What does this research mean for the field?

Reflectance confocal microscopy (RCM) demonstrates higher observed diagnostic performance and inter-reader agreement compared to line-field confocal optical coherence tomography (LC-OCT) for evaluating facial and scalp lesions suspicious for basal cell carcinoma, though both modalities are useful second-level diagnostic adjuncts. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To compare the diagnostic performance, inter-reader agreement, and artificial intelligence integration of reflectance confocal microscopy (RCM) versus line-field confocal optical coherence tomography (LC-OCT) in equivocal facial and scalp lesions suspicious for basal cell carcinoma (BCC).

August 22, 2026International Journal of DermatologyOpen Access

Reflectance Confocal Microscopy Versus Line‐Field Confocal Optical Coherence Tomography in Facial and Scalp Lesions Suspicious for Basal Cell Carcinoma: A Histopathology‐Referenced Multi‐Reader Study

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Authors

LALuca Ambrosio EREmanuele Rovaldi CCClaudio Conforti

Discussion

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Overview

Observational study demonstrates higher diagnostic accuracy and reliability for reflectance confocal microscopy over line-field OCT in skin lesions, indicating greater value as a diagnostic adjunct.

Key Points

To compare the diagnostic performance, inter-reader agreement, and artificial intelligence integration of reflectance confocal microscopy (RCM) versus line-field confocal optical coherence tomography (LC-OCT) in equivocal facial and scalp lesions suspicious for basal cell carcinoma (BCC).
Retrospective comparative observational study evaluating 100 facial and scalp lesions (69 BCCs, 31 non-BCCs) imaged by RCM and LC-OCT prior to excisional biopsy.
Four blinded dermatologists (two experts, two non-experts) independently graded anonymized images with diagnostic confidence scoring, alongside a single operating point evaluation of an integrated LC-OCT artificial intelligence model.
Expert readers achieved higher mean sensitivity (95.7% vs. 86.2%), specificity (85.5% vs. 67.7%), and accuracy (92.5% vs. 80.5%) with RCM compared to LC-OCT.
Inter-reader agreement was substantially higher for RCM (Fleiss' κ = 0.809) compared to LC-OCT (Fleiss' κ = 0.563).
The integrated LC-OCT artificial intelligence model achieved 87.0% sensitivity, 83.9% specificity, and 86.0% overall accuracy.

Cite This Study

Ambrosio et al. (2026) studied this question.

synapsesocial.com/papers/6a895eaeca7ade938187ccf8 https://doi.org/10.1111/ijd.70648

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August 22, 2026International Journal of DermatologyOpen Access

Reflectance Confocal Microscopy Versus Line‐Field Confocal Optical Coherence Tomography in Facial and Scalp Lesions Suspicious for Basal Cell Carcinoma: A Histopathology‐Referenced Multi‐Reader Study

View Full Paper

Ask AI

Bookmark

Authors

LALuca Ambrosio EREmanuele Rovaldi CCClaudio Conforti

Discussion

Member takes

Overview

Observational study demonstrates higher diagnostic accuracy and reliability for reflectance confocal microscopy over line-field OCT in skin lesions, indicating greater value as a diagnostic adjunct.

Key Points

To compare the diagnostic performance, inter-reader agreement, and artificial intelligence integration of reflectance confocal microscopy (RCM) versus line-field confocal optical coherence tomography (LC-OCT) in equivocal facial and scalp lesions suspicious for basal cell carcinoma (BCC).
Retrospective comparative observational study evaluating 100 facial and scalp lesions (69 BCCs, 31 non-BCCs) imaged by RCM and LC-OCT prior to excisional biopsy.
Four blinded dermatologists (two experts, two non-experts) independently graded anonymized images with diagnostic confidence scoring, alongside a single operating point evaluation of an integrated LC-OCT artificial intelligence model.
Expert readers achieved higher mean sensitivity (95.7% vs. 86.2%), specificity (85.5% vs. 67.7%), and accuracy (92.5% vs. 80.5%) with RCM compared to LC-OCT.
Inter-reader agreement was substantially higher for RCM (Fleiss' κ = 0.809) compared to LC-OCT (Fleiss' κ = 0.563).
The integrated LC-OCT artificial intelligence model achieved 87.0% sensitivity, 83.9% specificity, and 86.0% overall accuracy.

Cite This Study

Ambrosio et al. (2026) studied this question.

synapsesocial.com/papers/6a895eaeca7ade938187ccf8 https://doi.org/10.1111/ijd.70648

Also Consider

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