The effect of augmented real‐time image guidance on task workload during endoscopic sinus surgery
Bibliographic record
Abstract
BACKGROUND: Due to proximity to critical structures, the need for spatial awareness during endoscopic sinus surgery (ESS) is essential. We have developed an augmented, real-time image-guided surgery (ART-IGS) system that provides live navigational data and proximity alerts to the operating surgeon during ablation. We wished to test the hypothesis that task workload would be reduced when using this technology. METHODS: A trial involved 8 otolaryngology residents and fellows performing ESS on cadaveric specimens; 1 side in a conventional method (control) and 1 side with ART-IGS. After computed tomography scanning, anatomical contouring, and registration of the head, a three-dimensional (3D) virtual endoscopic view, ablative tool tracking, and proximity alerts were enabled. Each subject completed ESS tasks and rated their workload during and after the exercise using the National Aeronautics and Space Administration (NASA) Task Load Index (TLX). A questionnaire and open feedback interview were completed after the procedure. RESULTS: There was a significant reduction in mental demand, temporal demand, effort, and frustration when using the ART-IGS system in comparison to the control (p < 0.02). Perceived performance was increased (p = 0.02). Most subjects agreed that the system was sufficiently accurate, caused minimal interruption, and increased confidence. Optical tracking line-of-sight issues were frequently cited as the main limitation early in the study; however, this was largely resolved. CONCLUSION: ART-IGS reduces task workload for trainees performing ESS. Live navigation and alert zones may be a valuable intraoperative teaching aid.
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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".