BackgroundA 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.MethodWe 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.ResultsMost 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.ConclusionsWe 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.
机构:
Beijing Inst Technol, Sch Life Sci, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Liang, Xinyu
Peng, Fei
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Capital Med Univ, Beijing Neurosurg Inst, Neurointervent Ctr, Beijing, Peoples R China
Capital Med Univ, Beijing Tiantan Hosp, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Peng, Fei
Yao, Yunchu
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Beijing Inst Technol, Sch Life Sci, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Yao, Yunchu
Yang, Yuting
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Beijing Inst Technol, Sch Life Sci, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Yang, Yuting
Liu, Aihua
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Capital Med Univ, Beijing Neurosurg Inst, Neurointervent Ctr, Beijing, Peoples R China
Capital Med Univ, Beijing Tiantan Hosp, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Liu, Aihua
Chen, Duanduan
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Beijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
Beijing Inst Technol, Sch Med Technol, Beijing, Peoples R ChinaBeijing Inst Technol, Sch Life Sci, Beijing, Peoples R China
机构:
Sichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China
Ruan, Chang
Yu, Qi
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Sichuan Univ, Coll Mech Engn, Chengdu 610065, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China
Yu, Qi
Hou, Jingyuan
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Sichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China
Hou, Jingyuan
Ou, Xinying
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Sichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China
Ou, Xinying
Liu, Yi
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Sichuan Univ, West China Hosp, Dept Neurosurg, Chengdu 610041, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China
Liu, Yi
Chen, Yu
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Sichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R ChinaSichuan Univ, Dept Appl Mech, Chengdu 610065, Sichuan, Peoples R China