Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.

ABSTRACT:

Purpose

Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (CTA) images.

Methods

The clinical data of 1041 patients with 1227 aneurysms were retrospectively analyzed from August 2011 to May 2021. Patients with aneurysms were divided into unstable (ruptured, evolving and symptomatic aneurysms) and stable (fortuitous, nonevolving and asymptomatic aneurysms) groups and randomly divided into training (833 patients with 991 aneurysms) and internal validation (208 patients with 236 aneurysms) sets. One hundred and ninety-seven patients with 229 aneurysms from another hospital were included in the

SUBMITTER: Zeng L 

PROVIDER: S-EPMC11870988 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature