Variability of Vascular Territory in Stroke
- 1 June 1995
- journal article
- research article
- Published by Wolters Kluwer Health in Stroke
- Vol. 26 (6) , 942-945
- https://doi.org/10.1161/01.str.26.6.942
Abstract
Background and Purpose We investigated the efficacy and feasibility of determining infarction mechanisms and underlying embolic or hemodynamic pathologies from topographical patterns of ischemic damage seen on computed tomography or magnetic resonance imaging. Methods Infarction patterns from 22 patients with ipsilateral severe, hemodynamically relevant carotid stenosis (n=6) or occlusions (n=16) were superimposed, using two matching algorithms, onto maps showing the variability of the cerebral vascular territories as determined from recent cadaver studies. These images were used to classify the infarctions as border-zone or territorial for the two conditions of minimal and maximal middle cerebral artery distribution. Results Classification of infarction patterns resulting from carotid stenosis was independent of the territorial extension map chosen: 83% were classified as territorial. Classification of patterns due to carotid occlusion, however, varied highly; 81% of infarctions were considered territorial when the maximal middle cerebral artery distribution map was used, whereas only 19% were when the minimal territorial extension map was used. Conclusions The current concept that stroke mechanisms can be inferred from the interpretation of stroke patterns seen on computed tomography scans or magnetic resonance imaging is significantly confounded by the demonstrated variability in intracranial vascular distributions. Stroke pattern interpretation appears to be highly dependent on the in vivo vascular tree of the individual, which is unknown to the examiner. This calls into question the reliability of classifying infarction patterns as border-zone or territorial. Determination of true underlying stroke mechanisms requires a comprehensive approach and cannot be based solely on stroke pattern interpretation.Keywords
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