Segmentation of the Hyperdense Artery Sign on Noncontrast CT in Ischemic Stroke Using Artificial Intelligence.

ABSTRACT:

Background and purpose

We developed and validated an automated hyperdense artery sign (HAS) segmentation algorithm for the distal internal carotid artery and middle cerebral artery on noncontrast brain computed tomography (NCCT) using a multicenter dataset with independent annotation performed by two experts.

Methods

For training and external validation, we included patients with ischemic stroke who underwent concurrent NCCT and CT angiography between May 2011 and December 2022 at six hospitals and one hospital, respectively. For clinical validation, nonoverlapping patients admitted within 24 hours of onset were consecutively included between December 2020 and April 2023 from six hospitals. The model was trained using the 2D U-Net deep-learning architecture with manual annot

SUBMITTER: Kim PE 

PROVIDER: S-EPMC12303688 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature