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72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)
Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

06.06. - 09.06.2021

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Rupture risk assessment for multiple intracranial aneurysms – why there is no need for dozens of clinical, morphological and haemodynamic parameters

Assessment des Rupturrisikos von multiplen intrakraniellen Aneurysmen – warum es nicht notwendig ist, Dutzende von klinischen, morphologischen und hämodynamischen Parametern zu bestimmen

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  • presenting/speaker Belal Neyazi - Otto-von-Guericke University Magdeburg, Department of Neurosurgery, Magdeburg, Deutschland
  • Vanessa M. Swiatek - Otto-von-Guericke University Magdeburg, Department of Neurosurgery, Magdeburg, Deutschland
  • Martin Skalej - Otto-von-Guericke University Magdeburg, Magdeburg, Deutschland
  • Oliver Beuing - Otto-von-Guericke University Magdeburg, Magdeburg, Deutschland
  • Klaus-Peter Stein - Otto-von-Guericke University Magdeburg, Department of Neurosurgery, Magdeburg, Deutschland
  • Jörg Hattingen - KRH Klinikum Nordstadt, Institut für Radiologie, Hannover, Deutschland
  • Bernhard Preim - Otto-von-Guericke University Magdeburg, Department of Simulation and Graphics, Magdeburg, Deutschland; Research Campus STIMULATE, Magdeburg, Deutschland
  • Philipp Berg - Research Campus STIMULATE, Magdeburg, Deutschland; Otto-von-Guericke University Magdeburg, Department of Fluid Dynamics and Technical Flows, Magdeburg, Deutschland
  • Sylvia Saalfeld - Otto-von-Guericke University Magdeburg, Department of Simulation and Graphics, Magdeburg, Deutschland; Research Campus STIMULATE, Magdeburg, Deutschland
  • I. Erol Sandalcioglu - Otto-von-Guericke University Magdeburg, Department of Neurosurgery, Magdeburg, Deutschland

Deutsche Gesellschaft für Neurochirurgie. 72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie. sine loco [digital], 06.-09.06.2021. Düsseldorf: German Medical Science GMS Publishing House; 2021. DocP012

doi: 10.3205/21dgnc300, urn:nbn:de:0183-21dgnc3005

Published: June 4, 2021

© 2021 Neyazi et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.

Outline

Text

Objective: For rupture risk assessment of intracranial aneurysms, a multitude of approaches have been postulated. 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 (MIA), the PHASES Score might severely underestimate the rupture risk, since 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 MIA 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, which 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 MIA. For best possible rupture risk assessment of patients with MIA, only the morphological parameter AR1 and the hemodynamical parameter Aneurysm_RRT_max need to be included in the prediction model.