Lesions mimicking lacrimal gland pleomorphic adenoma
Bibliographic record
Abstract
AIM: To report a series of patients with lacrimal gland lesions simulating the clinicoradiological features of lacrimal gland pleomorphic adenoma (LGPA). METHODS: Multicentre retrospective, interventional case series. Clinical records of all patients with lesions mimicking LGPA seen in five orbital units were reviewed. RESULTS: The study included 14 patients (seven men and seven women) with a mean age of 50.9 years. The diagnosis of LGPA was made in all cases by experienced orbital surgeons, based on clinicoradiological features, and lacrimal gland excision was performed. Postoperative histology revealed lymphoma (four patients), chronic dacryoadenitis (three patients), adenoid cystic carcinoma (two patients), Sjogren's syndrome (two patients), cavernous haemangioma (one patient), benign lymphoid hyperplasia (one patient) and granulomatous dacryoadenitis (one patient). Comparison with the total number of histologically confirmed LGPA cases seen during the study period revealed that 22.6% of cases of suspected LGPA were misdiagnosed based on clinicoradiological criteria. CONCLUSIONS: Many different lesions may mimic the clinicoradiological features of LGPA. The accepted clinicoradiological criteria used for the diagnosis of LGPA have a high false-positive rate, even in experienced hands. Based on this study, the authors believe that fine-needle aspiration biopsy or intraoperative biopsy and frozen section diagnosis may help reduce unnecessary lacrimal gland excision.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".