American Journal of Neuroradiology 24:1869-1875, October 2003
© 2003 American Society of Neuroradiology
BRAIN
Correlation of Early Dynamic CT Perfusion Imaging with Whole-Brain MR Diffusion and Perfusion Imaging in Acute Hemispheric Stroke
a Department of Radiology, Duke University Medical Center, Durham, NC
b Department of Community and Family Medicine, Duke University Medical Center, Durham, NC
c Department of Medicine, Division of Neurology, Duke University Medical Center, Durham, NC
d Division of Neuroradiology, Massachusetts General Hospital, Boston, University Hospital, Lausanne, Switzerland
e Department of Diagnostic and Interventional Radiology, University Hospital, Lausanne, Switzerland
f Department of Diagnostic and Interventional Radiology, Friedrich-Schiller University, Jena, Germany
g Imaging Research Laboratories, John P. Robarts Research Institute, London, Ontario, Canada
Address reprint requests to James D. Eastwood, MD, Box 3808, Duke University Medical Center, Durham, NC 27710-3808
BACKGROUND AND PURPOSE: Compared with MR imaging, dynamic CT perfusion imaging covers only a fraction of the whole brain. An important assumption is that CT perfusion abnormalities correlate with total ischemic volume. The purpose of our study was to measure the degree of correlation between abnormalities seen on CT perfusion scans and the volumes of abnormality seen on MR diffusion and perfusion images in patients with acute large-vessel stroke.
METHODS: Fourteen patients with acute hemispheric stroke symptoms less than 12 hours in duration were studied with single-slice CT perfusion imaging and multislice MR diffusion and perfusion imaging. CT and MR perfusion studies were completed within 2.5 hours of one another (mean, 77 minutes) and were reviewed independently by two neuroradiologists. Hemodynamic parameters included cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Extents of abnormality on images were compared by using Kendall correlation.
RESULTS: Statistically significant correlation was found between CT-CBF and MR-CBF abnormalities (
= 0.60, P = .003) and CT-MTT and MR-MTT abnormalities ( = 0.65, P = .001). Correlation of CT-CBV with MR-CBV approached significance ( = 0.39, P = .06). Extent of initial hyperintensity on diffusion-weighted images correlated best with extent of MR-CBV abnormality ( = 0.69, P = .001), extent of MR-MTT abnormality ( = 0.67, P = .002), and extent of CT-CBV abnormality ( = 0.47, P = .02).
CONCLUSION: Good correlation was seen between CT and MR for CBF and MTT abnormalities. It remains uncertain whether CT perfusion CBV abnormalities correspond well to whole-brain abnormalities.
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