Novel Vascularized Pedicle Flaps for Dural Reconstruction via Endoscopic Transorbital Approach: Temporalis Muscle and Pericranial Flaps
Bibliographic record
Abstract
BACKGROUND: The endoscopic transorbital approach (ETOA) has emerged as a valuable minimally invasive technique in skull base surgery, providing direct access to the anterior and middle cranial fossae. However, effective reconstruction of dural defects remains a significant technical challenge. This study evaluates the feasibility and anatomical characteristics of temporalis muscle flaps (TFs) and pericranial flaps (PFs) for dural reconstruction following ETOA, using cadaveric models. METHODS: Four fresh cadaveric heads were dissected. The TFs were harvested using an inferior-based pedicle, whereas the PFs were obtained endoscopically. Flap dimensions were measured and reported as median and range. RESULTS: The TFs demonstrated consistent dimensions, with a median caudal length of 20.75 mm (range 20-22) and a median lateral width of 21.25 mm (range 20-23). PFs exhibited greater variability, with a mean length of 97.75 mm and a mean width of 54 mm. These findings suggest that TFs are optimal for defects centered on the temporal dura, whereas PFs offer broader, customizable coverage for larger or more complex reconstructions. CONCLUSIONS: Both TFs and PFs are feasible options for dural reconstruction following ETOA, providing robust vascularization and adaptability to defect size and location. Further clinical studies are warranted to validate their application in live surgical settings.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".