Fast simulation of hemodynamics in intracranial aneurysms for clinical use

URN zum Zitieren dieses Dokuments:: urn:nbn:de:bvb:355-epub-751084
DOI zum Zitieren dieses Dokuments:: 10.5283/epub.75108

Deuter, Daniel

; Haj, Amer ; Brawanski, Alexander ; Krenkel, Lars ; Schmidt, Nils-Ole ; Doenitz, Christian

Lizenz: Creative Commons Namensnennung 4.0 International
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Veröffentlichungsdatum dieses Volltextes: 04 Mrz 2025 09:00

Alternative Links zum Volltext:DOI Verlag

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Background
A widely accepted tool to assess hemodynamics, one of the most important factors in aneurysm pathophysiology, is Computational Fluid Dynamics (CFD). As current workflows are still time consuming and difficult to operate, CFD is not yet a standard tool in the clinical setting. There it could provide valuable information on aneurysm treatment, especially regarding local risks of rupture, which might help to optimize the individualized strategy of neurosurgical dissection during microsurgical aneurysm clipping.
Method
We established and validated a semi-automated workflow using 3D rotational angiographies of 24 intracranial aneurysms from patients having received aneurysm treatment at our centre. Reconstruction of vessel geometry and generation of volume meshes was performed using AMIRA 6.2.0 and ICEM 17.1. For solving ANSYS CFX was used. For validational checks, tests regarding the volumetric impact of smoothing operations, the impact of mesh sizes on the results (grid convergence), geometric mesh quality and time tests for the time needed to perform the workflow were conducted in subgroups.
Results
Most of the steps of the workflow were performed directly on the 3D images requiring no programming experience. The workflow led to final CFD results in a mean time of 22 min 51.4 s (95%-CI 20 min 51.562 s–24 min 51.238 s, n = 5). Volume of the geometries after pre-processing was in mean 4.46% higher than before in the analysed subgroup (95%-CI 3.43–5.50%). Regarding mesh sizes, mean relative aberrations of 2.30% (95%-CI 1.51–3.09%) were found for surface meshes and between 1.40% (95%-CI 1.07–1.72%) and 2.61% (95%-CI 1.93–3.29%) for volume meshes. Acceptable geometric mesh quality of volume meshes was found.
Conclusions
We developed a semi-automated workflow for aneurysm CFD to benefit from hemodynamic data in the clinical setting. The ease of handling opens the workflow to clinicians untrained in programming. As previous studies have found that the distribution of hemodynamic parameters correlates with thin-walled aneurysm areas susceptible to rupture, these data might be beneficial for the operating neurosurgeon during aneurysm surgery, even in acute cases.

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