Evaluation of a Deep Learning Tool for Detecting Large Vessel Occlusion and Intracranial Hemorrhage on Noncontrast Computed Tomography Scans.

ABSTRACT:

Background

The purpose of this study is to assess the accuracy of automated artificial intelligence (AI) deep-learning-based modules in predicting suspected intracranial hemorrhage (ICH) or anterior circulation large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) studies.

Methods

We conducted a multicenter international retrospective cohort study, involving 6 stroke centers from the United States and Europe. We included patients in whom an acute stroke was suspected on admission and who underwent an NCCT and a CT angiography when ICH was not observed. Two neuroradiologists and a third one in case of discrepancies retrospectively evaluated all images and established the presence of ICH on NCCT and LVO on computed tomography angiography (ground truth). All NC

SUBMITTER: Urra X 

PROVIDER: S-EPMC12697655 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature