Options
Design and experimental validation of a novel additively manufactured stenosis model for neurointerventional training
Citation Link: https://doi.org/10.15480/882.16210
Publikationstyp
Journal Article
Date Issued
2025-06-02
Sprache
English
TORE-DOI
Volume
7
Issue
1
Article Number
2067
Citation
Transactions on additive manufacturing meets medicine 7 (1): 2067 (2025)
Publisher DOI
Publisher
Infinite Science Publishing
Stenoses, or pathological narrowings of blood vessels, are significant risk factors for cardiovascular events. While various stenosis models exist for training purposes, they often present limitations for intracranial applications due to their size and inability to maintain vessel dilation after treatment. This paper presents the development and evaluation of a novel stenosis model specifically designed for compact, intracranial applications within the neurointerventional simulator HANNES. The model utilizes a C-shaped clip mechanism that selectively constricts an elastic vessel, incorporating a designed breaking point that ensures permanent vessel dilation upon reaching a critical pressure during balloon angioplasty. The model was manufactured using stereolithographic additive manufacturing and underwent experimental evaluation using a standard PTA balloon catheter. Results demonstrated reproducible burst pressures of 12 ± 1 bar, aligning with typical clinical parameters. X-ray imaging confirmed successful integration into the HANNES simulator, enabling realistic simulation of stenosis treatment procedures. Experiments showed that the developed stenosis model should be used with elastic silicone tubes connected to additively manufactured vessel models, as direct application to printed vessels either resulted in vessel wall damage during compression or insufficient constriction depending on the C-clip geometry. Based on these findings and the successful validation results, the model represents a reliable and reproducible platform for neurointerventional training, with its parametric design allowing adaptation to various clinical scenarios.
DDC Class
620: Engineering
Publication version
publishedVersion
Loading...
Name
2067_AMMM2025_Paper_Schmiech.pdf
Size
422.23 KB
Format
Adobe PDF