Suitability of Suprasellar Meningiomas for Endoscopic Endonasal Surgery: Anatomy and Surgical Outcomes
Bibliographic record
Abstract
Background: The treatment of perisellar meningioma intracranial tumors has remained a challenge over the past several decades, mainly attributed to the high risk of visual pathway involvement and vascular encasement. Surgical approaches have remained the mainstay of definitive treatment, but the extended endoscopic transphenoidal surgery is emerging as an alternative option for treatment of these lesions. Endoscopic transsphenoidal surgery provides wider access to the anterior skull base when compared with the classical microscopic transsphenoidal approach, and technological advances such as angled endoscopes and image guidance have extended the success rates of this approach. Most authors however agree that only certain tumors would be appropriate for this treatment option, which causes an obvious selection bias. There are a limited number of studies investigating perisellar meningiomas because of the low incidence of the lesion. This is a retrospective review of perisellar meningiomas that were operated on by Dr. R. Akagami at Vancouver General Hospital between 2001 and 2013 with an open craniotomy approach but may have been appropriate for an endoscopic treatment. Our aim is to have those patients who may have been candidates for endoscopic surgery identified based on radiographic tumor characteristics, and then compared against those patients who had perisellar meningiomas with anatomy not suitable for endoscopic treatment. We will attempt to characterize the patients' suprasellar and meningioma anatomy, and then investigate their outcomes following transcranial resection of their tumor. Our hope is that the results will further identify prospective patients who would be good candidates for endoscopic surgery for perisellar meningiomas, and offer that as an additional treatment option alongside open craniotomy. Methods: This is a retrospective chart review. We will look at patient demographics, clinical presentation, tumor characteristics based on imaging, specific surgical management, postoperative course, and complications. A combination of univariate, multivariate, and logistic regression analyses will be done on data collected. Results: To date, we have reviewed the imaging of 119 patients who had open surgical resection of parasellar meningioma lesions between 2001 and 2013. We have identified 54 patients with tumor anatomy who would be appropriate for endoscopic resection, and analysis is pending ethics approval. Conclusion: Our hypothesis is that those patients who had perisellar meningiomas with anatomy suitable for endoscopic surgery will have more favorable postoperative outcomes from transcranial surgery.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".