Superoxide Dismutase-Mimetic Polyphenol-Based Carbon Dots for Multimodal Bioimaging and Treatment of Atopic Dermatitis.

Polyphenols have been investigated for their potential to mitigate inflammation in the context of atopic dermatitis (AD). In this study, epigallocatechin-3-gallate (EGCG)-based carbon dots (EGCG@CDs) were developed to enhance transdermal penetration, reduce inflammation, recapitulate superoxide dismutase (SOD) activity, and provide antimicrobial effects for AD treatment. The water-soluble EGCG@CDs in a few nanometers size exhibit a negative zeta potential, making them suitable for effective transdermal penetration. The fluorescence properties, including an upconversion effect, make EGCG@CDs suitable imaging probes for both in vitro and in vivo applications. By mimicking the SOD enzyme, EGCG@CDs scavenge reactive oxygen species (ROS) and actively produce hydrogen peroxide through a highly catalytic capability toward the oxygen reduction reaction, resulting in the inhibition of bacterial growth. The enhanced antioxidant properties, high charge mobility, and various functional groups of EGCG@CDs prove effective in reducing intracellular ROS in an in vitro AD model. In the mouse AD model, EGCG@CDs incorporated into a hydrogel actively penetrated the epidermal layer, leading to ROS scavenging, reduced mast cell activation, and histological recovery of skin barriers. This research represents the versatile potential of EGCG@CDs in addressing AD and advancing tissue engineering.

Parameter-based transfer learning for severity classification of atopic dermatitis using hyperspectral imaging.

BACKGROUND/PURPOSE: Because atopic dermatitis (AD) is a chronic inflammatory skin condition that causes structural changes, there is a growing need for noninvasive research methods to evaluate this condition. Hyperspectral imaging (HSI) captures skin structure features by exploiting light wavelength variations in penetration depth. In this study, parameter-based transfer learning was deployed to classify the severity of AD using HSI. Therefore, we aimed to obtain an optimal combination of classification results from the four models after constructing different source- and target-domain datasets. METHODS: We designated psoriasis, skin cancer, eczema, and AD datasets as the source datasets, and the set of images acquired via hyperspectral camera as the target dataset for wavelength-specific AD classification. We compared the severity classification performances of 96 combinations of sources, models, and targets. RESULTS: The highest classification performance of 83% was achieved when ResNet50 was trained on the augmented psoriasis dataset as the source, with the resulting parameters used to train the model on the target Near-infrared radiation (NIR) dataset. The second highest classification accuracy of 81% was achieved when ResNet50 was trained on the unaugmented psoriasis dataset as the source, with the resulting parameters used to train the model on the target R dataset. ResNet50 demonstrated potential as a generalized model for both the source and target data, also confirming that the psoriasis dataset is an effective training resource. CONCLUSION: The present study not only demonstrates the feasibility of the severity classification of AD based on hyperspectral images, but also showcases combinations and research scalability for domain exploration.

Hyperspectral imaging-based erythema classification in atopic dermatitis.

BACKGROUND/PURPOSE: Among the characteristics that appear in the epidermis of the skin, erythema is primarily evaluated through qualitative scales, such as visual assessment (VA). However, VA is not ideal because it relies on the experience and skill of dermatologists. In this study, we propose a new evaluation method based on hyperspectral imaging (HSI) to improve the accuracy of erythema diagnosis in clinical settings and investigate the applicability of HSI to skin evaluation. METHODS: For this study, 23 subjects diagnosed with atopic dermatitis were recruited. The inside of the right arm is selected as the target area and photographed using a hyperspectral camera (HS). Subsequently, based on the erythema severity visually assessed by a dermatologist, the severity classification performance of the RGB and HS images is compared. RESULTS: Erythema severity is classified as high when using (i) all reflectances of the entire HSI band and (ii) a combination of color features (R of RGB, a* of CIEL*a*b*) and five selected bands through band selection. However, as the number of features increases, the amount of calculation increases and becomes inefficient; therefore, (ii), which uses only seven features, is considered to perform classification more efficiently than (i), which uses 150 features. CONCLUSION: In conclusion, we demonstrate that HSI can be applied to erythema severity classification, which can further increase the accuracy and reliability of diagnosis when combined with other features observed in erythema. Additionally, the scope of its application can be expanded to various studies related to skin pigmentation.

Zinc penetration through the skin barrier in atopic dermatitis and rosacea using reflectance confocal microscopy.

Atopic dermatitis (AD) is a chronic, recurrent eczematous disorder with a complex pathophysiology caused by skin barrier abnormalities. Rosacea is a common chronic immune-mediated inflammatory disorder that results in diminished skin barrier function. Reflectance confocal microscopy (RCM) is a non-invasive method for visualizing the dynamic status of epidermal and upper dermal structures. In this study, we compared skin barrier permeability among normal, AD and rosacea groups. To assess skin barrier permeability, zinc was applied to lesional skin and the RCM reflectance intensity of zinc penetration was measured. Reflectance confocal microscopy revealed that the intensity in patients with rosacea and AD was higher than that in the normal group at depths of 8-24 µm in both the face and forearm, which were considered as the stratum corneum (SC) and tight junction (TJ) level (p < 0.0001). When comparing AD and rosacea, the intensity of rosacea was higher than that of AD at a depth of 8 µm in the face (p < 0.0001). The intensity of AD was higher than that of rosacea at a depth of 24 µm (p = 0.009). This suggests that skin barrier permeability is increased in the upper epidermis of patients with AD and rosacea. On the face, patients with rosacea had more SC weakness than did those with AD, whereas patients with AD had more TJ weakness than those with rosacea.

Abnormal brain structure in atopic dermatitis: Evidence from Mendelian randomization study.

BACKGROUND: Structural abnormalities in the brain of patients with atopic dermatitis (AD) have been reported; however, the cause has not been determined yet. Herein, we used Mendelian randomization (MR) to reveal the causal effect of AD on brain structure. METHODS: This study utilized summary statistics from genome-wide association studies (GWASs) to investigate a collection of cerebral structural measures, encompassing cortical thickness (CT), cortical surface area (CA), and subcortical volumes in T1 images. A comprehensive GWAS meta-analysis identified a total of 20 independent single nucleotide polymorphisms linked to AD, surpassing the genome-wide significance threshold (p < 5 × 10⁻8). MR estimates were aggregated through the application of the inverse variance weighted method. Additional complementary analyses (i.e., MR-Egger and weighted median approaches) were conducted to further assess the robustness of the obtained results. Sensitivity analysis and multivariate MR (MVMR) while adjusting for brain structural changes risk factors (i.e., depression and anxiety) were performed to assess the reliability and stability of observed causality. RESULTS: Genetically determined AD exhibited a causal link with reduced caudate volumes (IVW-MR: ß = -0.186, p = 0.001, p-corrected = 0.009). Furthermore, we identified potential causal associations between AD and reduced CT in the cingulate region (posterior cingulate, IVW-MR: ß = -0.065, p = 0.018, p-corrected = 0.551; isthmus cingulate, IVW-MR: ß = -0.086, p = 0.003, p-corrected = 0.188), as well as abnormal cortical surface area (CA) in the supramarginal (IVW-MR: ß = -0.047, p = 0.044, p-corrected = 0.714) and isthmus cingulate (IVW-MR: ß = 0.053, p = 0.018, p-corrected = 0.714). Additional supplementary analyses yielded consistent outcomes. There was no evidence of horizontal pleiotropy. MVMR analysis showed that the causal effects of AD on abnormal brain structure remained significant while adjusting for depression and anxiety. CONCLUSION: This MR study provided suggestive evidence that decreased caudate nucleus, posterior cingulate cortex, isthmus cingulate cortex and supramarginal gyrus are suggestively associated with higher AD risk. Future investigation into the brain regions is recommended, which helps to clarify the underlying mechanisms and point to new therapies against AD.

Analysis of skin aging patterns using a facial imaging system in patients with atopic dermatitis.

BACKGROUND: There are few studies on skin aging in patients with atopic dermatitis (AD). OBJECTIVES: To clarify the characteristics of facial skin aging in AD patients. MATERIALS & METHODS: Using facial images obtained by a digital imaging system (VISIA evolution), we compared the severity scores for 10 aging signs in 53 women in the AD group and 29 women in the healthy control group, all 35-49 years old. RESULTS: The severity scores for fine lines on the forehead, periorbital wrinkles, nasolabial folds, and texture of the mouth contour were significantly higher in the AD group than in the controls. However, in order to exclude a direct effect of dermatitis at the time of measurement, cases with signs of AD at the evaluation site were excluded from the AD group (defined as the AD [non-lesion] group), revealing no statistical significance between the AD (non-lesion) group and the healthy control group for any of the 10 facial signs. Age subset analysis showed that for individuals in their late 40s, the AD (non-lesion) group exhibited significantly higher scores for crow's feet wrinkle and nasolabial fold compared to the healthy control group. Furthermore, these two scores correlated with one other, suggesting that they may be induced by the same factors. CONCLUSION: The results of this study show that skin aging associated with AD is prominent in areas prone to transient wrinkling by frequent blinking and speaking or facial expressions. Understanding of the need for appropriate AD treatment from a cosmetic perspective may increase patient adherence.

High-frequency ultrasound biomicroscopy findings of the skin of dogs with atopic dermatitis.

BACKGROUND: The high-frequency ultrasonographic appearance of skin of dogs with atopic dermatitis (cAD) has not been described. OBJECTIVES: To compare high-frequency ultrasonographic findings among lesional, macroscopically nonlesional skin of dogs with cAD, and the macroscopically nonlesional skin of healthy dogs. Additionally, to determine whether there is any correlation between the ultrasonographic findings in lesional skin and local Canine Atopic Dermatitis Extent and Severity Index, 4th iteration (CADESI-04) or its domains (erythema, lichenification, excoriations/alopecia). As a secondary aim, six cAD dogs were re-evaluated after management intervention. ANIMALS: Twenty dogs with cAD (six were re-examined after treatment) and six healthy dogs. MATERIALS AND METHODS: In all dogs, ultrasonographic examination was performed on the same 10 skin sites, using a 50 MHz transducer. Wrinkling of skin surface, presence/width of subepidermal low echogenic band, hypoechogenicity of dermis and thickness of the skin were evaluated and scored/measured blindly. RESULTS: Dermal hypoechogenicity was more common and severe in lesional compared to macroscopically nonlesional skin of dogs with cAD. In lesional skin, presence/severity of wrinkling of skin surface and of dermal hypoechogenicity were positively correlated with presence/severity of lichenification, while severity of dermal hypoechogenicity was positively correlated with local CADESI-04. A positive correlation between the change in skin thickness and the change in the severity of erythema during treatment was noted. CONCLUSIONS AND CLINICAL RELEVANCE: High-frequency ultrasound biomicroscopy may be useful for the evaluation of skin of dogs with cAD and for evaluating the progression of skin lesions during treatment.

Improve the dupilumab therapy evaluation with dermoscopy and high-frequency ultrasound in moderate-to-severe atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory disease. Monoclonal antibody dupilumab was approved to treat moderate-to-severe AD in recent years. An objective assessment of treatment response by skin imaging modality is adjuvant for clinical evaluations. This study aimed to explore the value of dermoscopy and high-frequency ultrasound (HFUS) imaging characteristics in treatment evaluation for moderate-to-severe AD patients treated with dupilumab. METHODS: Moderate-to-severe AD patients refractory to conventional therapy were enrolled in the study. All patients went through at least a 16-week standardized treatment of dupilumab. Clinical scores (eczema area scoring index [EASI], SCOARD, numerical rating scale of pruritus, dermatology life quality index), dermoscopy, and HFUS examinations were conducted at 0, 2, 4, 8, 12, and 16 weeks of treatment. Erythema, scales, erosion, and pigmentation under dermoscopy were scored, and subepidermal low-echogenic band (SLEB) thickness under HFUS was measured as quantitative indexes. Descriptive analysis and mixed effect linear regression models were used for statistical analysis. RESULTS: Sixteen patients were enrolled in the study and their average age was 45.63 ± 18.18 years. All clinical scores decreased with significant difference after 16-week treatment compared with baseline. All patients achieved EASI 50 (EASI score decreased by 50% or more), and 9/16 patients reached EASI 75 after 16-week treatment. Dermoscopy evaluation of erythema, scales and erosion scores were decreased, and the sign of pigmentation score was increased after treatment. For HFUS, the mean SLEB value was 0.51 ± 0.29 mm and decreased to 0.27 ± 0.15 mm after 16-week treatment (p < 0.01). SLEB value decreased linearly with treatment time and correlated with clinical scores. However, SLEB values of two patients were 0.57 and 0.68 mm at week 16, respectively, which were higher than the average, and one of the patients showed EASI 75. CONCLUSION: Dermoscopy and HFUS were able to reveal deeper inflammation response than clinical scores in AD and can be an effective method to evaluate and monitor clinical improvement during dupilumab treatment for AD patients. The preliminary value of imaging methods for predicting the treatment endpoint of dupilumab remains to be verified.

Machine Learning Assisted Handheld Confocal Raman Micro-Spectroscopy for Identification of Clinically Relevant Atopic Eczema Biomarkers.

Atopic dermatitis (AD) is a common chronic inflammatory skin dermatosis condition due to skin barrier dysfunction that causes itchy, red, swollen, and cracked skin. Currently, AD severity clinical scores are subjected to intra- and inter-observer differences. There is a need for an objective scoring method that is sensitive to skin barrier differences. The aim of this study was to evaluate the relevant skin chemical biomarkers in AD patients. We used confocal Raman micro-spectroscopy and advanced machine learning methods as means to classify eczema patients and healthy controls with sufficient sensitivity and specificity. Raman spectra at different skin depths were acquired from subjects' lower volar forearm location using an in-house developed handheld confocal Raman micro-spectroscopy system. The Raman spectra corresponding to the skin surface from all the subjects were further analyzed through partial least squares discriminant analysis, a binary classification model allowing the classification between eczema and healthy subjects with a sensitivity and specificity of 0.94 and 0.85, respectively, using stratified K-fold (K = 10) cross-validation. The variable importance in the projection score from the partial least squares discriminant analysis classification model further elucidated the role of important stratum corneum proteins and lipids in distinguishing two subject groups.

Altered resting-state functional connectivity of default mode network in brachioradial pruritus.

BACKGROUND: Patients with chronic pruritus (CP) have a low quality of life, thus it is important to gain a better understanding of the underlying processes. Previous functional magnetic resonance imaging studies at rest (rsfMRI) have shown that mainly areas associated with the default mode network (DMN), sensorimotor (SMN), frontoparietal (FPN) and salience networks (SN) are involved in the processing of itch in patients with chronic pruritus (CP), as well as the cortico-striatal circuit, which is involved in the motoric preparation of scratching. rsfMRI studies on functional connectivity (FC) patterns of resting-state networks (RSNs) in patients with inflammatory atopic dermatitis (AD) or with neuropathic brachioradial pruritus (BRP) compared with healthy controls (HC) are lacking. OBJECTIVES: The main goals of this study were to investigate whether functional connectivity within networks and areas associated with itch detection and processing are altered in patients with AD and BRP compared with matched healthy controls by rsfMRI, respectively. METHODS: Patients with AD (n = 28) and with BRP (n = 28) were compared with corresponding matched healthy controls by rsfMRI. Group-specific RSNs were identified by independent component analysis (ICA) and between-group differences in the RSNs were analysed by dual regression technique. Seed-based functional connectivity was analysed in several itch-related brain regions belonging to the DMN, SN and FPN, respectively. RESULTS: ICA and seed-based analyses revealed decreased functional connectivity in BRP compared with HC specially within the DMN including the precuneus and cingulate cortex. For AD patients in comparison with HC, as well as when BRP and AD patients were compared directly, no significant FC differences at rest were seen. CONCLUSIONS: Our findings point towards decreased FC particularly in the DMN at rest in patients with BRP. These results seem to indicate that central connectivity patterns at rest differentially encode itch in BRP and AD.

ECHO project in atopic dermatitis in Argentina: An innovative strategy to reach underserved areas with up to date knowledge, first year of experience.

BACKGROUND: The ECHO® (Extension for Community Healthcare Outcomes) project is a model of distance medical education developed in the United States to support health professionals in the management of patients with complex diseases. Since 2019, it has been implemented in atopic dermatitis (AD) in Argentina. The program consists of the periodic presentation of clinical cases by videoconference, virtual classes, and a permanently available open chat between professionals in charge of patients with AD and a group of experts. OBJECTIVE: The objective of this study was to analyze the impact of the ECHO Project AD on the medical knowledge and medical skills of Argentinian health professionals when treating patients with AD. METHODS: A survey was carried out among the participants in order to evaluate the impact of the program on the care of patients with AD. RESULTS: ECHO Project AD revealed a significant improvement in the management of patients with AD. The program contributed to the interpretation and use of severity scores, use of phototherapy, and management and prescription of both classic and innovative topical and systemic treatments. STUDY LIMITATIONS: The reduced number of participants and the short period of time. The answers of the survey may be biased by the enthusiasm of the participants. CONCLUSIONS: The ECHO project is an educational tool that enhances the medical skills of doctors and institutions, in which a climate of a partnership comes first and the participants look forward to learning from experiences, successes, and mistakes from one another, producing a scientific hub in constant evolution.

Mild to moderate atopic dermatitis severity can be reliably assessed using smartphone-photographs taken by the patient at home: A validation study.

BACKGROUND: The use of photographs to diagnose and monitor skin diseases is gaining ground. OBJECTIVES: To investigate the validity and reliability of photographic assessments of atopic dermatitis (AD) severity. METHODS: AD severity was evaluated in the clinic by two assessors using the Eczema Area and Severity Index (EASI), SCOring Atopic Dermatitis (SCORAD), and Investigator's Global Assessment (IGA). Participants photographed the lesions with their own smartphone and completed a questionnaire about the extent of eczema the same day from home. The photographs were assessed twice with an 8 weeks interval by five dermatologists experienced in photographic evaluations. Intraclass correlation coefficients (ICC) with 95% confidence interval (CI) were applied. RESULTS: Seventy-nine participants were enrolled. The ICC between clinical EASI and photographic EASI was 0.88 (95% CI 0.81-0.93), and 0.86 (0.70-0.93) between clinical SCORAD and photographic SCORAD. Perfect agreement between clinical IGA and photograph IGA was observed for 62%, with the difference between the two never deviating with more than 1 score. The inter-rater ICC for photographic EASI and photographic SCORAD, respectively, was 0.90 (0.85-0.94), and 0.96 (0.91-0.98). The intra-rater agreements between the first and second assessments varied from 0.95 to 0.98 for photographic EASI, and from 0.86 to 0.94 for photographic SCORAD. CONCLUSION: There was high agreement between mild to moderate AD severity assessed clinically and based on smartphone photographs. Further, the photographic assessments can be reproduced with high reliability.

Assessment of nail findings in children with atopic dermatitis.

BACKGROUND: Cutaneous findings are well known in atopic dermatitis (AD), but nail changes have not received as much attention. AIM: To determine the clinical and disease-related capillaroscopic findings of nail findings in paediatric patients with AD. METHODS: In total, 100 participants aged 2-16 years were sourced from the dermatology outpatient clinic: 50 of these had been diagnosed with AD according to the Hanifin-Rajka criteria, and the others were 50 healthy controls (HCs) without AD. The AD severity score (SCORing Atopic Dermatitis; SCORAD) was calculated for all patients with AD. A digital epiluminescence device was used for nailfold capillaroscopy. RESULTS: The nail findings detected in patients with AD were pitting, punctate leuconychia, trachyonychia, onycholysis and onychomadesis. Pitting was significantly (P < 0.01) more frequent in the patient group (26%) than in the HC group (6%). Similarly, the patient group had significantly higher rates for capillary density decrease (P < 0.01), capillary array irregularity (P < 0.001), capillary dilatation increase (P < 0.001), tortuosity (P = 0.04), ramification increase (P = 0.02), bush-like appearance (P = 0.02) and avascular areas (P < 0.01). Significant correlations were determined between pitting and trachyonychia (P < 0.05, r = 0.21), capillary density decrease (P < 0.05, r = 0.25), avascular areas (P < 0.001; r = 0.29) and SCORAD (P < 0.05, r = 0.35). CONCLUSION: The nailfold capillaroscopic images of children with AD were similar to those of scleroderma spectrum disorder. Thus, we believe it would be beneficial to support detailed clinical examination of patients with a capillaroscopic examination.

Deep learning approach to skin layers segmentation in inflammatory dermatoses.

Monitoring skin layers with medical imaging is critical to diagnosing and treating patients with chronic inflammatory skin diseases. The high-frequency ultrasound (HFUS) makes it possible to monitor skin condition in different dermatoses. Accurate and reliable segmentation of skin layers in patients with atopic dermatitis or psoriasis enables the assessment of the treatment effect by the layer thickness measurements. The epidermis and the subepidermal low echogenic band (SLEB) are the most important for further diagnosis since their appearance is an indicator of different skin problems. In medical practice, the analysis, including segmentation, is usually performed manually by the physician with all drawbacks of such an approach, e.g., extensive time consumption and lack of repeatability. Recently, HFUS becomes common in dermatological practice, yet it is barely supported by the development of automated analysis tools. To meet the need for skin layer segmentation and measurement, we developed an automated segmentation method of both epidermis and SLEB layers. It consists of a fuzzy c-means clustering-based preprocessing step followed by a U-shaped convolutional neural network. The network employs batch normalization layers adjusting and scaling the activation to make the segmentation more robust. The obtained segmentation results are verified and compared to the current state-of-the-art methods addressing the skin layer segmentation. The obtained Dice coefficient equal to 0.87 and 0.83 for the epidermis and SLEB, respectively, proves the developed framework's efficiency, outperforming the other approaches.

Automated severity scoring of atopic dermatitis patients by a deep neural network.

Scoring atopic dermatitis (AD) severity with the Eczema Area and Severity Index (EASI) in an objective and reproducible manner is challenging. Automated measurement of erythema, papulation, excoriation, and lichenification severity using images has not yet been investigated. Our aim was to determine whether convolutional neural networks (CNNs) could assess erythema, papulation, excoriation, and lichenification severity at a level of competence comparable to dermatologists. We created a standard dataset of 8,000 clinical images showing AD. Each component of the EASI was scored from 0 to 3 by three dermatologists. We trained four CNNs (ResNet V1, ResNet V2, GoogLeNet, and VGG-Net) with the image dataset and determined which CNN was the most suitable for erythema, papulation, excoriation, and lichenification scoring. The brightness of the images in each dataset was adjusted to - 80% to + 80% of the original brightness (i.e., 9 levels by 20%) to investigate if the CNNs accurately measured scores if image brightness levels were changed. Compared to the dermatologists' scoring, accuracy rates of the CNNs were 99.17% for erythema, 93.17% for papulation, 96.00% for excoriation, and 97.17% for lichenification. CNNs trained with brightness-adjusted images achieved a high accuracy without the need to standardize camera settings. These results suggested that CNNs perform at level of competence comparable to dermatologists for scoring erythema, papulation, excoriation, and lichenification severity.

In vivo non-invasive staining-free visualization of dermal mast cells in healthy, allergy and mastocytosis humans using two-photon fluorescence lifetime imaging.

Mast cells (MCs) are multifunctional cells of the immune system and are found in skin and all major tissues of the body. They contribute to the pathology of several diseases including urticaria, psoriasis, atopic dermatitis and mastocytosis where they are increased at lesional sites. Histomorphometric analysis of skin biopsies serves as a routine method for the assessment of MC numbers and their activation status, which comes with major limitations. As of now, non-invasive techniques to study MCs in vivo are not available. Here, we describe a label-free imaging technique to visualize MCs and their activation status in the human papillary dermis in vivo. This technique uses two-photon excited fluorescence lifetime imaging (TPE-FLIM) signatures, which are different for MCs and other dermal components. TPE-FLIM allows for the visualization and quantification of dermal MCs in healthy subjects and patients with skin diseases. Moreover, TPE-FLIM can differentiate between two MC populations in the papillary dermis in vivo-resting and activated MCs with a sensitivity of 0.81 and 0.87 and a specificity of 0.85 and 0.84, respectively. Results obtained on healthy volunteers and allergy and mastocytosis patients indicate the existence of other MC subpopulations within known resting and activated MC populations. The developed method may become an important tool for non-invasive in vivo diagnostics and therapy control in dermatology and immunology, which will help to better understand pathomechanisms involving MC accumulation, activation and degranulation and to characterize the effects of therapies that target MCs.

A Preliminary 18F-FDG-PET/MRI Study Shows Increased Vascular Inflammation in Moderate-to-Severe Atopic Dermatitis.

BACKGROUND: Recent data suggest that patients with atopic dermatitis (AD) have increased systemic immune activation and cardiovascular risk. However, unlike psoriasis, evaluation of active vascular inflammation using state-of-the-art imaging is lacking in AD. OBJECTIVE: To assess aortic and carotid vascular inflammation using 18F-fluorodeoxyglucose-positron emission tomography/magnetic resonance imaging (18F-FDG-PET/MRI) imaging in moderate-to-severe AD versus healthy individuals. METHODS: A total of 27 patients with moderate-to-severe AD and 12 healthy controls were imaged using 18F-FDG-PET/MRI. Target-to-background ratio (TBR) values were calculated in multiple segments of the aorta and carotid vessels. RESULTS: Patients with AD had elevated aortic max TBR (fold change [FCH] = 1.45, P = .057) versus healthy controls and significantly elevated mean TBR (FCH = 1.20; P < .05) in the right carotid (RC) arteries versus controls. When examining greatest focal inflammation (most diseased segment [MDS] TBR), patients with AD had higher aortic inflammation (FCH = 1.28; P = .052). AD clinical severity significantly correlated with C-reactive protein (ρ = 0.60, P < .01) and with RC mean TBR levels (ρ = 0.60, P = .04). Stratifying patients into moderate-to-severe and very severe AD showed greater RC mean TBR in patients with very severe AD versus controls (FCH = 1.31; P = .02) and versus patients with moderate/severe AD (FCH = 1.23, P = .05). Aortic inflammation was also significantly greater in patients with very severe AD versus controls (max TBR: FCH = 1.6, P = .04; MDS TBR: FCH = 1.73, P = .03). CONCLUSIONS: This preliminary study is the first that establishes greater vascular (aorta and carotid) inflammation in moderate-to-severe AD versus healthy controls. Furthermore, very severe AD showed higher inflammation than both moderate/severe patients and healthy controls. Future studies with larger patient cohorts and evaluation before and after treatment are needed to determine the extent to which vascular inflammation in AD is modifiable.

Artificial Intelligence in Multiphoton Tomography: Atopic Dermatitis Diagnosis.

The diagnostic possibilities of multiphoton tomography (MPT) in dermatology have already been demonstrated. Nevertheless, the analysis of MPT data is still time-consuming and operator dependent. We propose a fully automatic approach based on convolutional neural networks (CNNs) to fully realize the potential of MPT. In total, 3,663 MPT images combining both morphological and metabolic information were acquired from atopic dermatitis (AD) patients and healthy volunteers. These were used to train and tune CNNs to detect the presence of living cells, and if so, to diagnose AD, independently of imaged layer or position. The proposed algorithm correctly diagnosed AD in 97.0 ± 0.2% of all images presenting living cells. The diagnosis was obtained with a sensitivity of 0.966 ± 0.003, specificity of 0.977 ± 0.003 and F-score of 0.964 ± 0.002. Relevance propagation by deep Taylor decomposition was used to enhance the algorithm's interpretability. Obtained heatmaps show what aspects of the images are important for a given classification. We showed that MPT imaging can be combined with artificial intelligence to successfully diagnose AD. The proposed approach serves as a framework for the automatic diagnosis of skin disorders using MPT.

Microscopic and functional changes observed with dynamic optical coherence tomography for severe refractory atopic dermatitis treated with dupilumab.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory disease. Recently, dupilumab was approved for moderate-to-severe AD. D-OCT is a noninvasive tool for the characterization of skin diseases. OBJECTIVE: To describe the changes observed with D-OCT in lesional and clinically healthy skin of patients with refractory severe AD under dupilumab treatment. METHODS: We analyzed AD lesions and healthy skin by D-OCT. Clinical scores of AD severity were assessed at baseline (T0) and after 1 and 3 months of treatment (T1, T2). Descriptive statistics, chi-square test, and t test were used to compare the analyzed parameters over time and between AD lesions and clinically healthy skin. RESULTS: At baseline, average EASI was 45.7. During the follow-up, EASI75 and EASI90 were achieved in 57% and 36% of patients at T1 and 100% and 86% of patients at T2, respectively. Lesional skin D-OCT parameters related to epidermal remodeling and inflammation evidenced a significant improvement after 1 month of treatment. In clinically healthy skin, D-OCT parameters improved significantly after 3 months of treatment, especially for collagen remodeling and inflammation. CONCLUSION: The study demonstrates that the clinical improvement of severe AD patients under dupilumab treatment is correlated with specific D-OCT changes of patients' lesional and clinically healthy skin.

Ultrasonography patterns of atopic dermatitis in children.

BACKGROUND: Atopic dermatitis (AD) is one of the most common allergic diseases in children. The aim of the study was to evaluate the ultrasound picture of lesional and non-lesional skin in children with AD. MATERIALS AND METHODS: The study included a group of children with AD and a control group. Inclusion criteria were as follows: age 0-8 years and clinical diagnosis of AD. An ultrasound scanner with a 75 MHz transducer probe was used to produce B-mode skin images in lesions and non-lesional skin. The thickness and the echogenicity of epidermis, dermis, and subepidermal low-echogenic band (SLEB) were measured, and the ratio coefficient per body site was calculated. RESULTS: Ultrasonography of non-lesional skin in children with AD showed uneven epidermis contour, a tendency to increased epidermis and decreased dermis thickness, and the SLEB was observed in 77% of cases. In lesions, there was an increased thickness and a decreased echogenicity of epidermis and dermis, and epidermis had irregular contours in most cases. The SLEB was in all lesions, showing greater thickness and lower echogenicity compared with non-lesional skin. CONCLUSION: HF-USG of the skin allows visualizing the epidermal barrier disruption and inflammation in dermis in children with AD on the entire surface of the skin.