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Background: The development of artificial intelligence (AI) is rapidly expanding, showing promise in the dermatological field. Skin checks are a resource‐heavy challenge that could potentially benefit from AI‐tool assistance, particularly if provided in widely available AI solutions. A novel smartphone application(app)‐based AI system, "SCAI," was developed and trained to recognize spots in paired images of skin, pursuing identification of new skin lesions. This pilot study aimed to investigate the feasibility of the SCAI‐app to identify simulated skin changes in vivo. Materials and methods: The study was conducted in a controlled setting with healthy volunteers and standardized, simulated skin changes (test spots), consisting of customized 3‐mm adhesive spots in three colors (black, brown, and red). Each volunteer had a total of eight test spots adhered to four areas on back and legs. The SCAI‐app collected smartphone‐ and template‐guided standardized images before and after test spot application, using its backend AI algorithms to identify changes between the paired images. Results: Twenty‐four volunteers were included, amounting to a total of 192 test spots. Overall, the detection algorithms identified test spots with a sensitivity of 92.0% (CI: 88.1–95.9) and a specificity of 95.5% (CI: 95.0–96.0). The SCAI‐app's positive predictive value was 38.0% (CI: 31.0–44.9), while the negative predictive value was 99.7% (CI: 99.0–100). Conclusion: This pilot study showed that SCAI‐app could detect simulated skin changes in a controlled in vivo setting. The app's feasibility in a clinical setting with real‐life skin lesions remains to be investigated, where the challenge with false positives in particular needs to be addressed. [ABSTRACT FROM AUTHOR]

Background/purpose: A number of publications have suggested that optical coherence tomography (OCT) has the potential for non-invasive diagnosis of skin cancer. Currently, individual diagnostic features do not appear sufficiently discriminatory. The combined use of several features may however be useful. Methods: OCT is based on infrared light, photonics and fibre optics. The system used has an axial resolution of 10 μm, lateral 20 μm. We investigated the combined use of several OCT features from basal cell carcinomas (BCC) and actinic keratosis (AK). We studied BCC (41) and AK (37) lesions in 34 consecutive patients. The diagnostic accuracy of the combined features was assessed using a machine-learning tool. Results: OCT images of normal skin typically exhibit a layered structure, not present in the lesions imaged. BCCs showed dark globules corresponding to basaloid islands and AKs showed white dots and streaks corresponding to hyperkeratosis. Differences in OCT morphology were not sufficient to differentiate BCC from AK by the naked eye. Machine-learning analysis suggests that when a multiplicity of features is used, correct classification accuracies of 73% (AK) and 81% (BCC) are achieved. Conclusion: The data extracted from individual OCT scans included both quantitative and qualitative measures, and at the current level of resolution, these single factors appear insufficient for diagnosis. Our approach suggests that it may be possible to extract diagnostic data from the overall architecture of the OCT images with a reasonable diagnostic accuracy when used in combination. [ABSTRACT FROM AUTHOR]

Background/aims: In order to monitor the dynamics of experimentally-induced cutaneous inflammation in humans, we developed an objective, computerized video-optical method for wheal and flare area determination. Methods: The method was used for evaluation of PAF-acether-induced experimental inflammations on the volar aspect of the forearms of human volunteers. The study design was double-blind, randomized, placebo-controlled. Repeated measurements can be performed, e.g., with intervals of 1 min to reveal the time-course of the inflammatory reaction. In the present study, the effect of topical application of creams containing 3 different concentrations of the putative anti-inflammatory drug sodium sucrose-sulphate (SoS) on cutaneous inflammation was investigated. Results: 30 min after intracutaneous PAF-acether injection, a statistically significantly increased (p<0.05) wheal area was found in skin sites treated by either 1%, 3% and 9% SoS cream, whereas no influence of sucrose-sulphate could be demonstrated on the flare area. The reduction of the wheal area was significantly faster in the SoS-treated areas than in the placebo (p<0.05). Conclusions: Computerized video-optical quantification of acute skin inflammatory reactions may be a suitable experimental tool for objective dynamic monitoring of both wheal and flare reactions and hence for quantification of the effect of anti-inflammatory drugs in humans. Topical application of SoS surprisingly increased PAF-acether-induced skin oedema (wheal), significantly whereas no effect was found on the flare reaction. No concentration-related effect of SoS could be shown. [ABSTRACT FROM AUTHOR]