Early experience with a patient‐specific virtual surgical simulation for rehearsal of endoscopic skull‐base surgery
Bibliographic record
Abstract
BACKGROUND: With the help of contemporary computer technology it is possible to create a virtual surgical environment (VSE) for training. This article describes a patient-specific virtual rhinologic surgical simulation platform that supports rehearsal of endoscopic skull-base surgery. We also share our early experience with select cases. METHODS: A rhinologic VSE was developed, featuring a highly efficient direct 3-dimensional (3D) volume renderer with simultaneous stereoscopic feedback during surgical manipulation of the virtual anatomy, as well as high-fidelity haptic feedback. We conducted a retrospective analysis on 10 patients who underwent various forms of sinus and ventral skull-base surgery to assess the ability of the rhinologic VSE to replicate actual intraoperative findings. RESULTS: In all 10 cases, the simulation experience was realistic enough to perform dissections in a similar manner as in the actual surgery. Excellent correlation was found in terms of surgical exposure, anatomical features, and the locations of pathology. CONCLUSION: The current rhinologic VSE shows sufficient realism to allow patient-specific surgical rehearsal of the sinus and ventral skull base. Further validation studies are needed to assess the benefits of performing patient-specific rehearsal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".