Personalizing flow-diverter intervention for cerebral aneurysms: from computational hemodynamics to biochemical modeling.

This paper presents the computational modeling of a variety of flow-diverting stents, deployed in a number of patient-specific aneurysm geometries. We consider virtual device deployment and hemodynamics as well as thrombus formation, with the scope to assess pre-operatively the efficacy of specific devices in treating particular aneurysms. An algorithm based on a linear and torsional spring analogy is developed for the fast virtual deployment of stents and similar minimally invasive devices in patient-specific vessel geometries. The virtual deployment algorithm is used to accurately deploy a total of four stent designs in three aneurysm geometries. A variety of different flow-diverting stent designs, representing the commercially available and the entirely novel, are presented, varying in both mesh design and porosity. Transient computational hemodynamics simulations are performed on multiple patient-specific geometries to predict the reduction in aneurysm inflow after the deployment of each device. Further, a thrombosis initiation and growth model is implemented, coupled with the hemodynamic computations. Hemodynamic simulations show large variations in flow reduction between devices and across different aneurysm geometries. The industry standard of flow-diverters with 70% porosity, assumed to offer the best compromise in flexibility and flow reduction, is challenged in at least one aneurysm geometry.