Differentiation between Melanin-Laden Macrophages and Melanoma Cells in Vitreous Aspirates
Bibliographic record
Abstract
OBJECTIVE: The differential diagnosis between retinal detachment and melanoma metastatic to the vitreous can be challenging, both clinically and cytologically. We demonstrate the diagnostic features and pitfalls of the cytological assessment. STUDY DESIGN: A case of a metastatic melanoma to the vitreous is compared to a case of retinal detachment initially suspected as melanoma metastasis. Case 1 was a 54-year-old patient with a vague history of pigmented lesions 20 years previously and a current presentation of a visual defect. Case 2 was a 68-year-old patient with a history of melanoma and a presentation of floaters and flashing lights. RESULTS: The vitreous fluid of case 1 contained atypical, pigment-laden cells positive for HMB-45 and assessed as melanoma. On enucleation, a melanoma metastatic to the vitreous was diagnosed. The vitreous fluid of case 2 revealed atypical cells containing pigment granules. The cells were negative for melanocytic markers, while the granules stained positive for melanin. Macrophage marker CD163 was positive in all cells. The interpretation was one of macrophages reactive to the retinal detachment. CONCLUSION: Melanin-laden macrophages can mimic melanoma cells. This needs to be considered in the differential diagnosis. Additional stains can help the distinction.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".