Computed Tomographic Angiography for Localization of the Cutaneous Perforators of the Leg
Bibliographic record
Abstract
BACKGROUND: Results of vascular anatomical studies of the lower limb in the past have been primarily descriptive in nature and are therefore less useful in directing the design of local perforator-based flaps. The purpose of this study was to document the three-dimensional anatomy of the cutaneous perforators arising from the anterior tibial, posterior tibial, and peroneal arteries and provide a statistically verified method for predicting perforator location for use in the clinical setting. METHODS: Computed tomographic angiography and three-dimensional reconstructions of the lower limb using Mimics software were completed for five lead oxide-injected cadavers. The cutaneous perforators of the vessels of the tibial trunk were identified, and perforator diameter, course, and location relative to leg length were determined. Cluster analysis was performed to evaluate the consistency of perforator locations across individuals. RESULTS: The anterior tibial artery had the greatest number of perforator vessels, which clustered into three groups centered at 83 ± 6 percent (percent of tibial height ± SD), 59 ± 7 percent, and 28 ± 9 percent. Peroneal artery perforators were clustered in two groups centered at 61 ± 9 percent and 27 ± 11 percent. The posterior tibial artery perforators could also be divided into two groups; however, a larger SD in the two groups suggests that perforators arising from this vessel are more evenly spaced. CONCLUSIONS: Statistical analysis demonstrated that the major perforator vessels of the tibial trunk are conserved across individuals and can be reliably dissected using the cluster's statistical distribution. Results of this study will allow for better preoperative planning of local flaps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".