The Superficial Femoral Artery Flap: A 3-Dimensional Anatomical Study
Bibliographic record
Abstract
BACKGROUND: The superficial femoral artery perforator (SFAP) flap offers advantages for pedicled transfer including consistent perforators and vascular territory, well-hidden donor site scar, and hairless flap skin. This article provides a historical overview of the SFAP flap and describes the vascular anatomy of the SFAP by 3-dimensional analysis and angiography. METHODS: Ten fresh cadavers were injected using the lead oxide technique through the femoral artery. Spiral computed tomographic scanning and 3-dimensional evaluation were used to describe the SFAP number, diameter, length, type, and location. RESULTS: A total of 288 perforators in 15 cadaver limbs were identified; 19 ± 8 perforators per thigh ≥0.5 mm in diameter, with an average diameter of 0.8 ± 0.3 mm and a range of 0.5 to 2.1 mm; the mean length of each perforator was 68 ± 31 mm; 45% were septocutaneous and 55% were musculocutaneous. The medial thigh region was divided into 6 areas (anterior and posterior halves, then the proximal third, middle third, and distal third of each). The majority of the perforators were located in the middle and distal thirds of the anteromedial thigh (33% each). CONCLUSIONS: Using 3-dimensional vascular anatomical analysis, the number, location, length, type, and diameter of the SFAP were documented. In the literature, relatively few reports of the use of the SFAP flap are available, however, this is a valid donor site with consistent cutaneous perforators suitable for harvest as a local or regional flap transfer. This is the first 3-dimensional vascular anatomical study to comprehensively document the vascular anatomy of the SFAP flap.
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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 | 0.002 | 0.001 |
| 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".