Avoiding Facial Incisions with Midface Free Tissue Transfer
Bibliographic record
Abstract
BACKGROUND: We have adopted an intraoral microsurgical anastomosis to the facial vessels to eliminate the need for any visible facial incisions. METHODS: Cadaveric dissection was used to demonstrate accessibility of the facial artery and vein through an intraoral approach. Additionally, 5 patients underwent free tissue transfer for reconstruction of major defects of the midface through an intraoral, transmucosal approach, obviating the need for visible skin incisions. RESULTS: The pathology included palatal defects due to mucoepidermoid carcinoma and ischemic necrosis from cocaine abuse, maxillary defects secondary to fibrous dysplasia and avascular necrosis from traumatic blast injury, and a residual posttraumatic bony deformity of the zygoma. Reconstructions were performed with a free ulnar forearm flap, a free vastus lateralis muscle flap, a deep circumflex iliac artery myoosseous flap, a free fibula flap, and a deep circumflex iliac artery osseous flap, respectively. The facial artery and vein were used as recipient vessels for microvascular anastomosis for all cases. Mean follow-up was 12.2 months. All free tissue transfers were successful, and each patient had a satisfactory aesthetic outcome with no associated facial scars. CONCLUSION: This technique can be employed during reconstruction of an array of bony or soft-tissue midface deficits with minimal morbidity. This small series effectively demonstrates the varied pathologies and tissue deficiencies that can be successfully reconstructed with free tissue transfer using an entirely intraoral approach to the recipient facial vessels, resulting in no visible scars on the face and an improvement in the overall aesthetic outcome.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".