Fig. 3 | Scientific Reports

Fig. 3

From: Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture

Fig. 3

Four representative aneurysms from the study cohort are presented, illustrating morphological and hemodynamic characteristics: (a) aneurysm location (blue) at the parent vessel; (b) the ostium delineating the aneurysm lumen from the parent vessel (blue) along with the velocity iso-surface; (c) streamlines of the temporally averaged flow field color-coded by local blood velocity; (d) temporally averaged wall shear stress induced by frictional forces of blood flow; and (e) the oscillatory shear index, which describes directional changes in shear forces throughout the cardiac cycle. Aneurysms 1 and 2 are ruptured, whereas Aneurysms 3 and 4 are unruptured. Images were screenshoted from Blender 4.4 (https://www.blender.org), from the inhouse software MERCIA within MeVisLab© (https://www.mevislab.de/de/), the VMTK 1.4.0 (http://www.vmtk.org), the inhouse software for semi-automatic detection of the aneurysm neck curve implemented in MATLAB R2022a (https://www.mathworks.com/products/matlab.html?s_tid=hp_ff_p_matlab) and 2024 Simcenter STAR-CCM+ (https://plm.sw.siemens.com/en-US/simcenter/fluids-thermal-simulation/star-ccm/).

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