Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification.

ABSTRACT:

Purpose

Accurately quantifying the rupture risk of unruptured intracranial aneurysms (UIAs) is crucial for guiding treatment decisions and remains an unmet clinical challenge. Computational Flow Dynamics and morphological measurements have been shown to differ between ruptured and unruptured aneurysms. It is not clear if these provide any additional information above routinely available clinical observations or not. Therefore, this study investigates whether incorporating image-derived features into the established PHASES score can improve the classification of aneurysm rupture status.

Methods

A cross-sectional dataset of 170 patients (78 with ruptured aneurysm) was used. Computational fluid dynamics (CFD) and shape analysis were performed on patients' images to extract addi

SUBMITTER: Benemerito I 

PROVIDER: S-EPMC11757871 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature