P.142 The use of intraoperative magnetic resonance imaging for endoscopic transnasal transsphenoid surgery in children
Bibliographic record
Abstract
Background: Sellar and suprasellar pediatric lesions are uncommon. Endoscopic transnasal transphenoidal surgery (ETTS) is the preferred treatment, but early post-op MRI is hindered by sphenoidal packing. This study aims to assess iMRI safety and efficacy in pediatric ETTS cases. Methods: We performed a retrospective review from Jan 01, 2015 to Dec 31, 2022, evaluating use of iMRI. We determined if the goals of the surgery (biopsy, cyst decompression, subtotal resection, gross total resection) were met, and iMRI’s influence on surgery outcomes. We examined patient age, surgery duration, length of stay, histopathology results, surgical complications, post-op MRIs within 1 month, and tumor progression/recurrence. Results: Over eight years, 20 pediatric ETTS procedures, 14 with iMRI, were conducted. Achieving goals in 13 cases, iMRI prompted extra surgery once. Two adenomas progressed, requiring a second surgery, and craniopharyngioma cases had complications, needing further interventions. Hospital stays varied (1-9 days), with a mean surgery duration of 6 hours and 47 minutes. The study underscores iMRI’s potential impact, stressing the necessity for more research in pediatric transsphenoidal surgeries. Conclusions: While intraoperative MRI in pediatric transsphenoidal surgeries may aid goal verification, this small study doesn’t conclusively demonstrate improved outcomes. Complication rates align with non-IMRI procedures, highlighting the need for further research.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".