Predicting Language Improvement in Acute Stroke Patients Presenting with Aphasia: A Multivariate Logistic Model Using Location-Weighted Atlas-Based Analysis of Admission CT Perfusion Scans

Abstract

An imaging-based location-weighted multivariate model was developed to predict early language improvement of patients with aphasia by using admission data collected within 9 hours of stroke onset. This pilot model should be validated in a larger, prospective study; however, the semiautomated atlas-based analysis of brain CTP, along with the statistical approach, could be generalized for prediction of other outcome measures in patients with stroke.