Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke.

ABSTRACT:

Objective

To develop and validate a model based on the radiomics features of the infarct areas on non-contrast-enhanced CT to predict hemorrhagic transformation (HT) in acute ischemic stroke.

Materials and methods

A total of 118 patients diagnosed with acute ischemic stroke in two centers from January 2019 to February 2022 were included. The radiomics features of infarcted areas on non-contrast-enhanced CT were extracted using 3D-Slicer. A univariate analysis and the least absolute shrinkage and selection operator (LASSO) were used to select features, and the radiomics score (Rad-score) was then constructed. The predictive model of HT was constructed by analyzing the Rad-score and clinical and imaging features in the training cohort, and it was verified in the validation coh

SUBMITTER: Xie G 

PROVIDER: S-EPMC9533555 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature