Facial artery musculomucosal flap for reconstruction of skull base defects: A cadaveric study
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Failure in skull base defects reconstruction following tumor resection can have serious consequences such as ascending meningitis and pneumocephaly. The nasoseptal flap showed a very low incidence of cerebrospinal fluid leak but is not always available. The superiorly pedicled facial artery musculomucosal (FAMM) flap has been successfully used for reconstruction of head and neck defects. Our objective is to show that the FAMM flap can be used as a new alternative in skull base reconstruction. STUDY DESIGN: Cadaveric study. Feasibility. METHODS: Thirteen specimens underwent bilateral FAMM flap dissection. Two new modifications of the traditional FAMM flap have been developed. Feasibility in FAMM flap transfer to the skull base was investigated through endoscopic skull base dissection and maxillectomy in four specimens. Measurements were recorded for each harvested flap. RESULTS: The mean surface area of the modified FAMM flap efficient for reconstruction was 15.90 cm(2) . The flaps easily covered the simulated defects of the frontal sinus and the fovea ethmoidalis areas. Modifications of the traditional FAMM flap were necessary for a tension-free coverage of the planum sphenoidale and sella turcica. CONCLUSION: The FAMM flap holds high potential as a new alternative vascular flap in skull base reconstruction. However, it has not been used in patients yet and should be considered only when other options are not available. New modifications developed in this article can elongate the traditional FAMM flap, potentially contributing to a tighter seal of the skull base defect than FAMM flap alone.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".