Prognostic Significance of Vascularity in Cutaneous Melanoma: Pilot Study Using in Vivo Confocal Scanning Laser Microscopy
Bibliographic record
Abstract
BACKGROUND: Tumor vascularity may be of strong prognostic significance in cutaneous melanoma. We are the first to use a novel, noninvasive, in vivo confocal scanning laser microscope (CSLM) to evaluate vascularity in cutaneous melanoma. OBJECTIVE: Our purpose was to apply a CSLM to assess vascularity in melanoma and to evaluate the prognostic significance of these findings. METHODS: Patients with a suspicious pigmented lesion were prospectively recruited to undergo CSLM prior to skin biopsy, and those diagnosed with melanoma were included in this study. A blinded observer graded tumor vascularity from still digital CSLM images. The CSLM vascularity grading was correlated to tumor thickness and ulceration as a proxy for clinical prognosis. RESULTS: Sixty-six patients and 67 lesions underwent imaging with CSLM. Eleven patients were diagnosed with melanoma, including six in situ and five invasive melanomas. Prominent vascularity was observed in all advanced melanomas. There was an overall increase in mean tumor thickness between the absent (x = 0.315 mm) to prominent (x = 1.51 mm) categories. CONCLUSION: In this pilot study, vascularity was readily detected in cutaneous melanomas using CSLM. Prominent vascularity was observed in patients with advanced cutaneous melanomas. Our preliminary results are encouraging and indicate potential for the use of CSLM to assess vascularity in cutaneous melanoma, with potential prognostic and therapeutic implications.
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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 | 0.002 |
| 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 | 0.000 |
| 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".