Orbital Osteoma
Bibliographic record
Abstract
PURPOSE: This study reviews the clinical presentation and management of 11 cases of sino-orbital osteoma. METHODS: The medical records of patients with primary (originating from orbital bone) and secondary (originating from the paranasal sinuses) orbital osteoma from the academic practices of 4 surgeons (A.V.C., M.J.L., P.J.D., V.D.D.) were reviewed for clinical presentation and course, pathologic study, and radiologic reports. A Medline search of English-language literature on orbital osteomas was conducted for comparison with these findings. RESULTS: Eleven cases of primary (1) and secondary (10) orbital osteoma were reviewed, with a mean follow up of 16 months. Seven patients were women. Ages ranged from 15-68 years, with a median of 40 years. Presenting complaints included slowly progressive globe displacement, palpable bony nodule, pain, and diplopia. Surgery was performed in 10 cases. Surgical approach varied according to location and size of each lesion and was performed in combination with otolaryngology and neurosurgery services as needed. Reconstruction included sculpting osteomatous bone to natural orbital contours, repair of orbital wall defects with implants, and obliteration of frontal sinus. Lesions demonstrated mixed compact, cancellous, and fibrous histologic subtypes. CONCLUSIONS: Osteomas are the most common tumor of the paranasal sinuses (noted in up to 3% of coronal CT images), but secondary extension in or primary involvement of the orbit is rare. A variety of surgical approaches led to successful outcomes in this series. Complete surgical removal is not always necessary, and partial sculpting may relieve symptoms and cause less surgical morbidity in selected cases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".