The Change of Plane of the Supratrochlear and Supraorbital Arteries in the Forehead—An Ultrasound-Based Investigation
Bibliographic record
Abstract
BACKGROUND: Injecting soft tissue fillers into the deep plane of the forehead carries the risk of injection-related visual compromise due to the specific course of the arterial vasculature. OBJECTIVES: The aim of this study was to investigate the 2- and 3-dimensional location of the change of plane of the deep branch of the supratrochlear and supraorbital artery, respectively. METHODS: A total of 50 patients (11 males and 39 females; mean age, 49.76 [13.8] years, mean body mass index, 22.53 [2.6] kg/m2) were investigated with ultrasound imaging. The total thickness and the distance of the arteries from the skin and bone surface were measured with an 18-MHz broadband compact linear array transducer. RESULTS: The deep branch of the supraorbital artery changed plane from deep to superficial to the frontalis muscle at a mean distance of 13 mm (range, 7.0-19.0 mm) in males and at 14 mm (range, 4.0-24.0 mm) in females and for the deep branch of the supratrochlear artery at a mean distance of 14 mm in males and females (range, 10.0-19.0 in males, 4.0-27.0 in females) when measured from the superior orbital rim. CONCLUSIONS: Based on the ultrasound findings in this study, it seems that the supraperiosteal plane of the upper and lower forehead could be targeted during soft tissue filler injections because the deep branches of both the supraorbital and supratrochlear arteries do not travel within this plane. The superficial plane of the lower forehead, however, should be avoided due to the unpredictability and inconsistent presence of the central and paracentral arteries.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".