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3D-printed cranial models simulating operative field depth for microvascular training in neurosurgery
Vadim Byvaltsev1, Roman Polkin1, Dmitry Bereznyak1
1Department of Neurosurgery and Innovative Medicine, Irkutsk State Medical University, Irkutsk, Russia.
Surgical Neurology International
|June 4, 2021
Summary
3D printed skull models enhance microsurgical training by simulating deep operating fields. This novel approach improves trainee skills and patient safety before entering the operating room.
Area of Science:
- Neurosurgery
- Medical Simulation
- 3D Printing
Background:
- Microsurgical skills for deep neurosurgical fields are challenging to master in vivo.
- Existing training models often lack realistic simulation of deep operative environments.
- Patient safety is paramount, necessitating risk-free training alternatives.
Purpose of the Study:
- To develop and evaluate a novel 3D printed skull model for enhanced microsurgical training.
- To provide a laboratory-based simulation that replicates the depth of a real surgical field.
- To improve neurosurgical trainee proficiency and patient safety.
Main Methods:
- Computed tomography (CT) data of a patient's head were used to create 3D models.
- 3D printed skulls featured openings simulating common surgical approaches.
- Models facilitated practice on femoral artery and abdominal aortic anastomoses in simulated deep fields.
Main Results:
- Trainees reported improved hand positioning, comfort with anastomosis depth, and simulation of skull angle and fixation.
- The 3D models effectively recreated the deep operating field.
- Absence of intracranial structures noted as a limitation for future development.
Conclusions:
- 3D printed neurosurgical models offer a valuable tool for microsurgery training.
- Simulation of deep operative fields enhances accuracy and efficiency.
- This training methodology can significantly reduce patient risk during complex procedures.
