P.141 Spontaneous resolution of a left temporal extra-axial lesion: case report
Bibliographic record
Abstract
Background: Meningiomas are the most common intracranial extra-axial lesion. Reports of meningioma regression exist, often in the context of known hormonal or vascular fluctuations, though very few describe complete resolution. Though rare, extra-axial mimics such as lymphoma and chloroma may also spontaneously regress. Methods: Electronic medical records were used to access patient information in accordance with our local ethics review board. Results: A 29-year-old male presenting with new onset seizures was found to have a 22.7 x 26.6 mm left temporal extra-axial lesion, radiologically consistent with meningioma. Due to wait times and patient preference, repeat pre-operative imaging was not available prior to surgical resection 13 months later, though an interim CT had confirmed persistence of the tumour’s size 1 month after diagnosis. Decision was made to proceed with resection; however, intraoperatively, no lesion was identified. Post-operative imaging demonstrated complete disappearance of the lesion, and follow-up imaging has shown no recurrence. Conclusions: This case highlights the possibility of spontaneous resolution of extra-axial lesions and emphasizes the importance of serial imaging prior to resection.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".