Evidence map›Paper›PMID 41624622›Full record

ArticleBiomedical reports2026

Personalized surveillance in giant congenital melanocytic nevus, including the role of AI, histopathology and MC1R genotyping: A case report.

Preslav Vasilev, Ivelina Yordanova, Savelina Popovska, Zornitsa Kamburova

Abstract readCase Reports
In one paragraph

Article in Biomedical reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Preslav VasilevDepartment of Dermatology, Venereology and Allergology, Faculty of Medicine, Medical University-Pleven, 5800 Pleven, Bulgaria.
Ivelina YordanovaDepartment of Dermatology, Venereology and Allergology, Faculty of Medicine, Medical University-Pleven, 5800 Pleven, Bulgaria.
Savelina PopovskaDepartment of General and Clinical Pathology, Faculty of Medicine, Medical University-Pleven, 5800 Pleven, Bulgaria.
Zornitsa KamburovaCentre of Competence in Personalized Medicine, 3D and Telemedicine, Robotic Assisted and Minimally Invasive Surgery-'Leonardo da Vinci', 5800 Pleven, Bulgaria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Giant congenital melanocytic nevi (GCMN) are rare pigmented skin lesions present at birth that carry an increased risk of malignant melanoma and neurocutaneous melanosis. Early diagnosis and long-term follow-up care are essential for high-risk patients. The combination of modern imaging techniques with genetic testing can enable a more comprehensive risk assessment. The present case describes a 55-year-old woman with a bathing-trunk-type GCMN and >30 additional nevi. The patient was monitored using total body mapping combined with artificial intelligence (AI)-assisted dermoscopy (MoleAnalyzer Pro; FotoFinder Systems GmbH). Due to suspicious features, several lesions were surgically excised. Histopathology revealed a rare plexiform melanocytic schwannoma with low proliferative activity, showing immunopositivity for S100 protein and SOX10, with focal expression of Melan-A (MART-1). Germline testing by next-generation sequencing identified two high-risk melanocortin 1 receptor (MC1R) variants, p.Arg151Cys and p.Arg160Trp, in compound heterozygous state, both associated with melanoma susceptibility. No pathogenic variants were detected in NRAS or BRAF. The present case highlighted the integrative value of AI-assisted dermoscopy, histopathology, and genetic profiling in the surveillance of patients with GCMN. Compound heterozygosity for MC1R high-risk alleles may explain the extensive nevus burden and support intensified surveillance. Personalized follow-up strategies guided by advanced imaging and genomics can improve early detection and prevention of melanoma.

Indexed as

artificial intelligence dermoscopygiant congenital melanocytic nevusMC1R genemelanoma risknext-generation sequencingpersonalized surveillance

Identifiers

PMID41624622
PMCPMC12856533

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.