Focal leptomeningeal vascular anomalies on brain MRI: A mimic of leptomeningeal metastatic disease
Bibliographic record
Abstract
Background: The diagnosis of leptomeningeal metastatic disease has major prognostic and therapeutic implications. We report 13 patients with a radiologically distinct kind of focal, enhancing leptomeningeal lesion on brain MRI that mimics leptomeningeal metastatic disease. Methods: These patients were assessed at University Health Network (Toronto, Canada) between January 2001 and December 2023. Results: Median age was 68 years (range, 55-78 years) and 10 patients were women. All patients had brain magnetic resonance imaging (MRI) including contrast-enhanced T2-weighted fluid attenuation inversion recovery (FLAIR) and T1-weighted spin echo sequences. MRI in all 13 patients showed a focal enhancing lesion located along the leptomeningeal surface of the brain. The MRI exams were reported as possible or likely leptomeningeal metastatic disease for the majority (9/13) of patients. Each lesion was curvilinear rather than sheet-like, and some lesions consisted of multiple connected/branching curvilinear structures with the appearance of abnormal vessels. The lesions were distinct from normal blood vessels. Some lesions had a visible connection with a nearby cortical vein. Follow-up contrast-enhanced brain MRI for 8/13 (62%) patients at a median of 3.9 years (IQR 2.4-6.6 years) showed all lesions were unchanged over time. Another 2/13 (15%) patients had clinical and CT brain follow-up after one year with no evidence of metastatic disease. Conclusions: We describe a distinct kind of focal, enhancing leptomeningeal lesion on brain MRI that mimics metastatic disease. These lesions are likely a type of low-flow vascular anomaly. Their curvilinear/branching shape and intense enhancement particularly on T2-weighted FLAIR images distinguish these lesions from tumors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".