Virtual stenting workflow with vessel-specific initialization and adaptive expansion for neurovascular stents and flow diverters.
Comput Methods Biomech Biomed Engin
; 19(13): 1423-1431, 2016 Oct.
Article
em En
| MEDLINE
| ID: mdl-26899135
Endovascular intervention using traditional neurovascular stents and densely braided flow diverters (FDs) have become the preferred treatment strategies for traditionally challenging intracranial aneurysms. Modeling stent and FD deployment in patient-specific aneurysms and its flow modification results prior to the actual intervention can potentially predict the patient outcome and treatment optimization. We present a clinically focused, streamlined virtual stenting workflow that efficiently simulates stent and FD treatment in patient-specific aneurysms based on expanding a simplex mesh structure. The simplex mesh is generated using an innovative vessel-specific initialization technique, which uses the patient's parent artery diameter to identify the initial position of the simplex mesh inside the artery. A novel adaptive expansion algorithm enables the acceleration of deployment process by adjusting the expansion forces based on the distance of the simplex mesh from the parent vessel. The virtual stenting workflow was tested by modeling the treatment of two patient-specific aneurysms using the Enterprise stent and the Pipeline Embolization Device (commercial FD). Both devices were deployed in the aneurysm models in a few seconds. Computational fluid dynamics analyses of pre- and post-treatment aneurysmal hemodynamics show flow reduction in the aneurysmal sac in treated aneurysms, with the FD diverting more flow than the Enterprise stent. The test results show that this workflow can rapidly simulate clinical deployment of stents and FDs, hence paving the way for its future clinical implementation.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Vasos Sanguíneos
/
Interface Usuário-Computador
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Encéfalo
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Stents
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Hemodinâmica
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article