Numerical simulation of individualized flow diversion cerebral aneurysms treatment

Abstract Flow diverter implantation has emerged as a highly effective treatment for cerebral aneurysms. However, the variability in patient‐specific vascular anatomy necessitates detailed pre‐operative planning to mitigate potential complications arising from standard, one‐size‐fits‐all devices. To address these challenges, robust predictive simulation tools are essential for optimizing flow diverter design and implantation strategies tailored to the unique characteristics of each patient's anatomy. This study focuses on developing an advanced numerical simulation tool for modeling the mechanical behavior of braided flow diverters during crimping and navigation through patient‐specific vasculature. Using isogeometric analysis (IGA) with NURBS‐based representations in LS‐Dyna, the intricate deformations of the flow diverter wires during catheter crimping are captured with high accuracy. The patient‐specific vessel geometries, derived from imaging data, are integrated into the model to account for variations in vascular structure, ensuring precise alignment and controlled navigation of the device. The navigation process relies on optimizing the central axis of the blood vessel to minimize torsional stress on the flow diverter, reducing the risk of device malfunction or failure during deployment. By incorporating patient‐specific information, such as vessel curvature and tortuosity, the simulation tool enables the prediction of potential issues, thus allowing for intervention planning that is tailored to individual anatomy. This patient‐specific approach enhances the safety and efficacy of flow diverter implantation and serves as a foundation for improved device design prior to prototype development.