Artificial intelligence-driven skin aging simulation as a novel skin cancer prevention.

INTRODUCTION: Skin cancer, a prevalent cancer type among fair-skinned patients globally, poses a relevant public health concern due to rising incidence rates. Ultraviolet (UV) radiation poses a major risk factor for skin cancer. However intentional tanning associated with sunburns remains a common practice, notably among female adults Appropriate prevention campaigns targeting children and adolescents are needed to improve sun-protection behavior particularly in these age groups. The aim of our study is to investigate if an AI-based simulation of facial skin aging can enhance sun-protection behavior in female adults. METHODS: In this single-center prospective observational pilot study at Department of Dermatology at the University Hospital of Basel, we took photographs of healthy young females' faces with a VISIA-CR camera (Canfield Scientific Inc., Parsippany, New Jersey, Version 8.2) between February to March 2021. Digital images were performed in three angles (straight, left 45°, right 45°). All participants received an AI-based simulation of their facial skin with continuous aging to 80 years. A newly created anonymous questionnaire capturing participants' sociodemographic data and also tanning and sun-protection behavior was completed in pre- and post-aging simulation. To observe long-term effects, a 2-year follow-up was conducted between March to April 2023. RESULTS: The 60 participants (mean age 23.6±2.5 years) evaluated the importance of sun-protection significantly higher after skin aging simulation with VISIA-CR camera (p<0.0001; 95%-CI:8.2-8.8). Post-intervention, 91.7% (55/60) of the females were motivated to reduce UV exposure and to intensify UV protection in the future since the individual UV-dependent risk was perceived significantly higher (p<0.001; 95%-CI: 5.9-6.7). At two-year follow-up, 96% (24/25) indicated persistent effort reducing UV exposure. The preference for SPF50+ sunscreen increased to 46.7% (28/65) directly after the skin-aging simulation and continued to rise up to 60.0% (15/25) after two years. CONCLUSIONS: Our data emphasize the potential of AI-assisted photo-aging interventions to enhance motivation for UV protection in the short and the long term We encourage that different age and gender groups are addressed in a personalized, generation-specific manner with the appropriate media and by considering the Hawthorne effect. Campaigns with visual AI support can improve the intent of cancer-preventative behavior.

Psoriasis localization patterns in the Swiss Psoriasis Registry (SDNTT) over 11 years: an analysis by sex and age.

Real-world data on anatomically localized psoriasis and its response to systemic therapy across different age-groups and sexes is limited. This study aimed to evaluate the severity and distribution of psoriasis over time in female and male patients receiving systemic therapies, categorized by age within the Swiss psoriasis registry (SDNTT). Patient-data was obtained over 11 years through the SDNTT. The localized Psoriasis Area and Severity Index (locPASI) of the head, trunk, upper and lower extremities was analyzed over two years following the start of systemic non-/biologic treatment. A total of 316 female and 517 male patients were analyzed. Male patients had a higher baseline locPASI for legs, trunk and arms (p < 0.001), but not for the head (p = 0.961). The locPASI for the head in younger female patients (18-40 years) had a higher score than those aged 55 + (p = 0.022) and after two years, middle aged (41-54) showed a lower score compared to younger patients (p = 0.045). Younger male patients revealed a lower score after two years of therapy in the leg- and arm-area compared to older (p = 0.018 and p = 0.048, respectively). Female patients on non-biologics had a fast initial response, converging with male patients' scores over 24 months. Over 75% locPASI reduction was observed for female head-area (81.4%), male trunk (82.7%) and legs (76.1%). Absolute locPASI ≤ 2 was achieved 3-6 months for all locations with interleukin (IL)-17, IL-12/23 and IL-23-inhibitors, except for the legs of male patients on anti-IL-17 and female patients on anti-IL-12/23 and -IL-23. After two years, male patients did not achieve a locPASI ≤ 2 for any biologic-treatment in the legs, nor for the arms on anti-TNF-α. Significant disparities in localized PASI were observed between female and male patients. The age, sex and severity of distinct localizations should be considered to optimize treatment goals.

MITF regulates IDH1, NNT, and a transcriptional program protecting melanoma from reactive oxygen species.

Microphthalmia-associated transcription factor (MITF) is a master regulator of melanocyte function, development and plays a significant role in melanoma pathogenesis. MITF genomic amplification promotes melanoma development, and it can facilitate resistance to multiple therapies. Here, we show that MITF regulates a global antioxidant program that increases survival of melanoma cell lines by protecting the cells from reactive oxygen species (ROS)-induced damage. In addition, this redox program is correlated with MITF expression in human melanoma cell lines and patient-derived melanoma samples. Using a zebrafish melanoma model, we show that MITF decreases ROS-mediated DNA damage in vivo. Some of the MITF target genes involved, such as IDH1 and NNT, are regulated through direct MITF binding to canonical enhancer box (E-BOX) sequences proximal to their promoters. Utilizing functional experiments, we demonstrate the role of MITF and its target genes in reducing cytosolic and mitochondrial ROS. Collectively, our data identify MITF as a significant driver of the cellular antioxidant state.

Predicting Psoriatic Arthritis in Psoriasis Patients - A Swiss Registry Study.

Background: Psoriatic arthritis (PsA) is a prevalent comorbidity among patients with psoriasis, heavily contributing to their burden of disease, usually diagnosed several years after the diagnosis of psoriasis. Objectives: To investigate the predictability of psoriatic arthritis in patients with psoriasis and to identify important predictors. Methods: Data from the Swiss Dermatology Network on Targeted Therapies (SDNTT) involving patients treated for psoriasis were utilized. A combination of gradient-boosted decision trees and mixed models was used to classify patients based on their diagnosis of PsA or its absence. The variables with the highest predictive power were identified. Time to PsA diagnosis was visualized with the Kaplan-Meier method and the relationship between severity of psoriasis and PsA was explored through quantile regression. Results: A diagnosis of psoriatic arthritis was registered at baseline of 407 (29.5%) treatment series. 516 patients had no registration of PsA, 257 patients had PsA at inclusion, and 91 patients were diagnosed with PsA after inclusion. The model's AUROCs was up to 73.7%, and variables with the highest discriminatory power were age, PASI, physical well-being, and severity of nail psoriasis. Among patients who developed PsA after inclusion, significantly more first treatment series were classified in the PsA-group, compared to those with no PsA registration. PASI was significantly correlated with the median burden/severity of PsA (P = .01). Conclusions: Distinguishing between patients with and without PsA based on clinical characteristics is feasible and even predicting future diagnoses of PsA is possible. Patients at higher risk can be identified using important predictors of PsA.

Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In recent years, image-based artificial intelligence (AI) applications have emerged as promising tools to assist physicians by offering improved accuracy and efficiency. In this review, we provide an overview of the current landscape of image-based AI applications in psoriasis. Emphasis is placed on machine learning (ML) algorithms, a key subset of AI, which enable automated pattern recognition for various tasks. Key AI applications in psoriasis include lesion detection and segmentation, differentiation from other skin conditions, subtype identification, automated area involvement, and severity scoring, as well as personalized treatment selection and response prediction. Furthermore, we discuss two commercially available systems that utilize standardized photo documentation, automated segmentation, and semi-automated Psoriasis Area and Severity Index (PASI) calculation for patient assessment and follow-up. Despite the promise of AI in this field, many challenges remain. These include the validation of current models, integration into clinical workflows, the current lack of diversity in training-set data, and the need for standardized imaging protocols. Addressing these issues is crucial for the successful implementation of AI technologies in clinical practice. Overall, we underscore the potential of AI to revolutionize psoriasis management, highlighting both the advancements and the hurdles that need to be overcome. As technology continues to evolve, AI is expected to significantly improve the accuracy, efficiency, and personalization of psoriasis treatment.

Predictors of initiating biologics in the treatment of psoriasis.

BACKGROUND: Biologics are among the most effective therapies for psoriasis. However, many patients are only introduced to them at advanced stages of the disease course. OBJECTIVES: Our aim was to identify predictors of initiating biologic therapy in patients with psoriasis and compare patients initiating biologics early versus late in their disease course. METHODS: Kaplan-Meier curves visualized time to biologic initiation, while Cox regression models further explored variables as predictors of biologic initiation. Mann-Whitney U and chi-squared tests compared patients who started biologics early with those who began biologics later in the disease course. RESULTS: Our primary analysis included 233 psoriasis patients. Cox regression showed that age at diagnosis (P = 0.007), general physical well-being (P = 0.02), and nail psoriasis severity (P = 0.02) were significantly associated with time to biologic initiation. Our secondary analysis, the comparisons between patients starting biologics early versus later in the disease course, included a total of 378 patients. The median (interquartile range [IQR]) age at diagnosis was 34.5 (25.0-51.2) years for patients initiating biologics within 5 years, compared to 22.0 (15.0-32.8) years for patients initiating biologics later (P < 0.0001). The median (IQR) age at initiation was 37.0 (27.0-53.2) and 45.0 (36.0-55.0) years for patients initiating biologics earlier versus later than 5 years (P = 0.04). CONCLUSIONS: Age at diagnosis, general well-being, and severity of nail psoriasis significantly predicted future initiation of biologic treatment. Patients initiating biologics early in their disease course were generally older at diagnosis but younger at the time of biologic initiation compared to patients initiating biologics later in their disease course.

The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection.

AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D ("Skin Lesion Image Crops Extracted from 3D TBP") dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world. De-identified images were systematically extracted from sensitive 3D Total Body Photographs and are comparable in optical resolution to smartphone images. Algorithms trained on lower quality images could improve clinical workflows and detect skin cancers earlier if deployed in primary care or non-clinical settings, where photos are captured by non-expert physicians or patients. Such a tool could prompt individuals to visit a specialized dermatologist. This dataset circumvents many inherent limitations of prior datasets and may be used to build upon previous applications of skin imaging for cancer detection.

Classification of melanocytic lesions using direct illumination multispectral imaging.

With rising melanoma incidence and mortality, early detection and surgical removal of primary lesions is essential. Multispectral imaging is a new, non-invasive technique that can facilitate skin cancer detection by measuring the reflectance spectra of biological tissues. Currently, incident illumination allows little light to be reflected from deeper skin layers due to high surface reflectance. A pilot study was conducted at the University Hospital Basel to evaluate, whether multispectral imaging with direct light coupling could extract more information from deeper skin layers for more accurate dignity classification of melanocytic lesions. 27 suspicious pigmented lesions from 23 patients were included (6 melanomas, 6 dysplastic nevi, 12 melanocytic nevi, 3 other). Lesions were imaged before excision using a prototype snapshot mosaic multispectral camera with incident and direct illumination with subsequent dignity classification by a pre-trained multispectral image analysis model. Using incident light, a sensitivity of 83.3% and a specificity of 58.8% were achieved compared to dignity as determined by histopathological examination. Direct light coupling resulted in a superior sensitivity of 100% and specificity of 82.4%. Convolutional neural network classification of corresponding red, green, and blue lesion images resulted in 16.7% lower sensitivity (83.3%, 5/6 malignant lesions detected) and 20.9% lower specificity (61.5%) compared to direct light coupling with multispectral image classification. Our results show that incorporating direct light multispectral imaging into the melanoma detection process could potentially increase the accuracy of dignity classification. This newly evaluated illumination method could improve multispectral applications in skin cancer detection. Further larger studies are needed to validate the camera prototype.

AI-powered visual diagnosis of vulvar lichen sclerosus: A pilot study.

BACKGROUND: Vulvar lichen sclerosus (VLS) is a chronic inflammatory skin condition associated with significant impairment of quality of life and potential risk of malignant transformation. However, diagnosis of VLS is often delayed due to its variable clinical presentation and shame-related late consultation. Machine learning (ML)-trained image recognition software could potentially facilitate early diagnosis of VLS. OBJECTIVE: To develop a ML-trained image-based model for the detection of VLS. METHODS: Images of both VLS and non-VLS anogenital skin were collected, anonymized, and selected. In the VLS images, 10 typical skin signs (whitening, hyperkeratosis, purpura/ecchymosis, erosion/ulcers/excoriation, erythema, labial fusion, narrowing of the introitus, labia minora resorption, posterior commissure (fourchette) band formation and atrophic shiny skin) were manually labelled. A deep convolutional neural network was built using the training set as input data and then evaluated using the test set, where the developed algorithm was run three times and the results were then averaged. RESULTS: A total of 684 VLS images and 403 non-VLS images (70% healthy vulva and 30% with other vulvar diseases) were included after the selection process. A deep learning algorithm was developed by training on 775 images (469 VLS and 306 non-VLS) and testing on 312 images (215 VLS and 97 non-VLS). This algorithm performed accurately in discriminating between VLS and non-VLS cases (including healthy individuals and non-VLS dermatoses), with mean values of 0.94, 0.99 and 0.95 for recall, precision and accuracy, respectively. CONCLUSION: This pilot project demonstrated that our image-based deep learning model can effectively discriminate between VLS and non-VLS skin, representing a promising tool for future use by clinicians and possibly patients. However, prospective studies are needed to validate the applicability and accuracy of our model in a real-world setting.

Targeting IL-1 controls refractory pityriasis rubra pilaris.

Pityriasis rubra pilaris (PRP) is a rare inflammatory skin disease with a poorly understood pathogenesis. Through a molecularly driven precision medicine approach and an extensive mechanistic pathway analysis in PRP skin samples, compared to psoriasis, atopic dermatitis, healed PRP, and healthy controls, we identified IL-1ß as a key mediator, orchestrating an NF-κB-mediated IL-1ß-CCL20 axis, including activation of CARD14 and NOD2. Treatment of three patients with the IL-1 antagonists anakinra and canakinumab resulted in rapid clinical improvement and reversal of the PRP-associated molecular signature with a 50% improvement in skin lesions after 2 to 3 weeks. This transcriptional signature was consistent with in vitro stimulation of keratinocytes with IL-1ß. With the central role of IL-1ß underscoring its potential as a therapeutic target, our findings propose a redefinition of PRP as an autoinflammatory keratinization disorder. Further clinical trials are needed to validate the efficacy of IL-1ß antagonists in PRP.

Janus Kinase Inhibitors as Successful Treatment Alternative in Dupilumab-Induced Psoriasis.

Introduction: After the introduction of dupilumab as systemic treatment for atopic dermatitis, an increasing number of patients have been successfully treated. However, reports of patients developing psoriasis as a secondary skin condition have been accumulating. The most likely reason is assumed to be an immune shift from Th2- to Th1-mediated auto-inflammatory processes. Case Presentation: Our patient is a 38-year-old male suffering from head-neck type atopic dermatitis since childhood. As one of the first patients in Switzerland, he received dupilumab in 2018 leading to a significant improvement of his skin lesions. One year later he developed progressing circular erythematous-squamous plaques which correlated histologically with psoriasis. In 2021, 3 years after initiating dupilumab, we switched systemic therapy to baricitinib. Three months after initiation, his psoriatic lesions were completely healed, while the atopic lesions remained stable with low inflammatory activity. Conclusion: In patients treated with dupilumab for atopic dermatitis immune shift needs to be considered in case of newly appearing skin lesions. With a growing number of described cases, we conclude that baricitinib is a good alternative treatment for atopic dermatitis in patients suffering from biologic-induced psoriasis.

MR1 Gene and Protein Expression Are Enhanced by Inhibition of the Extracellular Signal-Regulated Kinase ERK.

The MHC class I-related molecule MR1 is ubiquitously expressed, is highly conserved among mammals, and presents bacterial and endogenous antigens in tumor cells. These features indicate that tumor-specific T cells restricted to MR1 may represent ideal candidates for novel cancer-directed T-cell immunotherapy. The very low expression of the MR1 protein at the cell surface is a potential challenge limiting the possible use of MR1-directed immunotherapies. To overcome this challenge, it is important that understanding of the mechanisms regulating MR1 expression is increased, as little is known about this currently. This study identified ERK1/2 as negative regulators of the MR1 gene and protein expression. Inhibition of ERK1/2 in tumor cells or treatment of BRAF-mutant tumor cells with drugs specific for mutated BRAF increased MR1 protein expression and recognition by tumor-reactive and MR1-restricted T cells. The ERK1/2 inhibition of MR1 was mediated by the ELF1 transcription factor, which was required for MR1 gene expression. The effects of ERK1/2 inhibition also occurred in cancer cell lines of different tissue origins, cancer cell lines resistant to drugs that inhibit mutated BRAF, and primary cancer cells, making them potential targets of specific T cells. In contrast to tumor cells, the recognition of healthy cells was very poor or absent after ERK1/2 inhibition. These findings suggest a pharmaceutical approach to increase MR1 protein expression in tumor cells and the subsequent activation of MR1-restricted T cells, and they have potential therapeutic implications.

Device-based physical therapies in chronic pruritus: A narrative review.

Chronic pruritus is a highly prevalent disease associated with high psychosocial and economic burdens. In addition to pharmacological treatments, device-based physical therapies also offer antipruritic effects. Phototherapy, laser, electrical neurostimulation technologies, acupuncture, cryotherapy, and cold atmospheric plasma are, in part, still experimental but emerging treatment options that augment our repertoire to treat patients with chronic pruritus. In this narrative review, we provided an overview of these physical modalities and their role in itch management.

International Consensus Definition and Diagnostic Criteria for Generalized Pustular Psoriasis From the International Psoriasis Council.

Importance: Generalized pustular psoriasis (GPP) lacks internationally accepted definitions and diagnostic criteria, impeding timely diagnosis and treatment and hindering cross-regional clinical and epidemiological study comparisons. Objective: To develop an international consensus definition and diagnostic criteria for GPP using the modified Delphi method. Evidence Review: The rarity of GPP presents a challenge in acquiring comprehensive published clinical data necessary for developing standardized definition and criteria. Instead of relying on a literature search, 43 statements that comprehensively addressed the fundamental aspects of the definitions and diagnostic criteria for GPP were formulated based on expert reviews of 64 challenging GPP cases. These statements were presented to a panel of 33 global GPP experts for voting, discussion, and refinements in 2 virtual consensus meetings. Consensus during voting was defined as at least 80% agreement; the definition and diagnostic criteria were accepted by all panelists after voting and in-depth discussion. Findings: In the first and second modified Delphi round, 30 (91%) and 25 (76%) experts participated. In the initial Delphi round, consensus was achieved for 53% of the statements, leading to the approval of 23 statements that were utilized to develop the proposed definitions and diagnostic criteria for GPP. During the second Delphi round, the final definition established was, "Generalized Pustular Psoriasis is a systemic inflammatory disease characterized by cutaneous erythema and macroscopically visible sterile pustules." It can occur with or without systemic symptoms, other psoriasis types, and laboratory abnormalities. GPP may manifest as an acute form with widespread pustules or a subacute variant with an annular phenotype. The identified essential criterion was, "Macroscopically visible sterile pustules on erythematous base and not restricted to the acral region or within psoriatic plaques." Conclusions and Relevance: The achievement of international consensus on the definition and diagnostic criteria for GPP underscores the importance of collaboration, innovative methodology, and expert engagement to address rare diseases. Although further validation is needed, these criteria can serve as a reference point for clinicians, researchers, and patients, which may contribute to more accurate diagnosis and improved management of GPP.

Variations of skin thermal diffusivity on different skin regions.

BACKGROUND AND OBJECTIVE: Skin thermal diffusivity plays a crucial role in various applications, including laser therapy and cryogenic skin cooling.This study investigates the correlation between skin thermal diffusivity and two important skin parameters, melanin content and erythema, in a cohort of 102 participants. METHODS: An in-house developed device based on transient temperature measurement was used to assess thermal diffusivity at different body locations. Melanin content and erythema were measured using a colorimeter. Statistical analysis was performed to examine potential correlations. RESULTS: The results showed that the measured thermal diffusivity values were consistent with previous reports, with variations observed among subjects. No significant correlation was found between thermal diffusivity and melanin content or erythema. This suggests that other factors, such as skin hydration or epidermis thickness, may have a more dominant influence on skin thermal properties. CONLCUSION: This research provides valuable insights into the complex interplay between skin thermal properties and physiological parameters, with potential implications for cosmetic and clinical dermatology applications.

Performance of an automated total body mapping algorithm to detect melanocytic lesions of clinical relevance.

IMPORTANCE: Total body photography for skin cancer screening is a well-established tool allowing documentation and follow-up of the entire skin surface. Artificial intelligence-based systems are increasingly applied for automated lesion detection and diagnosis. DESIGN AND PATIENTS: In this prospective observational international multicentre study experienced dermatologists performed skin cancer screenings and identified clinically relevant melanocytic lesions (CRML, requiring biopsy or observation). Additionally, patients received 2D automated total body mapping (ATBM) with automated lesion detection (ATBM master, Fotofinder Systems GmbH). Primary endpoint was the percentage of CRML detected by the bodyscan software. Secondary endpoints included the percentage of correctly identified "new" and "changed" lesions during follow-up examinations. RESULTS: At baseline, dermatologists identified 1075 CRML in 236 patients and 999 CRML (92.9%) were also detected by the automated software. During follow-up examinations dermatologists identified 334 CRMLs in 55 patients, with 323 (96.7%) also being detected by ATBM with automated lesions detection. Moreover, all new (n = 13) or changed CRML (n = 24) during follow-up were detected by the software. Average time requirements per baseline examination was 14.1 min (95% CI [12.8-15.5]). Subgroup analysis of undetected lesions revealed either technical (e.g. covering by clothing, hair) or lesion-specific reasons (e.g. hypopigmentation, palmoplantar sites). CONCLUSIONS: ATBM with lesion detection software correctly detected the vast majority of CRML and new or changed CRML during follow-up examinations in a favourable amount of time. Our prospective international study underlines that automated lesion detection in TBP images is feasible, which is of relevance for developing AI-based skin cancer screenings.

Post-transplant Inflammatory Bowel Disease Associated with Donor-Derived TIM-3 Deficiency.

Inflammatory bowel disease (IBD) occurring following allogeneic stem cell transplantation (aSCT) is a very rare condition. The underlying pathogenesis needs to be better defined. There is currently no systematic effort to exclude loss- or gain-of-function mutations in immune-related genes in stem cell donors. This is despite the fact that more than 100 inborn errors of immunity may cause or contribute to IBD. We have molecularly characterized a patient who developed fulminant inflammatory bowel disease following aSCT with stable 100% donor-derived hematopoiesis. A pathogenic c.A291G; p.I97M HAVCR2 mutation encoding the immune checkpoint protein TIM-3 was identified in the patient's blood-derived DNA, while being absent in DNA derived from the skin. TIM-3 expression was much decreased in the patient's serum, and in vitro-activated patient-derived T cells expressed reduced TIM-3 levels. In contrast, T cell-intrinsic CD25 expression and production of inflammatory cytokines were preserved. TIM-3 expression was barely detectable in the immune cells of the patient's intestinal mucosa, while being detected unambiguously in the inflamed and non-inflamed colon from unrelated individuals. In conclusion, we report the first case of acquired, "transplanted" insufficiency of the regulatory TIM-3 checkpoint linked to post-aSCT IBD.