Novel Stereoscopic Optical System for Objectively Measuring Above-Surface Scar Volume—First-Time Quantification of Responses to Various Treatment Modalities
Bibliographic record
Abstract
BACKGROUND: Current approaches use subjective semiquantitative or cumbersome objective methodologies to assess physical characteristics of hypertrophic and keloid scars. OBJECTIVE: This pilot study aimed to evaluate the accuracy and feasibility of a new stereoscopic optical and high-resolution 3-dimensional imaging system, for objectively measuring changes in above-surface scar volume after various interventions. METHODS: Feasibility and accuracy were assessed by monitoring the above-surface scar volume of 5 scars in 2 patients for 5 successive months. Above-surface scar volume and Vancouver Scar Scale scores and the investigator and patient volume improvement assessment scores were assessed before and 12 weeks after last intervention. RESULTS: Scar volume measured by the imaging system correlated significantly with the gold standard (actual weight). The greatest volume reduction followed a combination of cryotherapy and intralesional triamcinolone acetonide and 5-fluorouracil injections in Patient 1 and a combination of pulse dye laser and intralesional triamcinolone acetonide injections in Patient 2. CONCLUSION: The new stereoscopic optical system is a valid, accurate, and practical objective method for assessing scar volume and for monitoring treatment response. It is more sensitive and accurate than semiquantitative objective scales. Further studies with a higher number of patients and scars are required to increase the measurement validity of the system.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".