P.095 Novel use of fluorescein sodium in the resection of a pediatric posterior fossa tumor
Bibliographic record
Abstract
Background: Gross total resection of pediatric posterior fossa tumors is paramount towards improving progression-free survival. Fluorescein accumulates in tumoral tissue, where the blood-brain barrier is disrupted. It can therefore potentially aid in differentiating tumoral versus normal tissue. We aimed to evaluate the efficacy of fluorescent-guidance (using fluorescein) towards the resection of a pediatric cerebellar tumor, as the index case at our institution using this technique. Methods: 5 mg/kg of IV fluorescein sodium was injected upon induction of general anesthesia. During tumor resection, a yellow 560-nm filter (Kinevo microscope, Zeiss) was employed for fluorescent-guidance. The extent of resection was assessed via post-operative MRI. Results: There were no adverse side effects experienced by the patient. Tumoral material was clearly visualized under the yellow 560-nm filter, allowing for satisfactory gross total resection of the lesion (confirmed on post-operative MRI). Preliminary pathology was consistent with medulloblastoma. Conclusions: Fluorescent-guided resection of pediatric posterior fossa tumors appears to be a safe and useful adjunct for gross total resection of these lesions. To the best of our knowledge, this is the first reported case in Canada wherein IV fluorescein was used under a yellow 560-nm filter for resection of a posterior fossa medulloblastoma in a child.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".