The epidemiology of acne vulgaris in a multiethnic adolescent population from Rotterdam, the Netherlands: A cross-sectional study.

BACKGROUND: Although acne is a prevalent multifactorial inflammatory skin condition, few studies were performed in multiethnic populations. OBJECTIVES: To study the prevalence and determinants of acne in a multiethnic study at the start of puberty. METHODS: This cross-sectional study is embedded in Generation R, a population-based prospective study from Rotterdam, the Netherlands. Three-dimensional facial photos at the center visit in 2016-2019 (of ∼13-year-olds) were used to grade acne severity using the Global Evaluation of the Acne Severity (GEA). Analyses were stratified by biological sex and explored through chi-square tests and multivariable ordinal logistic regression. RESULTS: A total of 4561 children (51% girls) with a median age of 13.5 (IQR 13.3-13.6) were included. The visible acne prevalence (GEA 2-5) for girls vs boys was 62% vs 45% and moderate-to-severe acne (GEA 3-5) 14% vs 9%. Higher puberty stages (adjusted odds ratios: 1.38 [1.20-1.59] and 2.16 [1.86-2.51] for girls and boys, respectively) and darker skin colors V and VI (adjusted odds ratios: 1.90 [1.17-3.08] and 2.43 [1.67-3.56]) were associated with more severe acne in both sexes, and being overweight in boys (adjusted odds ratio: 1.58 [1.15-2.17]). LIMITATIONS: Cross-sectional design. CONCLUSIONS: Acne prevalence was high at the age of 13 years and was associated with advanced puberty, darker skin color, and weight status.

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.

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.

Predicting the evolution of clinical skin aging in a multi-ethnic population: Developing causal Bayesian networks using dermatological expertise.

INTRODUCTION: Software to predict the impact of aging on physical appearance is increasingly popular. But it does not consider the complex interplay of factors that contribute to skin aging. OBJECTIVES: To predict the +15-year progression of clinical signs of skin aging by developing Causal Bayesian Belief Networks (CBBNs) using expert knowledge from dermatologists. MATERIAL AND METHODS: Structures and conditional probability distributions were elicited worldwide from dermatologists with experience of at least 15 years in aesthetics. CBBN models were built for all phototypes and for ages ranging from 18 to 65 years, focusing on wrinkles, pigmentary heterogeneity and facial ptosis. Models were also evaluated by a group of independent dermatologists ensuring the quality of prediction of the cumulative effects of extrinsic and intrinsic skin aging factors, especially the distribution of scores for clinical signs 15 years after the initial assessment. RESULTS: For easiness, only models on African skins are presented in this paper. The forehead wrinkle evolution model has been detailed. Specific atlas and extrinsic factors of facial aging were used for this skin type. But the prediction method has been validated for all phototypes, and for all clinical signs of facial aging. CONCLUSION: This method proposes a skin aging model that predicts the aging process for each clinical sign, considering endogenous and exogenous factors. It simulates aging curves according to lifestyle. It can be used as a preventive tool and could be coupled with a generative AI algorithm to visualize aging and, potentially, other skin conditions, using appropriate images.

In vivo multiphoton imaging for non-invasive time course assessment of retinoids effects on human skin.

BACKGROUND: In vivo multiphoton imaging and automatic 3D image processing tools provide quantitative information on human skin constituents. These multiphoton-based tools allowed evidencing retinoids epidermal effects in the occlusive patch test protocol developed for antiaging products screening. This study aimed at investigating their relevance for non-invasive, time course assessment of retinoids cutaneous effects under real-life conditions for one year. MATERIALS AND METHODS: Thirty women, 55-65 y, applied either retinol (RO 0.3%) or retinoic acid (RA 0.025%) on one forearm dorsal side versus a control product on the other forearm once a day for 1 year. In vivo multiphoton imaging was performed every three months, and biopsies were taken after 1 year. Epidermal thickness and dermal-epidermal junction undulation were estimated in 3D with multiphoton and in 2D with histology, whereas global melanin density and its z-epidermal distribution were estimated using 3D multiphoton image processing tools. RESULTS: Main results after one year were as follows: a) epidermal thickening with RO (+30%); b) slight increase in dermal-epidermal junction undulation with RO; c) slight decrease in 3D melanin density with RA; d) limitation of the melanin ascent observed with seasonality and time within supra-basal layers with both retinoids, using multiphoton 3D-melanin z-epidermal profile. CONCLUSIONS: With a novel 3D descriptor of melanin z-epidermal distribution, in vivo multiphoton imaging allows demonstrating that daily usage of retinoids counteracts aging by acting not only on epidermal morphology, but also on melanin that is shown to accumulate in the supra-basal layers with time.

In vivo multiphoton multiparametric 3D quantification of human skin aging on forearm and face.

Quantifying skin aging changes and characterizing its 3D structure and function in a non-invasive way is still a challenging area of research, constantly evolving with the development of imaging methods and image analysis tools. In vivo multiphoton imaging offers means to assess skin constituents in 3D, however prior skin aging studies mostly focused on 2D analyses of dermal fibers through their signals' intensities or densities. In this work, we designed and implemented multiphoton multiparametric 3D quantification tools for in vivo human skin pigmentation and aging characterization. We first demonstrated that despite the limited field of view of the technic, investigation of 2 regions of interest (ROIs) per zone per volunteer is a good compromise in assessing 3D skin constituents in both epidermis and superficial dermis. We then characterized skin aging on different UV exposed areas-ventral and dorsal forearms, face. The three major facts of aging that are epidermal atrophy, the dermal-epidermal junction (DEJ) flattening and dermal elastosis can be non-invasively quantified and compared. Epidermal morphological changes occur late and were only objectified between extreme age groups. Melanin accumulation in suprabasal layers with age and chronic exposure on ventral and dorsal forearms is less known and appears earlier. Superficial dermal aging changes are mainly elastin density increase, with no obvious change in collagen density, reflected by SHGto2PEF ratio and SAAID index decrease and ImbrN index increase on all skin areas. Analysis of the z-dermal distribution of these parameters highlighted the 2nd 20 µm thickness normalized dermal sub-layer, that follows the DEJ shape, as exhibiting the highest aging differences. Moreover, the 3D ImbrN index allows refining the share of photoaging in global aging on face and the 3D SAAID index on forearm, which elastin or fibrillar collagens densities alone do not allow. Photoaging of the temple area evolves as a function of chronic exposure with a more pronounced increase in elastin density, also structurally modified from thin and straight elastic fibers in young volunteers to dense and compact pattern in older ones. More generally, multiphoton multiparametric 3D skin quantification offers rich spatial information of interest in assessing normal human skin condition and its pathological, external environment or product induced changes.