Abstract
Objective: This study investigates morphological, hemodynamic and structural mechanical factors influencing aneurysm rupture behavior, specifically focusing on Middle Cerebral Artery (MCA) and Anterior Communicating Artery (ACOMM) aneurysms, using computational fluid dynamics (CFD) and fluid-structure interaction (FSI) analyses.
Methods: Data from 116 patients with aneurysms located in the MCA and ACOMM, including 81 ruptured and 35 stable aneurysms. Aneurysms were modeled with FSI methods to examine key parameters: aneurysm angle, wall shear stress, and equivalent Mises stress as well as additional parameters. Statistical analyses were conducted using the Mann-Whitney U-test to identify significant differences in these parameters between the two locations in stable and ruptured aneurysms. In a further step univariate and multivariate regression analysis was performed.
Results: Results indicated no significant differences in the assessed parameters between ruptured MCA and ACOMM aneurysms. However, stable ACOMM aneurysms exhibited a larger aneurysm angle, lower wall equivalent stress as well as lower ratio of maximum WSS in the aneurysms and the parent vessel when compared to MCA aneurysms, indicating that ACOMM aneurysms may rupture at lower stresses possibly due to their higher aneurysm angle. Regression analysis underlines the statistical power of aneurysm angle.
Conclusions: These findings highlight morphological and hemodynamic differences in stable aneurysms across MCA and ACOMM locations. Stable MCA aneurysms appear to tolerate higher wall stress values compared to ACOMM aneurysms, leading to greater susceptibility to rupture in ACOMM aneurysms at stress levels where MCA aneurysms can remain stable. This study underscores the importance of considering morphological, hemodynamic and structural mechanical factors as well as the distinction between stable and ruptured aneurysms, to improve the accuracy of rupture risk.
Methods: Data from 116 patients with aneurysms located in the MCA and ACOMM, including 81 ruptured and 35 stable aneurysms. Aneurysms were modeled with FSI methods to examine key parameters: aneurysm angle, wall shear stress, and equivalent Mises stress as well as additional parameters. Statistical analyses were conducted using the Mann-Whitney U-test to identify significant differences in these parameters between the two locations in stable and ruptured aneurysms. In a further step univariate and multivariate regression analysis was performed.
Results: Results indicated no significant differences in the assessed parameters between ruptured MCA and ACOMM aneurysms. However, stable ACOMM aneurysms exhibited a larger aneurysm angle, lower wall equivalent stress as well as lower ratio of maximum WSS in the aneurysms and the parent vessel when compared to MCA aneurysms, indicating that ACOMM aneurysms may rupture at lower stresses possibly due to their higher aneurysm angle. Regression analysis underlines the statistical power of aneurysm angle.
Conclusions: These findings highlight morphological and hemodynamic differences in stable aneurysms across MCA and ACOMM locations. Stable MCA aneurysms appear to tolerate higher wall stress values compared to ACOMM aneurysms, leading to greater susceptibility to rupture in ACOMM aneurysms at stress levels where MCA aneurysms can remain stable. This study underscores the importance of considering morphological, hemodynamic and structural mechanical factors as well as the distinction between stable and ruptured aneurysms, to improve the accuracy of rupture risk.
Original language | English |
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Article number | 108335 |
Number of pages | 7 |
Journal | Journal of Stroke and Cerebrovascular Diseases |
Volume | 34 |
Issue number | 7 |
DOIs | |
Publication status | Published - Jul 2025 |
Fields of science
- 211912 Product design
- 104019 Polymer sciences
- 205 Materials Engineering
- 604008 Design
- 205015 Composites
- 302051 Neurosurgery
- 301405 Neuropathology
- 302052 Neurology
- 301114 Cell biology
JKU Focus areas
- Sustainable Development: Responsible Technologies and Management
- Digital Transformation