Constructing an Individualized Middle Cerebral Artery Model Using 3D Printing and Hydrogel for Bypass Training

Area of Science:

• Neurosurgery
• Biomedical Engineering
• Medical Simulation

Background:

• Cerebral bypass surgery (CBS) is complex, requiring specialized training.
• Existing training models for CBS are insufficient to meet training demands.

Purpose of the Study:

• To develop an anatomically accurate, DICOM-based middle cerebral artery (MCA) model for CBS training.
• To create a cost-effective and accessible training tool that mimics living tissue properties.

Main Methods:

• Utilized DICOM data of the MCA to create internal and external molds via 3D printing.
• Fabricated a tissue-mimicking cryo-gel using polyvinyl alcohol (PVA) and freeze-thaw cycles.
• Dissolved the internal mold using chloroform to obtain the final MCA model.

Main Results:

• The 3D-printed DICOM-based MCA model is anatomically accurate and cost-effective (<$5 per model).
• The model exhibits handling and suturing properties similar to living tissue.
• Statistically significant differences in dimensions were minimal, validating the model's accuracy.

Conclusions:

• The DICOM-based MCA model offers a valuable, low-cost solution for CBS training.
• This training model can improve microsurgical dexterity and cerebrovascular anatomy understanding.
• The developed training system addresses limitations in time, cost, and space for surgical skill acquisition.