Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters.

Abstract

Introduction:A multitude of approaches have been postulated for assessing the risk of intracranial aneurysm rupture. However, the amount of potential predictive factors is not applicable in clinical practice and they are rejected in favor of the more practical PHASES score. For the subgroup of multiple intracranial aneurysms (MIAs), the PHASES score might severely underestimate the rupture risk, as only the aneurysm with the largest diameter is considered for risk evaluation.Methods:In this study, we investigated 38 patients harboring a total number of 87 MIAs with respect to their morphological and hemodynamical characteristics. For the determination of the best suited parameters regarding their predictive power for aneurysm rupture, we conducted three phases of statistical evaluation. The statistical analysis aimed to identify parameters that differ significantly between ruptured and unruptured aneurysms, show smallest possible correlations among each other and have a high impact on rupture risk prediction.Results:Significant differences between ruptured and unruptured aneurysms were found in 16 out of 49 parameters. The lowest correlation were found for gamma, aspect ratio (AR1), aneurysm maximal relative residence time (Aneurysm_RRT_max) and aneurysm mean relative residence time. The data-driven parameter selection yielded a significant correlation of only two parameters (AR1 and the Aneurysm_RRT_max) with rupture state (area under curve = 0.75).Conclusion:A high number of established morphological and hemodynamical parameters seem to have no or only low effect on prediction of aneurysm rupture in patients with MIAs. For best possible rupture risk assessment of patients with MIAs, only the morphological parameter AR1 and the hemodynamical parameter Aneurysm_RRT_max need to be included in the prediction model.