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Record W4412166799 · doi:10.1017/cjn.2025.10272

P.118 A rare case of eccrine carcinoma with perineural metastases - a rare cause of facial pain

2025· article· en· W4412166799 on OpenAlexaffvenue
Olga Marushchak, Laila Alshafai

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer and Skin Lesions
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsMedicinePerineural invasionDermatologyFacial painSurgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

Background: Eccrine carcinoma is a rare skin tumor arising in eccrine sweat glands with a predilection for older adults. Over 30% of cases occur in the head and neck. Local and distal metastases are common. Prognosis is poor with regional recurrence in up to 19% of cases. Imaging is indicated in high-risk disease. Methods: We present a case report of eccrine carcinoma in the scalp with perineural metastasis to the left trigeminal nerve. Results: A seventy-nine-year-old male with a history of left temporal scalp pre-cancerous lesion treated with liquid nitrogen two years prior presented with left facial pain and paresthesia. The gadolinium-enhanced MRI head showed a tiny sub-centimetre spiculated subcutaneous lesion in the left temporal scalp and perineural enhancement along the left auricotemporal, V3 and trigeminal nerves. Subsequent excisional biopsy of the temporal lesion showed a poorly differentiated eccrine carcinoma without local perineural invasion. Conclusions: Undifferentiated facial pain is a frequent indication for head imaging, usually with low diagnostic utility. However, scrutiny for perineural enhancement is necessary to avoid missing a potentially deadly process. Eccrine carcinoma is a rare type of skin cancer. Small, painless, indolent primary lesions may be overlooked clinically. Radiologists can affect outcomes in these cases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.299
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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