Computational Fluid Dynamics Using a Porous Media Setting Predicts Outcome after Flow-Diverter Treatment

Abstract

Knowledge about predictors of the outcome of flow-diverter treatment is limited. The aim of this study was to predict the angiographic occlusion status after flow-diverter treatment with computational fluid dynamics using porous media modeling for decision-making in the treatment of large wide-neck aneurysms. A total of 27 patients treated with flow-diverter stents were retrospectively analyzed through computational fluid dynamics using pretreatment patient-specific 3D rotational angiography. These patients were classified into no-filling and contrast-filling groups based on the O'Kelly-Marotta scale. The patient characteristics, morphologic variables, and hemodynamic parameters were evaluated for understanding the outcomes of the flow-diverter treatment. The patient characteristics and morphologic variables were similar between the 2 groups. Flow velocity, wall shear stress, shear rate, modified aneurysmal inflow rate coefficient, and residual flow volume were significantly lower in the no-filling group. A novel parameter, called the normalized residual flow volume, was developed and defined as the residual flow volume normalized by the dome volume. The receiver operating characteristic curve analyses demonstrated that the normalized residual flow volume with an average flow velocity of ≥8.0 cm/s in the aneurysmal dome was the most effective in predicting the flow-diverter treatment outcomes. It was established in this study that the hemodynamic parameters could predict the angiographic occlusion status after flow-diverter treatment.