Phantom-based experimental validation of fast virtual deployment of self-expandable stents for cerebral aneurysms.
BACKGROUND
Endovascular intervention using a stent is a mainstream treatment for cerebral aneurysms. To assess the effect of intervention strategies on aneurysm hemodynamics, we have developed a fast virtual stenting (FVS) technique to simulate stent deployment in patient-specific aneurysms. However, quantitative validation of the FVS against experimental data has not been fully addressed. In this study, we performed in vitro analysis of a patient-specific model to illustrate the realism and usability of this novel FVS technique.


METHODS
We selected a patient-specific aneurysm and reproduced it in a manufactured realistic aneurismal phantom. Three numerical simulation models of the aneurysm with an Enterprise stent were constructed. Three models were constructed to obtain the stented aneurysms: a physical phantom scanned by micro-CT, fast virtual stenting technique and finite element method. The flow in the three models was simulated using a computational fluid dynamics software package, and the hemodynamics parameters for the three models were calculated and analyzed.


RESULTS
The computational hemodynamics in the patient-specific aneurysm of the three models resembled the very well. A qualitative comparison revealed high similarity in the wall shear stress, streamline, and velocity plane among the three different methods. Quantitative comparisons revealed that the difference ratios of the hemodynamic parameters were less than 10%, with the difference ratios for area average of wall shear stress in the aneurysm being very low.


CONCLUSIONS
In conclusion, the results of the computational hemodynamics indicate that FVS is suitable for evaluation of the hemodynamic factors that affect treatment outcomes.
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Qianqian
Q
Zhang
Department of Mechanics and Engineering Science, Fudan University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China.
Zhuangyuan
Z
Meng
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Ying
Y
Zhang
Department of Mechanics and Engineering Science, Fudan University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China.
Kai
K
Yao
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Jian
J
Liu
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yisen
Y
Zhang
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Linkai
L
Jing
Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. yang-xj@163.net.
Xinjian
X
Yang
Toshiba Stroke and Vascular Research Center, University at Buffalo, The State University of New York, Buffalo, NY, USA.
Nikhil
N
Paliwal
Toshiba Stroke and Vascular Research Center, University at Buffalo, The State University of New York, Buffalo, NY, USA.
Hui
H
Meng
Department of Mechanics and Engineering Science, Fudan University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China. szwang@fudan.edu.cn.
Shengzhang
S
Wang
D002343:Carotid Artery, Internal / Q000473:pathology; D003198:Computer Simulation; D020342:Finite Element Analysis; D006439:Hemodynamics; D006801:Humans; D057446:Hydrodynamics; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D002532:Intracranial Aneurysm / Q000601:surgery* / Q000628:therapy; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D033081:Shear Strength; D012984:Software; D015607:Stents; D013314:Stress, Mechanical; D055114:X-Ray Microtomography