P.053 Expanded endoscopic endonasal approach for petrous apex lesions: our clinical experience and surgical techniques
Bibliographic record
Abstract
Background: Traditionally petrous apex lesions surgical approach is associated with multiple complications including brain injury secondary to brain retraction. Expanded endoscopic endonasal trans-clival (EEET) can be used in selected patients with minimal complications. Methods: We are presenting our experience over the last three years in patients who underwent EEET resection of petrous apex lesions: 8 patients underwent such procedure. All patients underwent extensive workup including MRI and CTA to identify the relation of the carotid to the lesion. All surgeries were done with neuro-physiological monitoring. Intraoperative neuronavigation and endoscopic Doppler were used to identify the petrous segment of the internal carotid artery. Our follow up ranged from 6 months to 2.5 years. Results: All patients presented with severe neurologic symptoms related to either fifth cranial nerve, sixth cranial nerve or brain stem compression. Pathologies included chondrosarcoma, cholesterol granulomas and lymphangioma. All patients demonstrated improvement in their symptoms. None of our patients had intra-operative vascular injury. There was no post-operative CSF leak or infection. Postoperative imaging demonstrated excellent resection with no clear residual. Three patient required adjuvant stereotactic radiosurgery because of their underlying pathology. Conclusions: The expanded endoscopic endonasal approach for petrous apex lesion should be considered as a minimally invasive approach in selected cases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".