A novel model of dual-network composite hydrogels for application in endoscopic submucosal dissection

Endoscopic submucosal dissection (ESD) is a critical technique for treating early-stage gastrointestinal tumors, requiring precise operational skills. Traditional training methods, however, face challenges such as high costs, ethical concerns, and sustainability issues. This study aims to design a novel training model based on dual-network composite hydrogel (DNH) (Jing, et al, Polymers 11:952,2019) to simulate the multilayered structure of gastric tissue, providing a more realistic and effective training environment.

A new DNH model was developed to simulate gastric tissue's structure and biomechanics. The effectiveness of the model in ESD training was evaluated through structured assessments with participants of different experience levels. Physicians trained with the DNH model were evaluated for technical precision, efficiency, and complication risk.

The DNH model demonstrated superior performance, with physicians using the model showing significantly higher technical precision and efficiency in ESD procedures. Additionally, the model resulted in a substantially reduced risk of complications compared to traditional methods. Participants rated the model highly for reusability and lower cost, confirming its effectiveness as a training tool.

The dual-network composite hydrogel model offers great potential for ESD training, providing an efficient, safe, and cost-effective alternative to traditional training methods. Its integration into medical education could enhance the development of surgical skills and improve clinical practice outcomes.