Parametric Mold System for Rapid Fabrication of Silicone Tubular Surgical Training Models

Accessible microsurgical training tools are often limited by cost, manufacturing complexity, and limited adaptability across different training scenarios. This work presents an open-source framework for fabricating compliant silicone tubular models using parametrically generated molds produced via desktop FDM 3D printing. The key feature of this approach is the ability to systematically control lumen diameter, wall thickness, and segment length, enabling reproducible generation of training models with defined mechanical and geometric properties. This allows structured progression across different levels of technical difficulty within a given surgical domain, for example by gradually reducing lumen diameter or modifying wall characteristics. At the same time, the framework supports a wide range of surgical applications, including microvascular, pediatric, and gastrointestinal training scenarios, depending on the selected parameter combinations. Preconfigured printable mold geometries (STL/3MF) are provided for immediate use, while the underlying parametric CAD model enables further customization when needed. Initial demonstrations include suturable and perfusable silicone tubes, as well as composite variants incorporating textile reinforcement (e.g. nylon mesh) to improve suture retention and resistance to tear propagation under tension, while maintaining sufficient compliance for surgical handling. The workflow can be complemented by simple hydrostatic testing to assess leak resistance and structural integrity, enabling an objective complement to subjective training assessment. All files, including CAD models, fabrication notes, and demonstration material, are openly available via the linked dataset (DOI). This approach aims to lower barriers to surgical skills training and to enable distributed, low-cost, and parametrically controlled simulation environments. Users are encouraged to cite the dataset when applying or adapting this method. A future version of this dataset is currently in development, aiming to provide a precomputed library of mold geometries. This will allow users to directly download STL and 3MF files corresponding to specific parameter combinations (lumen diameter, wall thickness, and length) without requiring access to CAD software. For educational and simulation purposes only. Not for clinical use.