Investigating the role of blood models in predicting rupture status of intracranial aneurysms.

ABSTRACT: Purpose. Selecting patients with high-risk intracranial aneurysms (IAs) is of clinical importance. Recent work in machine learning-based (ML) predictive modeling has demonstrated that lesion-specific hemodynamics within IAs can be combined with other information to provide critical insights for assessing rupture risk. However, how the adoption of blood rheology models (i.e., Newtonian and Non-Newtonian blood models) may influence ML-based predictive modeling of IA rupture risk has not been investigated.Methods and Materials.In this study, we conducted transient CFD simulations using Newtonian and non-Newtonian rheology (Carreau-Yasuda [CY]) models on a large cohort of 'patient-specific' IA geometries (>100) under pulsatile flow conditions to investigate how each blood model m

SUBMITTER: Lyu Z 

PROVIDER: S-EPMC12747726 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature