Epidemiology and Risk Factors of Actinic Keratosis. What is New for The Management for Sun-Damaged Skin.

Actinic keratosis (AK) is considered a chronic skin disease mostly caused by long-term exposure to UV radiation and other risk factors such as immunosuppression, leading to an individual susceptibility for skin cancer manifestation. The treatment of AK is laborious and costly, and the incidence of skin cancer is forecasted to double until the year 2030 in an aging society.Risk factors in AK for malignant transformation in cutaneous squamous cell carcinoma (cSCC) are not fully understood, but studies suggest that histological features, such as atypia in the basal epidermal third and basal proliferation (PRO score) in AK play a pivotal role for development of malignancy. As the clinical appearance of AK does not correlate with the risk for malignancy, guidelines suggest treating every single AK lesion upon diagnosis. Skin imaging techniques, such as line-field confocal optical coherence tomography (LC-OCT) can help to provide an individual holistic follow-up for AK lesions by non-invasive visualization of atypia and basal proliferation. A follow-up for patients with AK may be critical for treatment success in terms of strengthening therapy adherence. When AK presents therapy refractory, cSCC manifests in nearly 30% of the cases after several years. Patients with AK suffering from field cancerization and immunosuppression are susceptible for a severe course of disease including metastasis and high mortality rates. Those vulnerable subgroups benefit from close skin cancer screening, early adequate treatment and chemoprevention, such as niacinamide or acitretin. Skin cancer prevention is substantial. Primary prevention should include chemical and physical UV-light protection and avoidance of indoor tanning. Secondary prevention is essential in high-risk populations, such as fair skin type elderly men and STORs. Tertiary prevention should comprise adequate treatment strategies to prevent therapy resistance, reoccurrence and cSCC, especially when field cancerization and immunosuppression are present.

Diagnose und Therapie aktinischer Keratosen: Diagnosis and therapy of actinic keratosis.

Actinic keratosis (AK) is considered a chronic and recurring in situ skin neoplasia, with a possible transformation into invasive squamous cell carcinoma (SCC). Among others, predominant risk factors for development of AK are UV-light exposure and immunosuppression. Basal epidermal keratinocyte atypia (AK I) and proliferation (PRO Score) seem to drive malignant turnover, rather than clinical appearance of AK (Olsen I-III). Due to the invasiveness of punch biopsy, those histological criteria are not regularly assessed. Non-invasive imaging techniques, such as optical coherence tomography (OCT), reflectance confocal microscopy (RCM) and line-field confocal OCT (LC-OCT) are helpful to distinguish complex cases of AK, Bowen's disease and SCC. Moreover, LC-OCT can visualize the epidermis and the papillary dermis at cellular resolution, allowing real-time PRO Score assessment. The decision-making for implementation of therapy is still based on clinical risk factors, ranging from lesion- to field-targeted and ablative to non-ablative regimes, but in approximately 85% of the cases a recurrence of AK can be observed after a 1-year follow-up. The possible beneficial use of imaging techniques for a non-invasive follow-up of AK to detect recurrence or invasive progression early on should be subject to critical evaluation in further studies.

Diagnosis and therapy of actinic keratosis.

Actinic keratosis (AK) is considered a chronic and recurring in situ skin neoplasia, with a possible transformation into invasive squamous cell carcinoma (SCC). Among others, predominant risk factors for development of AK are UV-light exposure and immunosuppression. Basal epidermal keratinocyte atypia (AK I) and proliferation (PRO score) seem to drive malignant transformation, rather than clinical appearance of AK (Olsen I-III). Due to the invasiveness of punch biopsy, those histological criteria are not regularly assessed. Non-invasive imaging techniques, such as optical coherence tomography (OCT), reflectance confocal microscopy (RCM) and line-field confocal OCT (LC-OCT) are helpful to distinguish complex cases of AK, Bowen's disease, and SCC. Moreover, LC-OCT can visualize the epidermis and the papillary dermis at cellular resolution, allowing real-time PRO score assessment. The decision-making for implementation of therapy is still based on clinical risk factors, ranging from lesion- to field-targeted and ablative to non-ablative regimens, but in approximately 85% of the cases a recurrence of AK can be observed after a 1-year follow-up. The possible beneficial use of imaging techniques for a non-invasive follow-up of AK to detect recurrence or invasive progression early on should be subject to critical evaluation in further studies.

Differences in the annotation between facial images and videos for training an artificial intelligence for skin type determination.

BACKGROUND: The Grand-AID research project, consisting of GRANDEL-The Beautyness Company, the dermatology department of Augsburg University Hospital and the Chair of IT Infrastructure for Translational Medical Research at Augsburg University, is currently researching the development of a digital skin consultation tool that uses artificial intelligence (AI) to analyze the user's skin and ultimately perform a personalized skin analysis and a customized skin care routine. Training the AI requires annotation of various skin features on facial images. The central question is whether videos are better suited than static images for assessing dynamic parameters such as wrinkles and elasticity. For this purpose, a pilot study was carried out in which the annotations on images and videos were compared. MATERIALS AND METHODS: Standardized image sequences as well as a video with facial expressions were taken from 25 healthy volunteers. Four raters with dermatological expertise annotated eight features (wrinkles, redness, shine, pores, pigmentation spots, dark circles, skin sagging, and blemished skin) with a semi-quantitative and a linear scale in a cross-over design to evaluate differences between the image modalities and between the raters. RESULTS: In the videos, most parameters tended to be assessed with higher scores than in the images, and in some cases significantly. Furthermore, there were significant differences between the raters. CONCLUSION: The present study shows significant differences between the two evaluation methods using image or video analysis. In addition, the evaluation of the skin analysis depends on subjective criteria. Therefore, when training the AI, we recommend regular training of the annotating individuals and cross-validation of the annotation.