Probability maps classify ischemic stroke regions more accurately than CT perfusion summary maps.

ABSTRACT:

Objectives

To compare single parameter thresholding with multivariable probabilistic classification of ischemic stroke regions in the analysis of computed tomography perfusion (CTP) parameter maps.

Methods

Patients were included from two multicenter trials and were divided into two groups based on their modified arterial occlusive lesion grade. CTP parameter maps were generated with three methods-a commercial method (ISP), block-circulant singular value decomposition (bSVD), and non-linear regression (NLR). Follow-up non-contrast CT defined the follow-up infarct region. Conventional thresholds for individual parameter maps were established with a receiver operating characteristic curve analysis. Probabilistic classification was carried out with a logistic regression model co

SUBMITTER: Peerlings D 

PROVIDER: S-EPMC9381605 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature