Ultra‐High Frequency Ultrasound in Melanoma Management
Bibliographic record
Abstract
OBJECTIVES: The main aim of this study is to evaluate the correspondence between the ultrasonographic thickness and the Breslow thickness in melanoma using ultra-high frequency ultrasound and the intra- and inter-operator repeatability in the ultrasonographic measurements of melanoma depth. Moreover, we propose a new protocol based on a combined ultrasonographic-histopathological approach. METHODS: We analyzed 27 melanomas in a population consisted of 27 patients (mean age 57.6 years, 51.8% males), who came at the Department of Dermatology (University of Pisa, Pisa, Italy) from April 2016 to March 2018 and had an ultrasonographic examination of a suspected lesion before the surgical removal using ultra-high frequency ultrasound (Vevo®MD, Fujifilm, Visualsonics, Toronto, Canada; 70 MHz probe). B-mode images were analyzed by two skilled and blinded operators, and the maximum depth of the lesions was measured using a dedicated graphical user interface developed in Matlab R2016b (MathWorks Inc., Natick, MA), to obtain repetitive measurements. RESULTS: All melanomas appeared as band-like or oval/fusiform shaped hypoechoic inhomogeneous lesions. We observed an excellent agreement between the Breslow thickness of melanomas and the ultrasonographic thickness, as well as a reduced intra- and inter-operator variability in the ultrasonographic measurements of melanoma depth. CONCLUSIONS: We propose a ultrasonographic-histopathological protocol which may help clinicians to reduce the diagnostic delay, improve prognosis and survival rates, perform a surgical excision with negative margins, and reduce the variability in the assessment of Breslow thickness.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".