Functional Cluster Analysis of CT Perfusion Maps: A New Tool for Diagnosis of Acute Stroke? |
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Authors: | Christian Baumgartner Ph.D. Kurt Gautsch M.D. Christian Böhm Ph.D. Stephan Felber M.D. |
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Affiliation: | (1) Research Group for Biomedical Data Mining, Institute for Information Systems, University for Health Sciences, Medical Informatics and Technology, Eduard Wallnöfer Zentrum 1, A-6060 Hall in Tirol, Austria;(2) Department for Radiology II, Innsbruck Medical University, Anichstrasse 35, A-6020 Innsbruck, Austria;(3) Institute for Computer Science, University of Munich, Oettingenstrasse 67, D-80538 Munich, Germany |
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Abstract: | CT perfusion imaging constitutes an important contribution to the early diagnosis of acute stroke. Cerebral blood flow (CBF), cerebral blood volume (CBV) and time-to-peak (TTP) maps are used to estimate the severity of cerebral damage after acute ischemia. We introduce functional cluster analysis as a new tool to evaluate CT perfusion in order to identify normal brain, ischemic tissue and large vessels. CBF, CBV and TTP maps represent the basis for cluster analysis applying a partitioning (k-means) and density-based (density-based spatial clustering of applications with noise, DBSCAN) paradigm. In patients with transient ischemic attack and stroke, cluster analysis identified brain areas with distinct hemodynamic properties (gray and white matter) and segmented territorial ischemia. CBF, CBV and TTP values of each detected cluster were displayed. Our preliminary results indicate that functional cluster analysis of CT perfusion maps may become a helpful tool for the interpretation of perfusion maps and provide a rapid means for the segmentation of ischemic tissue. |
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Keywords: | Computed tomography perfusion imaging brain infarction cluster analysis |
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