Abstract
During cardiovascular surgical skill training, the direct quantification regarding surgical performance is still lacking, including transferring clinically relevant information. We introduced a novel computational fluid dynamics-based method in support of vascular surgical hands-on training, which applies continuous self-assessment in vascular anastomoses. The validation of the methodology was implemented in comparing with conventional training courses. The fifth and seventh consecutive anastomoses of the experimental group showed significantly improved results regarding anastomosis quality when compared with the control group. Consecutive demonstration of three-dimensional morphology and functional assessment of anastomoses results in improved practical performance among learners regarding anastomosis quality.
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