ArticleOral and maxillofacial surgery2026
Exploratory systematic characterization of vascular features in confocal laser endomicroscopy of cutaneous squamous cell carcinoma.
Article in Oral and maxillofacial surgery, 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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Abstract
purposeThis exploratory study aimed to systematically evaluate vascular features in confocal laser endomicroscopy (CLE) for distinguishing cutaneous squamous cell carcinoma (cSCC) from healthy skin, assessing both the overall diagnostic value of these features using a composite vascular scoring system and the performance of individual criteria.
methodsCLE video sequences of tumor and corresponding healthy skin were retrospectively analyzed in nine patients, using histopathology as the reference standard. Six vascular criteria were defined from the literature, three associated with healthy tissue and three with tumor tissue. Three experienced investigators performed a blinded assessment, and a majority decision determined the presence of each criterion. Sensitivity, specificity, predictive values, and interrater agreement were calculated. A composite vascular score (0-6) was derived, and ROC analysis was used to determine the optimal cutoff for discriminating tumor from healthy tissue.
resultsThe features with the highest diagnostic relevance were "honeycomb-like capillaries" and "round vascular structures" for healthy tissue, and "leaky capillaries" for tumor sequences. ROC analysis identified a cutoff of ≥ 3 (Youden index 0.905, AUC 0.96). Within the analyzed dataset, the composite vascular score achieved a sensitivity of 100%, specificity of 90.48%, PPV of 91.3%, and NPV of 100%.
conclusionVascular features captured by CLE showed promising discriminatory potential for differentiating cSCC from healthy skin. Among the individual criteria, absence of "honeycomb-like pattern" of capillaries and "round vascular structures" are particularly suitable for inclusion in a CLE-based scoring system for cSCC.
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