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Published on: January 11, 2020
Feasibility and practicality of a novel teaching aid for microvascular anastomosis simulation training in
Guosheng Shi1, Huiling Ren2, Dawei Zhao1
1Department of Neurosurgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
Background:
This study aimed to develop a novel teaching aid for microvascular anastomosis training in neurosurgery using 3D printing technology based on CT and MRI imaging data, and to evaluate its effectiveness and practicality.
Methods:
Based on CT or MRI imaging data, a 3D model integrating micro-vessels, skull, and brain tissue was fabricated and connected to a peristaltic pump and a pipeline system to create a teaching aid for microvascular anastomosis simulation training. Twenty senior medical students were recruited and divided into two groups: a control group, which trained using traditional soft rubber tubes, and an observation group, which trained using the 3D-printed teaching aid. Following the training, participants from both groups performed chicken wing artery anastomosis. The training outcomes, including the patency rate of vascular anastomosis, the time required to complete the anastomosis, and the trainees' surgical performance, were evaluated. Additionally, six experienced neurosurgeons were recruited to teach the course using both teaching aids for two hours each. They were then surveyed via a questionnaire to assess and rate the effectiveness of the teaching aids.
Results:
The observation group demonstrated a significantly higher patency rate of vascular anastomosis, a shorter time to complete the anastomosis, and higher scores for surgical proficiency and procedural standardization compared to the control group (all P < 0.001). Additionally, the neurosurgeons provided positive evaluations of the novel 3D-printed teaching aid, awarding high scores for its practicality, scientific rigor, and overall effectiveness.
Conclusion:
The novel 3D-printed teaching aid serves as an effective tool for microvascular anastomosis training in neurosurgery, offering significant advantages such as enhanced training effectiveness, high-fidelity simulation, cost efficiency, and customization capabilities.
