Development and Validation of a Novel Human Fixed Cadaveric Model Reproducing Cerebrospinal Fluid Circulation for Training in Endoscopic Skull Base Surgery
Bibliographic record
Abstract
Background: Endoscopic endonasal skull base reconstruction is a complex skill to acquire during surgical training. Currently described cadaveric models for training purposes mainly use fresh-frozen cadaveric heads, which have the disadvantage of being less accessible and less reusable than formaldehyde treated specimens. Another drawback of currently described models is the general lack of measurement of the pressure generated by the simulated cerebrospinal fluid (CSF) flow. Objective: To elaborate and validate the practicality of a human formaldehyde-fixed cadaveric model that reproduces a realistic CSF circulation and that adequately renders a CSF leak similar to those encountered during endoscopic endonasal skull base surgery. Methods: An external ventricular drain that connects with a peristaltic pump is placed under direct visualization in the subarachnoid spaces of the interpeduncular cisterns, which allows a water circulation that reproduces CSF circulation. A fiber-optic intracranial pressure (ICP) sensor is also used, to measure intracranial pressure at all times and adjust water flow to obtain ICP measurements similar to those encountered during surgery. Endoscopic endonasal skull base approaches reflecting the currently most used corridors are performed, to create different skull base openings and CFS leaks. Medical students, surgical residents as well as experienced ENT surgeons and neurosurgeons were tasked with reconstruction of the various defects using a standardized multilayered approach, with the goal of obtaining a watertight closure under normal ICP ranges. Compiled data included total reconstruction time, continuous ICP monitoring and success/failure to achieve watertight reconstruction. A Likert questionnaire was used to evaluate authenticity and usefulness of the model. Results: The newly created human fixed cadaveric model reproduced CSF circulation in all tested conditions. The model was tested multiple times on four different specimens, with four different types of dural defects (sellar, suprasellar, transcribriform and transclival). Intracranial pressures were similar to physiologic conditions (between 12 and 20 mm Hg) and were reproducible with fixed peristaltic pump parameters. Each reconstruction could easily be tested for any residual leaks and success rate concurred with the training level. There was a strong correlation between subjective assessment of the quality of skull base reconstruction and intracranial pressure after reconstruction. Ninety-four percent of participants strongly agreed that the cadaveric model was realistic and allowed them to improve their surgical skills, as well as their endoscopic abilities. Conclusion: This novel human fixed cadaveric model for CSF circulation is efficient and adequately reproduces surgical conditions, as well as CSF leaks created by different skull base approaches. The newly created cadaveric model is accessible, easy to reproduce and can be reused. It can be used as a tool for research purposes and as a learning tool for endoscopic endonasal skull base surgery, which usually require a long learning curve for residents and trainees. Publication History Article published online: 01 February 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".