Evolution of a Pediatric Primary Cerebral ALK-1-Positive Anaplastic Large Cell Lymphoma on Serial MRI
Bibliographic record
Abstract
BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare central nervous system tumor, especially in the pediatric population. There are fewer than 20 described cases of pediatric primary central nervous system anaplastic large cell lymphoma. The child described in our case report demonstrated a dramatic evolution of this tumor in the first 4 weeks on serial imaging. METHODS: Serial MRI imaging was performed followed by biopsy and chemotherapy. RESULTS: Initial imaging revealed a T2 hyperintense lesion in the frontal lobe with abnormally enhancing sulci and minimal surrounding edema and diffusion restriction. Serial imaging revealed progressive increase in the degree of gadolinium enhancement, and the hyperintense T2 edema progressed markedly to exert mass effect. The lesion itself grew marginally. Biopsy revealed an anaplastic large cell lymphoma, only described in 14 previous pediatric patient case reports. The patient was successfully treated with chemotherapy and autologous stem cell transplant. CONCLUSIONS: Our case demonstrates the rapidity with which a PCNSL lesion can develop, and the evolution of the imaging characteristics prior to definitive diagnosis and treatment. Serial imaging by MRI may help differentiate the behavior of a PCNSL from other imitating lesions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".