Characterization of Vessel Deformations During EVAR: A Preliminary Retrospective Analysis to Improve Fidelity of Endovascular Simulators

Abstract

Objective: During endovascular aneurysm repair (EVAR), vessel deformations occur due to the insertion of tools and deployment of stent grafts in the arteries. We present a method for the characterization of vessel deformations during EVAR, and its application on patient datasets for a preliminary retrospective analysis that may be used to improve fidelity of endovascular simulators.

Design: The method provides the extraction of vessel profiles from intraoperative fluoroscopic images and the calculation of a tortuosity index in the 2D fluoroscopy view (τ_2D) used to quantify the vessel deformations (δ%) during EVAR caused by the stiff guidewire insertion (δ%_Stiff) and the stent graft deployment (δ%_Graft), when compared with the undeformed vessel configuration (no device inserted). We applied the method to analyze retrospectively 7 EVAR patient datasets, including vasculature anatomies with different grades of vessel tortuosity or calcification: 2 patients (Pts) with absent tortuosity and mild calcification, 2 with mild tortuosity and mild calcification, 2 with severe tortuosity and mild calcification, and 1 with severe tortuosity and severe calcification. The analysis was focused on deformations of the left common iliac artery (LCIA), which is one of the arterial segments most affected by deformations.

Results: In patients with mild LCIA calcification, the vessel straightening effect due to the stiff guidewire insertion increases as the severity of LCIA tortuosity increases (δ%_Stiff = 0 ± 2%, -19 ± 2%, -45 ± 2% for absent, mild, and severe tortuosity, respectively). In patients with mild/severe LCIA tortuosity, the artery with the deployed graft seems to retain part of the straightening effect caused by the stiff guidewire (δ%_Graft = -9 ± 3%, -31 ± 2%, for mild and severe tortuosity, respectively). In case of severe LCIA calcification, the stiff guidewire causes only a slight straightening effect (δ%_Stiff = -12%) despite the severe vessel tortuosity.

Conclusion: The method was effective in characterizing real vessel deformations during EVAR. Results gave evidence of a relationship between the obtained deformations and the anatomical vessel conformation. These results may be useful to drive predictive models of vessel deformations during EVAR to be implemented in endovascular patient-specific simulators for improving their fidelity.

Keywords: EVAR; Medical Knowledge; Practice-Based Learning and Improvement; endovascular simulator; fluoroscopy; image processing; patient data; vessel deformation.