Transverse Cervical Artery: Consistent Anatomical Landmarks and Clinical Experience with Its Use as a Recipient Artery in Complex Head and Neck Reconstruction
Bibliographic record
Abstract
BACKGROUND: Many head and neck reconstructions occur in patients with extensive history of surgery or radiation treatment. This leads to complicated free flap reconstructions, especially in choosing recipient vessels in a "frozen neck." The transverse cervical artery is an optimal second-line recipient artery in head and neck reconstruction. METHODS: Seventy-two neck sides in 36 cadavers were dissected, looking for the transverse cervical artery and transverse cervical vein. Anatomical location of these vessels, their diameter, and length were documented. A retrospective analysis on 19 patients who had head and neck reconstruction using the transverse cervical artery as a recipient artery was undertaken as well with regard to outcome of procedures, reason for surgery, previous operations, and use of vein grafts during surgery. RESULTS: The transverse cervical artery was present in 72 of 72 of cadaveric specimens, and was infraclavicular in two of 72 specimens. Transverse cervical artery length ranged from 4.0 to 7.0 cm, and the mean diameter was 2.65 mm. The transverse cervical vein was present in 61 of 72 cadaveric specimens, the length ranged from 4.0 to 7.0 cm, and the mean diameter was 2.90 mm. The transverse cervical artery averaged 33 mm from midline, and branched off the thyrocervical trunk at an average 17 mm superior to the clavicle. Transverse cervical artery stenosis was markedly less in comparison with external carotid artery stenosis. In a 20-year clinical follow-up study, the transverse cervical artery was the recipient artery in 19 patients. A vein graft was used in one patient, and no flap loss occurred in any of the 19 patients. CONCLUSION: The transverse cervical artery is a reliable and robust option as a recipient artery in free flap head and neck reconstruction.
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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 | 0.004 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".