Anatomic Sphenoid Cell Variants: Introduction of the Retrosphenoid Cell and Relevance in the Presentation and Management of Sinus Disease
Bibliographic record
Abstract
Background Despite the well-appreciated variability in sphenoid sinus anatomy, there are no documented cases of retrosphenoid cells in the literature to date. Objective This study defines and determines the prevalence of retrosphenoid cells as identified on computed tomography (CT) imaging and intraoperative endoscopy and reviews the prevalence of other related anatomical variants of the sphenoid sinus. Methods Retrospective study of 300 random noncontrast sinus CT scans of patients with chronic rhinosinusitis presenting to a tertiary rhinology center. All identifiable anatomic variations and any presence of retrosphenoid cells and their pneumatization patterns were recorded. The prevalence of various anatomic variations of the sphenoid sinus was also calculated. Results A total of 300 sinus CT scans were included in the study. Protrusion of both the internal carotid artery (42.6%) and optic nerve (19.7%) into the sinus was more prevalent than the dehiscence of either one. A retrosphenoid cell was identified in 2% of CT scans. Other anatomic variants were less prevalent. Conclusion Meticulous review of preoperative imaging is key in identifying rare and complex sphenoid cell variations in planning surgical approaches and potential treatment strategies for the unusually pneumatized sphenoid air cells. Various manifestations of sinus disease can be localized to this area, and suspicion of a retrosphenoid cell should be raised in patients presenting with recalcitrant headache.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".