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(Stroke. 2007;38:194.)
© 2007 American Heart Association, Inc.
Research Reports |
From the Athinoula A. Martinos Center for Biomedical Imaging (N.M.M., H.A., M.W.Z., C.J.L., A.G.S.), Department of Radiology, Massachusetts General Hospital and the Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Boston, Mass; the Stroke Service (H.A., A.B.S., W.J.K.), Department of Neurology, Massachusetts General Hospital, Boston, Mass; and the Departments of Clinical Radiology and Neurology (J.O.K., Y.L., J.N.), Kuopio University Hospital, Kuopio, Finland; and Functional Brain Imaging Unit, Helsinki Brain Research Center, Finland; Centre for Military Medicine, Finnish Defence Forces, Helsinki, Finland; Department of Diagnostic Radiology, University of Turku, Finland (H.J.A.).
Correspondence to A. Gregory Sorensen, MD, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Bldg 149, 13th St (2301), Charlestown, MA 02129. E-mail sorensen{at}nmr.mgh.harvard.edu
Background and Purpose— The severity of the neurological deficit after ischemic stroke is moderately correlated with infarct volume. In the current study, we sought to quantify the impact of location on neurological deficit severity and to delineate this impact from that of volume.
Methods— We developed atlases consisting of location-weighted values indicating the relative importance in terms of neurological deficit severity for every voxel of the brain. These atlases were applied to 80 first-ever ischemic stroke patients to produce estimates of clinical deficit severity. Each patient had an MRI and National Institutes of Health Stroke Scale (NIHSS) examination just before or soon after hospital discharge. The correlation between the location-based deficit predictions and measured neurological deficit (NIHSS) scores were compared with the correlation obtained using volume alone to predict the neurological deficit.
Results— Volume-based estimates of neurological deficit severity were only moderately correlated with measured NIHSS scores (r=0.62). The combination of volume and location resulted in a significantly better correlation with clinical deficit severity (r=0.79, P=0.032).
Conclusions— The atlas methodology is a feasible way of integrating infarct size and location to predict stroke severity. It can estimate stroke severity better than volume alone.
Key Words: infarcts magnetic resonance imaging models outcome statistical stroke
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