Hemodynamic markers: CFD-based prediction of cerebral aneurysm rupture risk

Predicting which intracranial aneurysms will progress to rupture remains a major unmet need in neurosurgical practice. Conventional imaging provides limited insight into the hemodynamic forces acting on the aneurysm wall, yet these forces play a central role in its long-term stability. To address this limitation, we developed a patient-specific computational pipeline capable of converting routine MRA data into detailed maps of aneurysmal blood-flow dynamics. The tool reconstructs vascular geometry directly from imaging and quantifies hemodynamic biomarkers associated with rupture risk, enabling clinicians to access physiologically meaningful information that is not visible on structural imaging alone. Using this framework, we analyzed six aneurysm cases with known longitudinal outcomes to determine whether baseline flow conditions differed between lesions that later ruptured and those that remained stable. High-resolution CFD simulations were used to compute wall shear stress (WSS), time-averaged WSS (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP). Distinct hemodynamic patterns emerged: aneurysms that remained stable showed higher WSS/TAWSS and lower OSI/RRT, whereas aneurysms that ultimately ruptured exhibited low shear environments, stronger oscillatory flow, and greater endothelial activation. Regions with elevated OSI and RRT frequently coincide with vortex cores, suggesting localized flow disturbances that may serve as early indicators of wall vulnerability. These results demonstrate that clinically acquired MRA, when paired with a dedicated computational tool, can reveal baseline hemodynamic signatures predictive of future aneurysm behavior. This approach offers a noninvasive, imaging-driven method to support clinical decision-making, refine surveillance strategies, and improve individualized management of patients with intracranial aneurysms.