Intraocular Lymphoma and Central Nervous System Lymphoma Involving the Hypothalamus
Bibliographic record
Abstract
A 77-year-old woman presented with sudden onset of loss of vision in the left eye and bilateral eye inflammation. Biopsy of the vitreous fluid of the right eye revealed large abnormal cells suggestive of lymphoma. A staging F-18 FDG PET/CT showed intense uptake in the hypothalamus, and mild focal uptake in the subcutaneous tissues of the right lower leg, which were biopsied to reveal diffuse large B cell lymphoma. The patient was treated with high dose chemotherapy (methotrexate), and a follow-up PET/CT showed complete resolution of the hypothalamic and right leg lesions. Intraocular-central nervous system lymphoma (also known as oculocerebral lymphoma) is rare, with only 150 cases reported in the literature. This case highlights the utility of PET/CT in the staging and evaluation of response to therapy for this rare lymphoma subtype. We recommend that patients with intraocular-central nervous system lymphoma, who have a staging PET/CT should have total body acquisitions that include the head and neck, and upper and lower extremities, as these may yield unexpected sites of disease, easily accessible for biopsy.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".