Internal mammary artery and vein: Recipient vessels for free tissue transfer to the head and neck in the vessel‐depleted neck
Bibliographic record
Abstract
BACKGROUND: Microvascular free tissue transfer is a standard reconstructive option for postablative defects of the head and neck. However, the success of this surgery requires suitable recipient vessels in the cervical region. This form of reconstruction can be particularly challenging in the vessel-depleted neck. While the internal mammary artery and vein (IMA/V) have been used extensively in breast reconstruction, there are few reports describing their use in head and neck reconstruction. We report the first case series of the use of the internal mammary vessels for head and neck microvascular reconstruction. METHODS: We reviewed 5 cases of free tissue transfers to the head and neck in which extensive prior treatment precluded the use of more traditional recipient vessels in the neck or upper chest. RESULTS: A variety of free flaps were transferred for different reconstructive problems which included: chin/lower lip (n = 2), closure of widely patent tracheoesophageal puncture sites (n = 2), and pharyngoesophageal reconstruction following staged repair of a severe stenosis (n = 1). The radial forearm free flap was transferred in 4 patients and the rectus abdominus free flap in 1 patient. The IMA/V on the right side was prepared in all cases. All free flaps were successfully revascularized without the need for vein grafts and without the need for any microvascular revision procedures. CONCLUSION: The internal mammary artery and vein provide reliable, easily accessible recipient vessels for microvascular reconstruction in the vessel-depleted neck. The selection of free flap donor sites with long donor vessels facilitates the microvascular repair.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".