ArticleJournal of vascular surgery cases and innovative techniques2022
New computational fluid dynamics-based method for morphological and functional assessment in cardiovascular skill training.
Article in Journal of vascular surgery cases and innovative techniques, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- From Geometry to Flow Allocation: A Physics-Based Framework for Interpretable Microvascular Hemodynamics.Bioengineering (Basel, Switzerland) · 2026Article
- Machine Learning Models for Objective Assessment of Vascular Anastomoses Using Computational Fluid Dynamics for Surgical Skill Training-A Retrospective Study.Journal of clinical medicine · 2026Article
- Computational fluid dynamics to simulate stenotic lesions in coronary end-to-side anastomosis.Interdisciplinary cardiovascular and thoracic surgery · 2025Article
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Authors and funding
7 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: During cardiovascular surgical skill training, the direct quantification regarding surgical performance is still lacking, including transferring clinically relevant information. Methods: 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. Results: The fifth and seventh consecutive anastomoses of the experimental group showed significantly improved results regarding anastomosis quality when compared with the control group. Conclusions: 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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