CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke.


Journal Article

PURPOSE: To measure mean cerebral blood flow (CBF) in ischemic and nonischemic territories and in low-attenuation regions in patients with acute stroke by using deconvolution-derived hemodynamic imaging. MATERIALS AND METHODS: Twelve patients with acute middle cerebral artery stroke and 12 control patients were examined by using single-section computed tomography (CT) perfusion scanning. Analysis was performed with a deconvolution-based algorithm. Comparisons of mean CBF, cerebral blood volume (CBV), and mean transit time (MTT) were determined between hemispheres in all patients and between low- and normal-attenuation regions in patients with acute stroke. Two independent readers examined the images for extent of visually apparent regional perfusion abnormalities. The data were compared with extent of final infarct in seven patients with acute stroke who underwent follow-up CT or magnetic resonance imaging. RESULTS: Significant decreases in CBF (-50%, P =.001) were found in the affected hemispheres of patients with acute stroke. Significant changes in CBV (-26%, P =.03) and MTT (+111%, P =.004) were also seen. Significant alterations in perfusion were also seen in low- compared with normal-attenuation areas. Pearson correlation between readers for extent of CBF abnormality was 0.94 (P =.001). Intraobserver variation was 8.9% for CBF abnormalities. CONCLUSION: Deconvolution analysis of CT perfusion data is a promising method for evaluation of cerebral hemodynamics in patients with acute stroke.

Full Text

Duke Authors

Cited Authors

  • Eastwood, JD; Lev, MH; Azhari, T; Lee, T-Y; Barboriak, DP; Delong, DM; Fitzek, C; Herzau, M; Wintermark, M; Meuli, R; Brazier, D; Provenzale, JM

Published Date

  • January 2002

Published In

Volume / Issue

  • 222 / 1

Start / End Page

  • 227 - 236

PubMed ID

  • 11756730

Pubmed Central ID

  • 11756730

International Standard Serial Number (ISSN)

  • 0033-8419

Digital Object Identifier (DOI)

  • 10.1148/radiol.2221010471


  • eng

Conference Location

  • United States