Histopathological Study on the Proposed Pathogenesis of Intratarsal Keratinous Cysts
Bibliographic record
Abstract
PURPOSE: Intratarsal keratinous cysts (IKCs) are a recently described entity that is frequently misdiagnosed clinically as chalazia and mislabeled in the literature as "intratarsal epidermal inclusion cysts" or "epidermoid cysts." It is important to accurately diagnose IKCs and distinguish them from chalazia because IKCs require a complete surgical excision and can exhibit multiple recurrences following curettage. The authors performed a retrospective case series to further elucidate the pathogenesis of IKCs and to determine the diagnostically optimal panel of stains for diagnosis. METHODS: A study group of 8 specimens of IKCs and control specimens of epidermal inclusion cysts were obtained from their pathology laboratories. The authors compared the histological and immunohistochemical profile of IKCs and epidermal inclusion cysts by staining sections from each specimen with hematoxylin and eosin, periodic acid-Schiff, Masson trichrome, cytokeratin 5, cytokeratin 17, carcinoembryonic antigen, and epithelial membrane antigen. The immunoreactivity data were then analyzed using a 2-tailed Mann-Whitney test, assuming a nonparametric population (p < 0.05 is significant). RESULTS: Histopathologically, IKCs are embedded in the tarsus lined by stratified squamous epithelium with an inner undulating cuticle filled with a compact keratinous-appearing material. The authors demonstrate that IKCs develop progressively from dilated meibomian ducts to the formation of complete cysts with their markers. The most valuable immunochemical stains to diagnose IKC were cytokeratin 17, carcinoembryonic antigen, and epithelial membrane antigen (p < 0.05 with each). CONCLUSIONS: These findings provide a better understanding of the pathogenesis and the immunohistochemical findings of this relatively new entity allowing for more appropriate diagnosis of IKCs aiming to reduce future complications from their management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".