A novel model of dual-network composite hydrogels for application in endoscopic
submucosal dissection
#MMPMID41184750
Zhao F
; Bai Y
; Wu J
; Zhu Z
; Mao J
; Aili A
; Gu H
; Yu S
; Wang Z
BMC Gastroenterol
2025[Nov]; 25
(1
): 781
PMID41184750
show ga
BACKGROUND AND AIMS: 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.
METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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