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A predictive hemodynamic model based on risk factors for ruptured mirror aneurysms
Sheng-Qi Hu1, Ru-Dong Chen1, Wei-Dong Xu1
1Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Frontiers in Neurology
|September 26, 2022
Summary
Low shear area, mean combined hemodynamic parameter, and wall shear stress gradient ratio are key hemodynamic risk factors for intracranial aneurysm rupture. A new predictive model incorporating these factors can aid clinical evaluation.
Area of Science:
- Neurosurgery
- Medical Imaging
- Biomedical Engineering
Background:
- Intracranial aneurysms pose a significant risk of rupture, leading to potentially devastating outcomes.
- Identifying reliable risk factors for aneurysm rupture is crucial for effective patient management and treatment planning.
Purpose of the Study:
- To identify hemodynamic risk factors associated with intracranial aneurysm rupture.
- To develop and validate a predictive model for aneurysm rupture risk assessment.
Main Methods:
- Analysis of hemodynamic parameters in 91 pairs of ruptured mirror aneurysms.
- Conditional univariate and multivariate logistic regression to identify independent risk factors.
- Development of a predictive model and validation using a separate cohort of 189 aneurysms.
Main Results:
- Low shear area (LSA), mean combined hemodynamic parameter (CHP), and wall shear stress gradient (WSSG) ratio were identified as independent risk factors.
- A predictive model incorporating LSA, mean CHP, and WSSG ratio demonstrated good predictive performance (AUC 0.748 in development, 0.736 in validation).
- The model showed superior predictive ability compared to individual factors.
Conclusions:
- LSA, mean CHP (>0.087), and WSSG ratio (>893.180) are significant independent risk factors for intracranial aneurysm rupture.
- The developed predictive model offers a valuable tool for practical risk evaluation in clinical settings.
