Non-invasive characterization of the relationship between skin microrelief and dermal-epidermal junction topography using line-field confocal optical coherence tomography (LC-OCT).

Non-invasive technologies for observing internal skin structures without damaging the surface have advanced in recent years. However, an integrated understanding of internal structures together with the morphology of surface "microrelief"-the surface pattern consisting of furrows and ridges (i.e., sulci cutis and cristae cutis)-remains limited. We elucidated the relationship between internal skin structure and microrelief by combining line-field confocal optical coherence tomography (LC-OCT) with a proprietary AI system. We applied a semantic segmentation-based image AI system to LC-OCT data from 11 adults. The system extracted the coordinates of sulci cutis, stratum corneum thickness, viable epidermal thickness, and dermal-epidermal junction (DEJ) topography. The analysis revealed that the skin surface and DEJ in sulci cutis were nearly parallel. The DEJ undulation index in cristae cutis correlated with epidermal thickness, stratum corneum multilayering rate, and ceramide subclass parameters. We verified the relationship between the skin surface and the DEJ structure by incorporating positional information of the microrelief. LC-OCT combined with AI-based analysis provides a non-invasive approach to link age-related changes in DEJ structure with alterations in microrelief and related biomarkers.