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Endoscopic Endonasal Trans-sphenoidal Approach: Minimally Invasive Surgery for Pituitary Adenomas

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Published on: January 17, 2018

Training models and simulators for endoscopic transsphenoidal surgery: a systematic review.

Giacomo Santona¹, Alba Madoglio^2,3, Davide Mattavelli⁴

¹Department of Information Engineering, University of Brescia, Brescia, Italy.

Neurosurgical Review

|September 19, 2023

Summary

This systematic review evaluates training models for endoscopic transsphenoidal surgery (ETS). Current models have limitations in simulating tumor removal and arachnoid preservation, highlighting a need for improved, cost-effective solutions for neurosurgical training.

Keywords:

3D printing Animal head Arachnoid Cadaveric head Pituitary adenoma Training models Training simulators Transsphenoidal surgery

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Simulator Training for Endovascular Neurosurgery

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Published on: May 6, 2020

Area of Science:

Neurosurgery
Medical Education
Surgical Simulation

Background:

Endoscopic transsphenoidal surgery (ETS) is a complex technique requiring specialized training.
Existing training models and simulators for ETS lack comprehensive systematic review.
There is a need to critically evaluate current training methodologies for ETS.

Approach:

A systematic literature search was conducted on PubMed and Scopus databases until February 2023, supplemented by Google searches for commercial models.
101 articles were included in the final analysis, categorizing models into enhanced cadaveric heads, animal models, artificial solutions, virtual/augmented reality simulators, and pre-operative planning tools.
Key features assessed included training capabilities, anatomical reproduction (tumor/arachnoid), assessment methods, validation, and cost.

Key Points:

Training models were categorized into five types, each with distinct advantages and limitations.
Cadaver-based models are costly, while cheaper artificial solutions are suitable primarily for initial training stages.
Most current models inadequately simulate sellar tumors and suprasellar arachnoid structures, particularly during tumor removal with arachnoid preservation.

Conclusions:

Further research is needed to develop realistic and cost-effective simulation of tumor removal with arachnoid preservation for ETS training.
Optimizing artificial models is crucial for efficient and safe training of future neurosurgical generations.
Current limitations in existing training models necessitate advancements for comprehensive ETS skill development.