Lateral Intracanalicular Growth of Vestibular Schwannomas and Surgical Planning
Bibliographic record
Abstract
OBJECTIVE: To assess the lateral growth pattern in adult patients with growing sporadic vestibular schwannomas (VSs) and to decide if repeat imaging is always necessary immediately preoperatively when determining the route of access for microsurgical excision. PATIENTS: Adults identified as having VS growth from serial scanning (3 scans per patient) between 1994 and 2007 in a single referral center. Neurofibromatosis Type 2 patients and those with tumor growth already to the fundus of the internal auditory canal were excluded. INTERVENTION: Retrospective review of serial imaging. MAIN OUTCOME MEASURES: Lateral growth (in millimeters) in the internal auditory canal. RESULTS: Thirty subjects were identified who had continued serial imaging after documented growth, of whom 26 (87%)showed no lateral growth and 4 (13%) showed growth of 1 mm.This was determined over a median time period of 26 months(interquartile range, 20Y36.5 mo). The time frame between the second and third scans looked at the period of continued observation in this group of subjects in whom known previous tumor growth had occurred, which was 13 months (interquartile range, 9.25Y16.75 mo), and this is the most reliable time frame upon which a practice-changing decision regarding repeat scanning can be made from these data. CONCLUSION: Sporadic VSs that are documented to be growing on serial imaging do not seem to grow to any significant degree in a lateral direction within the internal auditory canal.The results imply that scans performed within a year of any surgical intervention need not be repeated to assess concerns of any further lateral growth while accepting that repeat imaging may be required for other clinical reasons. Key Words:Internal auditory canal
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".