3.8 Article

Evaluation and Verification of Fast Computational Simulations of Stent-Graft Deployment in Endovascular Aneurysmal Repair

Journal

FRONTIERS IN MEDICAL TECHNOLOGY
Volume 3, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmedt.2021.704806

Keywords

aneurysm; computer assisted surgery; stent graft; endovascular aneurysm repair; reduced order model (ROM)

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FEVAR is a minimally invasive procedure for repairing the aorta while preserving blood flow to critical organs. This study introduces and evaluates a virtual reality-based assistance solution for FEVAR, which has been verified to achieve accuracy compatible with clinical expectations.
Fenestrated Endovascular Aortic Repair, also known as FEVAR, is a minimally invasive procedure that allows surgeons to repair the aorta while still preserving blood flow to kidneys and other critical organs. Given the high complexity of FEVAR, there is a pressing need to develop numerical tools that can assist practitioners at the preoperative planning stage and during the intervention. The aim of the present study is to introduce and to assess an assistance solution named Fast Method for Virtual Stent-graft Deployment for computer assisted FEVAR. This solution, which relies on virtual reality, is based on a single intraoperative X-ray image. It is a hybrid method that includes the use of intraoperative images and a simplified mechanical model based on corotational beam elements. The method was verified on a phantom and validated on three clinical cases, including a case with fenestrations. More specifically, we quantified the errors induced by the different simplifications of the mechanical model, related to fabric simulation and aortic wall mechanical properties. Overall, all errors for both stent and fenestration positioning were less than 5 mm, making this method compatible with clinical expectations. More specifically, the errors related to fenestration positioning were less than 3 mm. Although requiring further validation with a higher number of test cases, our method could achieve an accuracy compatible with clinical specifications within limited calculation time, which is promising for future implementation in a clinical context.

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