Variability in the Vascularity of the Pectoralis Major Muscle
Bibliographic record
Abstract
OBJECTIVE: Although the pectoralis major muscle has been the subject of numerous anatomic studies over the past 20 years, there remains a high complication rate for pedicled pectoralis musculocutaneous flaps. In this report, angiograms of 43 pectoralis major muscles were studied to assess the vascular territories of its three arterial supplies: lateral thoracic artery, the pectoral branch of the thoracoacromial artery, and the anterior intercostal perforators of the internal mammary artery. METHODS: Twenty-two adult human cadavers underwent whole-body arterial perfusion (200 mL/kg) with a mixture of lead oxide, gelatin, and water through the carotid artery. All pectoralis major muscles were dissected and radiographed. Radiographs were photographically printed as contact prints. The vasculature of each muscle was analyzed using the paper template technique. RESULTS: The pectoral branch of the thoracoacromial artery supplied 50.7% of the vascular territory of the pectoralis major. The lateral thoracic artery was present in 37 of 43 angiograms and supplied a mean territory of 6.6%. The anterior intercostal perforating branches of the internal mammary artery supplied 43% of muscle parenchyma. There was considerable variability in the extent of various vascular territories from muscle specimen to specimen. CONCLUSION: Despite excellent surgical technique, certain pedicled musculocutaneous pectoralis major flaps may suffer partial distal necrosis simply owing to the relatively small vascular territory of the pectoral branch of the thoracoacromial artery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| 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".