Characterization of the <scp>MSAP</scp> Flap in Head and Neck Surgical Oncology: A <scp>3D</scp> Cadaveric Study
Bibliographic record
Abstract
OBJECTIVES: The medial sural artery (MSA) perforator flap is a versatile free flap. However, the cutaneous perforators are not well characterized. The objectives of this pilot anatomical study were to: (1) visualize in three-dimensions, as in-situ, the origin, course, and distribution of the cutaneous perforators, (2) characterize the number and frequency of the perforators, and (3) quantify mean pedicle length. METHODS: Thirteen cadaveric specimens were dissected, digitized, and modeled in 3D. Three-dimensional models and dissection photographs were used to determine the origin, course, number, distribution, and pedicle length of MSA perforators. RESULTS: The most common pattern consisted of three perforators (39% of specimens). The maximum number of perforators identified was four (23%). The majority of specimens (92%) had a cutaneous perforator originating from the lateral branch of the MSA and coursed most frequently in the second (43%) and third (37%) quartiles of the length of the tibia. Mean pedicle length was 19.1 ± 6.9 cm. Perforators originating from the medial branch of the MSA were significantly (p < 0.05) shorter than those from the lateral branch and were found to course only in the first quartile. CONCLUSION: The 3D models constructed in this study provide a comprehensive overview of the location and course of the perforators, enabling measurement of parameters in 3D-space. Anatomical characterization of the MSA perforator flap using 3D analysis can assist reconstructive surgeons in understanding the relevant anatomy and optimizing the surgical technique for flap harvest. LEVEL OF EVIDENCE: N/A Laryngoscope, 134:4298-4303, 2024.
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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 | 0.000 | 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".