Sellar and Parasellar Intravascular Lymphoma Mimicking Pituitary Apoplexy
Bibliographic record
Abstract
BACKGROUND: Intravascular lymphoma (IVL) is a rare subtype of large-cell non-Hodgkin lymphoma, characterized by proliferation of lymphoma cells within the lumina of small vessels. There are no previously reported cases of IVL involving the pituitary gland presenting with neuro-ophthalmic findings. METHODS: A 68-year-old female presented with headache, right third nerve palsy, and Horner syndrome. MRI showed a 1.4-cm sellar mass consistent with a pituitary macroadenoma. Two weeks later, despite treatment with dexamethasone, the patient developed complete bilateral ophthalmoplegia and ptosis. Repeat MRI showed invasion of the clivus and cavernous sinuses, and a transsphenoidal pituitary biopsy was undertaken. RESULTS: The preliminary histopathology was consistent with bland pituitary apoplexy, but subsequent examination of an incidentally biopsied nasal polyp revealed endovascular malignant lymphoid cells that, on further scrutiny, were also present in the pituitary tissue. The diagnosis of IVL was confirmed, and the patient had an excellent clinical and radiological response to cyclophosphamide, doxorubicin, vincristine, prednisolone, and rituximab (CHOP-R) chemotherapy. CONCLUSION: IVL may involve the pituitary gland, causing sellar mass effect, cavernous sinus infiltration, and pituitary ischemia, mimicking pituitary apoplexy with neuro-ophthalmic features. It can be effectively treated with CHOP-R chemotherapy.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".