Development and validation of a synthetic 3D-printed simulator for training in neuroendoscopic ventricular lesion removal.

OBJECTIVE

Neuroendoscopic surgery using an ultrasonic aspirator represents a valid tool with which to perform the safe resection of deep-seated ventricular lesions, but the handling of neuroendoscopic instruments is technically challenging, requiring extensive training to achieve a steep learning curve. Simulation-based methods are increasingly used to improve surgical skills, allowing neurosurgical trainees to practice in a risk-free, reproducible environment. The authors introduce a synthetic, patient-specific simulator that enables trainees to develop skills for endoscopic ventricular tumor removal, and they evaluate the model's validity as a training instrument with regard to realism, mechanical proprieties, procedural content, and handling.

METHODS

The authors developed a synthetic simulator based on a patient-specific CT data set. The anatomical features were segmented, and several realistic 1:1 skull models with all relevant ventricular structures were fabricated by a 3D printer. Vascular structures and the choroid plexus were included. A tumor model, composed of polyvinyl alcohol, mimicking a soft-consistency lesion, was secured in different spots of the frontal horn and within the third ventricle. Neurosurgical trainees participating in a neuroendoscopic workshop qualitatively assessed, by means of a feedback survey, the properties of the simulator as a training model that teaches neuroendoscopic ultrasonic ventricular tumor surgery; the trainees rated 10 items according to a 5-point Likert scale.

RESULTS

Participants appreciated the model as a valid hands-on training tool for neuroendoscopic ultrasonic aspirator tumor removal, highly rating the procedural content. Furthermore, they mostly agreed on its comparably realistic anatomical and mechanical properties. By the model's first application, the authors were able to recognize possible improvement measures, such as the development of different tumor model textures and the possibility, for the user, of creating a realistic surgical skull approach and neuroendoscopic trajectory.

CONCLUSIONS

A low-cost, patient-specific, reusable 3D-printed simulator for the training of neuroendoscopic ultrasonic aspirator tumor removal was successfully developed. The simulator is a useful tool for teaching neuroendoscopic techniques and provides support in the development of the required surgical skills.