Primary Central Nervous System Cytotoxic/Suppressor T-Cell Lymphoma: Report of a Unique Case and Review of the Literature
Bibliographic record
Abstract
Peripheral T-cell lymphoma primary to the central nervous system is a rare occurrence. The authors report a case of an 89-year-old woman who presented with a 3-month history of worsening confusion and recent onset of headache, nausea and vomiting, and upper limb tremors. Computed tomography and magnetic resonance imaging examinations demonstrated a 4.5-cm solitary brain mass in the right basal ganglia with compression along the ventricular system. No other lesion was found in the patient. Histologic and immunohistochemical studies of a stereotactic biopsy of the mass showed a T-cell lymphoproliferative lesion positive for CD3, CD8, CD57, and T-cell intracellular antigen 1 and negative for CD4, CD56, CD30, anaplastic lymphoma kinase, and CD20. A monoclonal T-cell receptor-gamma gene rearrangement was detected by polymerase chain reaction analysis of genomic DNA isolated from paraffin-embedded tumor tissue sections. These findings were consistent with peripheral T-cell lymphoma of cytotoxic/suppressor phenotype, resembling the phenotype of T-cell large granular cell leukemia. To the authors' best knowledge, this represents the first reported case of primary brain T-cell lymphoma with a cytotoxic/suppressor immunophenotype. A brief review of the literature of primary brain T-cell lymphoma is also presented.
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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 | 0.002 | 0.002 |
| 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 | 0.003 |
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".