Radiological Anatomy of the Olfactory Fossa: Is Skull Base Anatomy Really Ever “Safe”?
Bibliographic record
Abstract
Abstract Objective Computed tomography (CT) is a powerful tool for delineating the anatomy of the anterior skull base. The goal of this study is to further characterize the relevant anatomical features of this area, along with other parameters important for endoscopic sinus surgery. Design Retrospective case review. Setting Tertiary care hospital. Participants Thirty patients who had CT scans of the paranasal sinuses. Main Outcome Measures The following features were assessed using image analysis software: olfactory fossa depth, the length and angle of the lateral lamella, fovea ethmoidalis length and shape, ethmoid roof height and slope, and the position and course of the anterior ethmoid artery. Statistical analysis was performed assessing for differences in the above parameters. Results The mean olfactory fossa depth of the anterior and posterior skull base was 3.4 ± 1.1 and 2.4 ± 0.9 mm, respectively (p < 0.05). The mean lateral lamella length was 3.6 ± 0.9 mm, which did not demonstrate significant variability. The angle of the lateral lamella varied significantly by skull base position, measuring 63.1 ± 17.8 degrees anteriorly, and 39.1 ± 17.9 degrees posteriorly (p < 0.05). In scans classified as a Keros type I, 25.3% had lateral lamellae longer than 4 mm. Furthermore, 43.7% had lateral lamellae with angles less than 45 degrees. Moving anteriorly, the posterior skull base sloped downward in 46.7% of patients. Conclusion Thorough preoperative assessment of CT scans is crucial to understanding the inherent variability of skull base anatomy. Even “safe” anatomy can still contain features such as long and acutely angled lateral lamella, which may predispose patients to iatrogenic injury.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".