Increasing Precision When Targeting the Depressor Anguli Oris Muscle With Neuromodulators: An Ultrasound-Based Investigation
Bibliographic record
Abstract
BACKGROUND: Neuromodulator treatments of the perioral region are increasingly popular and aim to modulate the position of the modiolus. The predominantly targeted muscle is the depressor anguli oris (DAO) which allows for the modiolus to reposition cranially once temporarily relaxed. OBJECTIVES: The aim of this study was to identify the precise anatomic position of the DAO in relation to the marionette line, thereby increasing precision and reducing adverse events during neuromodulator treatments. METHODS: A total of n = 80 DAO muscles were investigated in n = 40 healthy, toxin-naïve volunteers (11 males, 29 females) with a mean [standard deviation] age of 48.15 [15] years and a mean BMI of 24.07 [3.7] kg/m2. The location of the DAO in relation to the labiomandibular sulcus, and its depth, extent, and thickness were investigated with high-frequency ultrasound imaging. RESULTS: The skin surface projection of the labiomandibular sulcus separates the DAO into medial and lateral portions. The distance between skin surface and muscle surface was on average 4.4 mm, with males having a greater distance (P < .001) and higher BMI being an important influencing factor for a greater distance (P < .001). The thickness of the DAO was on average 3.5 mm, with a range of 2.8 to 4.8 mm and with females having thinner muscles compared with males (P < .001). The most favorable injection depth was calculated to be 6.1 mm for intramuscular product placement. CONCLUSIONS: Understanding the perioral anatomy and the influence of age, sex, and BMI will potentially allow injectors to increase the efficacy and duration of neuromodulator treatments while expertly managing adverse events.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".