Delayed pseudoprogression of a vestibular schwannoma postradiosurgery
Bibliographic record
Abstract
Radiosurgery (RS) can offer excellent local control in the management of both benign and malignant tumors measuring less than 3 cm in size. A known late complication of radiosurgery is radiation necrosis which generally occurs within 6-18 months following treatment and has an increased risk of occurrence with higher radiation doses. The lower dose used to treat vestibular schwannomas (VS) makes this complication less frequent. Tumors that do not respond to radiosurgery and continue to grow may require surgical intervention. We report a case of a young male who received radiosurgery (18 Gy in 3 fractions) in February 2016 for a recurrent VS following initial debulking surgery in 2008. Follow-up imaging revealed an interval decrease in size by May 2017; however, by April 2018, there was significant interval increase in the cisternal components of the tumor. By September 2018, the lesion had increased by >50% (to a size of 29 mm) compared to May 2017. The patient agreed to undergo repeat surgical debulking. Upon review of the preoperative MRI, the cisternal component of the tumor had substantially decreased in size. Although uncommon, this reflects delayed, pseudoprogression which, in our case, was self-limiting. This raises a question regarding when to proceed with surgical intervention of growing VS following radiosurgery given the potential for delayed resolution of radiation necrosis and demonstrates a gap in our current literature involving surgery of VS following radiosurgery.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".