes and reducing trial sample sizes remains debated due to conflicting prior studies.

Purpose of the Study:

  • To investigate if DWI lesion characteristics independently predict functional outcomes in diverse acute stroke patients.
  • To assess the predictive value of DWI parameters and a specific "Three-Item Scale" for 3-month outcomes.

Main Methods:

  • Recruited hospital-admitted patients with suspected stroke of varying severity.
  • Assessed stroke severity using the NIH Stroke Scale (NIHSS) and performed early brain DWI.
  • Evaluated 3-month outcomes using the modified Rankin Scale and logistic regression analysis.

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Main Results:

  • Age and stroke severity (NIHSS) were the only independent predictors of 3-month outcome.
  • DWI lesion volume, apparent diffusion coefficient, and the "Three-Item Scale" did not independently predict outcomes.
  • DWI may predict outcomes only in severe cortical ischemic strokes, contrary to broader findings.

Conclusions:

  • Diffusion-weighted imaging (DWI) does not offer independent predictive value for functional outcomes in a wide spectrum of acute stroke patients.
  • DWI is unlikely to reduce sample sizes in acute stroke trials focused on functional outcomes, particularly with modest treatment effects.
  • Clinical variables like age and stroke severity remain primary outcome predictors.