P.105 The “Comprehensive 3D Skull Base Lab”-- enhancing resident education with virtual/augmented reality and 3D printing at Northwestern University
Bibliographic record
Abstract
Background: Due to increasingly limited access to cadavers and first-hand operative experience, there is an increasing need for innovative modalities in neurosurgical education. Recent developments in computer modelling, virtual/augmented reality, and video game technology have created new opportunities for novel teaching tools. We set out to develop a library of 3D models of normal anatomy and pathologic states for use in conjunction with an interactive simulated environment and 3D printing for teaching of neurosurgical residents. Methods: Anatomically accurate 3D models were developed using CT/MRI data from multiple patients using open source segmentation and 3D animation software. An interactive simulated environment was then created using a 3D game engine and used in conjunction with a virtual/augmented reality system. 3D models were also used to for 3D printing. Results: 3D models and an interactive simulated environment were used in conjunction with various viewing modalities, including 3D video, 360 video, and virtual reality headsets, as well as 3D printing. These teaching tools were successfully implemented in neurosurgery didactic teaching sessions and in the skull base lab. Additional benefits were seen with patient engagement and marketing. Conclusions: 3D modeling and animation show considerable promise for neurosurgical education, with additional benefits for patient engagement, marketing, and social media.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".