Amelanotic Lentigo Maligna Melanoma: Mohs Surgery as the Definitive Treatment of an Invisible Tumour
Bibliographic record
Abstract
Amelanotic lentigo maligna melanoma represents <2% of melanomas. Diagnosis is delayed owing to the lack of lesion pigmentation and advanced disease at presentation. Excision with appropriate margins is the treatment standard, but the starting point for such margins is often unclear. We describe 2 patients with amelanotic melanoma treated by Mohs micrographic surgery (MMS) that would not have been cleared by wide local excision alone and provide an extensive review of the literature. Both patients presented with histologic diagnoses of malignant melanoma, one with a barely perceptible biopsy site scar on the left infraorbital cheek/lower eyelid (Breslow 1.8 mm) and the second with an amelanotic tumour on the right helix (Breslow 10 mm). Due to location, aggressive histology, amelanotic appearance, and no apparent surrounding skin surface changes, MMS was elected to maximise margin control. For patient 1, invasive and in situ tumour was found at the American Joint Committee on Cancer-recommended margin of 1.5 cm, and the final defect measured 8.5 × 4.8 cm. Patient 2 had a significant invasive and amelanotic lentigo maligna component, resulting in a 9.0 × 6.5-cm defect. MMS allows for immediate histologic feedback on tumour margins of a clinically invisible tumour and thus offers the most definitive treatment.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".