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The use of the novel fenestrated stent graft system in patients with hostile aortic aneurysmal morphology is feasible with acceptable short-term outcomes.

This study shows feasibility of creation of a crisis scenario in a fully immersive angiosuite simulation and team performance of a simulated rEVAR. Performance metrics differentiated between experienced specialists and trainees, and the realism of the simulation exercise and environment were rated highly by experienced endovascular specialists. This simulation has potential as a powerful training and assessment tool with opportunities to improve team performance in rEVAR through both technical and human factor skills training.

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Endovascular instrument video motion analysis is feasible and may represent a valuable tool for the objective assessment of endovascular skill.

PurposeTranscatheter aortic valve implantation (TAVI) demands precise and efficient handling of surgical instruments within the confines of the aortic anatomy. Operational performance and dexterous skills are critical for patient safety, and objective methods are assessed with a number of manipulation features, derived from the kinematic analysis of the catheter/guidewire in fluoroscopy video sequences.MethodsA silicon phantom model of a type I aortic arch was used for this study. Twelve endovascular surgeons, divided into two experience groups, experts () and novices (), performed cannulation of the aorta, representative of valve placement in TAVI. Each participant completed two TAVI experiments, one with conventional catheters and one with the Magellan robotic platform. Video sequences of the fluoroscopic monitor were recorded for procedural processing. A semi-automated tracking software provided the 2D coordinates of the catheter/guidewire tip. In addition, the aorta phantom was segmented in the videos and the shape of the entire catheter was manually annotated in a subset of the available video frames using crowdsourcing. The TAVI procedure was divided into two stages, and various metrics, representative of the catheter’s overall navigation as well as its relative movement to the vessel wall, were developed.ResultsExperts consistently exhibited lower values of procedure time and dimensionless jerk, and higher average speed and acceleration than novices. Robotic navigation resulted in increased average distance to the vessel wall in both groups, a surrogate measure of safety and reduced risk of embolisation. Discrimination of experience level and types of equipment was achieved with the generated motion features and established clustering algorithms.ConclusionsEvaluation of surgical skills is possible through the analysis of the catheter/guidewire motion pattern. The use of robotic endovascular platforms seems to enable more precise and controlled catheter navigation.

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