Analysis of the wall thickness of intracranial aneurysms: Can computational fluid dynamics detect the translucent areas of saccular intracranial aneurysms and predict the rupture risk preoperatively?

ABSTRACT

Background and purpose: The translucent area on the surface of intracranial aneurysms (IAs) is associated with rupture risk. In the present study, the Polyflow module of the Ansys software was used to simulate and analyze the thickness of the aneurysm wall to detect whether it was "translucent" and to assess the rupture risk. Methods: Forty-five patients with 48 IAs who underwent microsurgery were retrospectively reviewed. The medical records, radiographic data, and intraoperative images of the patients were collected. The image data were analyzed using computational fluid dynamics (CFD) simulations to explore the relationship between the simulated thickness of the aneurysm wall, the translucent area, and the rupture point of the real aneurysm's surface to predict the rupture risk and provide a certain reference basis for clinical treatment. Results: The Polyflow simulation revealed that the location of the minimum extreme point of the simulated aneurysm wall thickness was consistent with the translucent area or rupture point on the surface of the real aneurysm. There was a downward trend in the correlation between the change rate (IS) in the wall area and volume during aneurysm growth and rupture. Ruptured aneurysms have a greater inhomogeneity coefficient Iδ than the unruptured ones. In the unruptured group, translucent aneurysms also had greater inhomogeneity coefficients Iδ and more significant thickness changes (multiple IBA) than non-translucent ones. Conclusions: The Ansys software Polyflow module could detect whether the unruptured aneurysms were translucent and predict the rupture risk and rupture point. Clinical trial registration https//clinicaltrials.gov/, Identifier, NCT03133624.