480 Elastography-Based Quantification of Burn Scar Stiffness
Bibliographic record
Abstract
The purpose of this study is to test the feasibility of using acoustic radiation force impulse (ARFI) ultrasound elastography to quantify the stiffness of hypertrophic burn scars. ARFI imaging is a non-invasive ultrasound technique that has been used to determine tissue stiffness in many fibroproliferative disorders including cutaneous scleroderma. Given that the technology is both objective and operator-independent, it has the potential to overcome the limitations inherent in using subjective clinical tools for assessing scar stiffness. Thirteen patients from the outpatient Burn Clinic at our tertiary pediatric hospital participated in this study. Only patients with a hypertrophic burn scar that was clinically diagnosed by a burn care specialist were eligible to participate. For each participant, a section of scar as well as a section of contralateral matched normal skin were marked for ultrasound measurement. ARFI ultrasound elastography was then carried out by a trained ultrasound technician to obtain values for the elastic modulus (E) of scar and control sites. Scar thickness was also measured using conventional gray-scale ultrasound. The Wilcoxon signed-rank test was used to compare scar and control sites and the Spearman’s correlation test was used to examine the relationship between scar stiffness and thickness. The results of this study show that hypertrophic scars are significantly stiffer than normal skin. More specifically, scarred areas were found to be approximately four times stiffer than the control sites (scar Emean = 42.68 kPa compared to control Emean = 10.05 kPa). Lastly, there was no correlation between scar stiffness and thickness (rs = 0.026; p > 0.05). We have shown that ARFI ultrasound elastography can be used to discriminate between scar and normal skin and should be considered a potentially valuable tool in the armamentarium of objective scar measures. Future research should focus on establishing reference data and determining the technology’s ability to detect scar changes over time and their responsiveness to treatment in longitudinal studies. The ability to objectively measure scar stiffness will allow clinicians to monitor scar progression (or regression) over time and evaluate response to treatment.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".