1. Defining Ischemic Core in Acute Ischemic Stroke Using CT Perfusion: A Multiparametric Bayesian-Based Model.
- Author
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Tadayon, E, Wheelwright, D, Metry, A, Fifi, J, Tuhrim, S, De Leacy, R, Doshi, A, Chang, H, Mocco, J, and Nael, Kambiz
- Subjects
Aged ,Aged ,80 and over ,Bayes Theorem ,Brain Ischemia ,Cerebral Arteries ,Cerebral Infarction ,Cerebrovascular Circulation ,Female ,Humans ,Image Processing ,Computer-Assisted ,Magnetic Resonance Imaging ,Male ,Middle Aged ,Perfusion Imaging ,Stroke ,Thrombectomy ,Tomography ,X-Ray Computed ,Treatment Outcome - Abstract
BACKGROUND AND PURPOSE: The Bayesian probabilistic method has shown promising results to offset noise-related variability in perfusion analysis. Using CTP, we aimed to find optimal Bayesian-estimated thresholds based on multiparametric voxel-level models to estimate the ischemic core in patients with acute ischemic stroke. MATERIALS AND METHODS: Patients with anterior circulation acute ischemic stroke who had baseline CTP and achieved successful recanalization were included. In a subset of patients, multiparametric voxel-based models were constructed between Bayesian-processed CTP maps and follow-up MRIs to identify pretreatment CTP parameters that were predictive of infarction using robust logistic regression. Subsequently CTP-estimated ischemic core volumes from our Bayesian model were compared against routine clinical practice oscillation singular value decomposition-relative cerebral blood flow
- Published
- 2019