Pitfalls in the diagnosis of lentigo maligna and lentigo maligna melanoma, facts and an opinion
Bibliographic record
Abstract
Lentigo maligna/lentigo maligna melanoma (LM/LMM) affects chronically sun-damaged skin of the head and neck with a slow radial growth phase. It is characterised by predominantly lentiginous proliferation of small, but atypical melanocytes with occasional upward scatter in an atrophic epidermis. It is not uncommon for pathologists to receive partial or scouting biopsies to assess for LM. This makes the interpretation of symmetry and circumscription of the lesions challenging. Therefore, both cytologic and architectural criteria should be taken into consideration to render an accurate diagnosis of melanoma. Moreover, pathologists should be vigilant to avoid missing invasion, as this can change the treatment plan and prognosis. Herein, we aim to discuss important pitfalls in the diagnosis of LMM and its invasive component. Some of these caveats are differentiating between true invasion versus adnexal involvement by the in situ component or an incidental intradermal nevus, detection of microinvasion and multifocal invasion, and recognition of desmoplastic/spindle cell melanoma component.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".