Geometrical deployment for braided stent

被引:31
作者
Bouillot, Pierre [1 ,2 ]
Brina, Olivier [1 ]
Ouared, Rafik [1 ]
Yilmaz, Hasan [1 ]
Farhat, Mohamed [2 ]
Erceg, Gorislav [1 ]
Lovblad, Karl-Olof [1 ]
Vargas, Maria Isabel [1 ]
Kulcsar, Zsolt [1 ]
Pereira, Vitor Mendes [1 ,3 ,4 ]
机构
[1] Univ Hosp Geneva, Dept Neuroradiol, Geneva, Switzerland
[2] Ecole Polytech Fed Lausanne, Lab Hydraul Machines LMH, Ave Cour 33bis, CH-1007 Lausanne, Switzerland
[3] Univ Hlth Network, Toronto Western Hosp, Dept Med Imaging, Div Neuroradiol, Toronto, ON, Canada
[4] Univ Hlth Network, Toronto Western Hosp, Dept Surg, Div Neurosurg, Toronto, ON, Canada
基金
瑞士国家科学基金会;
关键词
Flow diverter stent; Braided stent; Virtual deployment; Geometrical model; Intracranial aneurysm; PIPELINE EMBOLIZATION DEVICE; COMPUTATIONAL FLUID-DYNAMICS; ANEURYSMAL FLOW MODIFICATION; INTRACRANIAL ANEURYSMS; DIVERSION TREATMENT; CEREBRAL ANEURYSMS; PARENT VESSEL; IN-VITRO; PERFORATORS; DIVERTORS;
D O I
10.1016/j.media.2016.01.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The prediction of flow diverter stent (FDS) implantation for the treatment of intracranial aneurysms (IAs) is being increasingly required for hemodynamic simulations and procedural planning. In this paper, a deployment model was developed based on geometrical properties of braided stents. The proposed mathematical description is first applied on idealized toroidal vessels demonstrating the stent shortening in curved vessels. It is subsequently generalized to patient specific vasculature predicting the position of the filaments along with the length and local porosity of the stent. In parallel, in-vitro and in-vivo FDS deployments were measured by contrast-enhanced cone beam CT (CBCT) in idealized and patient-specific geometries. These measurements showed a very good qualitative and quantitative agreement with the virtual deployments and provided experimental validations of the underlying geometrical assumptions. In particular, they highlighted the importance of the stent radius assessment in the accuracy of the deployment prediction. Thanks to its low computational cost, the proposed model is potentially implementable in clinical practice providing critical information for patient safety and treatment outcome assessment. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:85 / 94
页数:10
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