Epidermal renewal during the treatment of atopic dermatitis lesions: A study coupling line-field confocal optical coherence tomography with artificial intelligence quantifications: LC-OCT reveals new biological markers of AD

Abstract

Objective: This study explores the application of Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging coupled with artificial intelligence (AI)-based algorithms to investigate atopic dermatitis (AD), a common inflammatory dermatosis.

Materials and methods: AD acute and chronic lesions (ADL) were compared to clinically healthy-looking skin (ADNL). LC-OCT was used noninvasively and in real-time to image the skin of AD patients during flare-ups and monitor remissions under topical steroid treatment for 2 weeks. Quantitative parameters were extracted from the images, including morphological and cellular-level markers of epidermal architecture. A novel cellular-level parameter, nuclei "atypia," which quantifies the orderliness of epidermal renewal, was used to highlight abnormal maturation processes.

Results: Compared to healthy skin, AD lesions exhibited significant increases in both epidermal and stratum corneum (SC) thickness, along with a more undulated dermo-epidermal junction (DEJ). Additionally, keratinocyte nuclei (KN) were larger, less compact, and less organized in lesional areas, as indicated by the atypia parameter. A higher degree of atypia was observed in chronic lesions compared to acute ones. Following treatment, all the parameters normalized to levels observed in healthy skin within 2 weeks, mirroring clinical improvements.

Conclusion: This study provides insights into the quantification of epidermal renewal using a noninvasive imaging technique, highlighting differences between ADL/ADNL and acute/chronic lesions. It also presents the AD treatment mechanism, paving the way for future investigations on AD and other skin barrier function-related conditions.

Keywords: LC‐OCT; artificial intelligence; atopic dermatitis; biomarkers; corticosteroids; epidermis.

FIGURE 1

(A) Macroscopic pictures of ADL and ADNL areas at D00 (ankle, subject 1). (B) Corresponding vertical LC‐OCT cross‐sections (C—D) Corresponding 3D LC‐OCT stacks. Using an AI‐based algorithm, the skin layers have been segmented (green) and in (C) the KN is sorted by size (red, blue, yellow), and in (D) the atypia parameter is calculated. ADL, AD acute and chronic lesions; AI, artificial intelligence; KN, keratinocyte nuclei; LC‐OCT, line‐field confocal optical coherence tomography.

FIGURE 2

Histological metrics (viable epidermis thickness, SC thickness, and DEJ undulation) at baseline and after 7 and 14 days of topical steroids treatment for lesional skin (ADL) and control healthy‐looking areas (ADNL). The stars indicate the effect size (*** very strong, ** strong, *moderate) whenever the p‐value is significant (p‐value < 5%). ADL, AD acute and chronic lesions; DEJ, dermal–epidermal junction; SC, stratum corneum.

FIGURE 3

Layer‐by‐layer analysis of KN volume, compactness, and atypia for ADL and ADNL areas, from the top of the viable epidermis (layer 0) to deeper levels. The three parameters are represented at baseline (left) and after one (middle) and 2 weeks (right) of treatment. The stars indicate the effect size (*** very strong, ** strong, *moderate,—weak) when the p‐value is significant (< 5%). ADL, AD acute and chronic lesions; KN, keratinocyte nuclei.

FIGURE 4

KN atypia for ADL and ADNL at different layers of the epidermis from top (0) to bottom (12). Atypia is represented at D00 (acute N = 16/chronic N = 6), D07 (acute N = 16/chronic N = 4), and D14 (acute N = 15/chronic N = 3), after the beginning of topical steroid treatment. Statistics compared acute versus chronic lesions at D00 and D07. At D14, the number of chronic lesions no longer allowed for a robust conclusion. The stars indicate the effect size (*** very strong, ** strong, *moderate) whenever the p‐value is significant (p‐value < 5%). ADL, AD acute and chronic lesions; KN, keratinocyte nuclei.