Morphologic Features of Cutaneous T-Cell Lymphomas Using Dermoscopy and High Frequency Ultrasound
Bibliographic record
Abstract
The diagnosis of cutaneous T-cell lymphomas (CTCL) is frequently delayed by a median of three years and requires the clinical evaluation of an experienced dermatologist and a confirmatory skin biopsy. Dermoscopy and high-frequency ultrasound (HFUS) represent two non-invasive diagnostic tools. While dermoscopy is inexpensive and widely used for the diagnosis of melanoma and non-melanoma skin cancers, HFUS of skin lymphomas represents a novel diagnostic approach that is not yet implemented in the routine dermatologic practice. The aim of our study was to prospectively assess skin lesions of patients with either CTCL patches or plaques with dermoscopy and HFUS and to compare the findings with atopic dermatitis (AD) and psoriasis. Thirteen patients with an established diagnosis of CTCL, psoriasis, or AD were studied: Dermoscopy features including spermatozoa-like structures and the presence of white scales could assist in differentiating between early-stage CTCL and AD. HFUS measurements of the skin thickness indicated increased epidermal-, thickness in CTCL, and psoriasis compared with AD. Our results support the use of dermoscopy as a useful tool to diagnose CTCL. HFUS could augment the dermatologic assessment, but further studies will be needed to define standardized parameters.
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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 | 0.002 | 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) | 0.001 | 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".