Neurolymphomatosis of the Brachial Plexus and its Branches: Case Series and Literature Review
Bibliographic record
Abstract
BACKGROUND: Neurolymphomatosis is a process of neoplastic endoneurial invasion, most strongly associated with non-Hodgkin's lymphoma. It must be distinguished from paraneoplastic, metabolic, nutritional and treatment-related causes of neuropathy that are common in this patient population. METHODS: This brief case series illustrates the protean manifestations of neurolymphomatosis of the brachial plexus, ranging from focal distal mononeuropathy to multifocal brachial plexopathy, either as the index manifestation of lymphoma or as a complication of relapsing disease. RESULTS: Prominent asymmetry, pain and nodular involvement on neuroimaging may help distinguish neurolymphomatosis from paraneoplastic immune demyelinating radiculoneuropathy. MR neurography criteria for the diagnosis of neurolymphomatosis include hyperintensity on T2 and STIR sequences, focal and diffuse nerve enlargement with fascicular disorganization and gadolinium enhancement. No specific anatomical distribution within the brachial plexus has, however, been found to be characteristic. Fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging is the imaging modality with the highest sensitivity for detection of nodal or extranodal spread in lymphoma. CONCLUSIONS: Brachial plexus neuropathy in neurolymphomatosis is highly protean in its distribution, semiology and relation to lymphoma staging. Dedicated MRI and PET-CT imaging are leading diagnostic modalities.
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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 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".