Prediction of bleb formation in intracranial aneurysms using machine learning models based on aneurysm hemodynamics, geometry, location, and patient population.

ABSTRACT:

Background

Bleb presence in intracranial aneurysms (IAs) is a known indication of instability and vulnerability.

Objective

To develop and evaluate predictive models of bleb development in IAs based on hemodynamics, geometry, anatomical location, and patient population.

Methods

Cross-sectional data (one time point) of 2395 IAs were used for training bleb formation models using machine learning (random forest, support vector machine, logistic regression, k-nearest neighbor, and bagging). Aneurysm hemodynamics and geometry were characterized using image-based computational fluid dynamics. A separate dataset with 266 aneurysms was used for model evaluation. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), true positive

SUBMITTER: Salimi Ashkezari SF 

PROVIDER: S-EPMC9023610 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature