Optimisation of skin phototype classification

Normal and melanoma skin visualized, quantified and compared by in vivo photoacoustic imaging

Photoacoustic imaging (PAI) shows promise for skin cancer diagnosis by detecting chromophores like melanin, hemoglobin, lipids, and collagen. While most studies focus on malignant lesions, understanding normal skin variability across anatomical regions is crucial for validating PAI's clinical application and its use in melanoma diagnosis. We assessed normal skin in 20 healthy volunteers from three different body locations using a clinical PAI system and compared suspicious looking pigmented skin lesions, including melanomas, to adjacent normal skin (n = 74). Higher deoxyhemoglobin levels were observed in the ankle compared to the cheek and volar forearm, while melanin, lipids, and collagen showed minimal variation. Patients with malignant lesions had significantly higher deoxyhemoglobin levels (p = 0.001) than adjacent normal skin, a difference not seen in benign lesions. These findings suggest that PAI may help diagnose malignancies by identifying increased vascularity in skin cancers, while anatomical differences should be considered during diagnostic work-up.

Emerging therapies and innovations in vitiligo management: a comprehensive review

Vitiligo is a common skin disorder where melanocytes, the cells that produce skin pigment, are destroyed by the immune system, leading to white patches on the skin and mucous membranes. This condition affects 0.4% to 2.0% of the global population, with a higher prevalence in females and often beginning in childhood. In India, about 1% of the population is affected, particularly in northern regions, with a higher incidence in females and links to other autoimmune diseases. This review examines recent progress in understanding vitiligo and its treatment. It focuses on the genetic, autoimmune, and environmental factors involved in the disease and highlights new therapies, such as targeted molecular treatments and advanced repigmentation methods. Current research shows that oxidative stress and genetic predispositions contribute to the autoimmune destruction of melanocytes. Novel drug delivery systems, including liposomes, nanoemulsions, and nanostructured lipid carriers, have improved treatment effectiveness. Clinical trials are exploring new treatments like Ruxolitinib cream and melanocyte transplantation, while teledermatology is becoming useful for managing patients. Vitiligo also poses a significant economic burden due to its impact on patients' quality of life. Continued research is essential to develop better, more accessible treatments and reduce the economic impact of vitiligo.

Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements

The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may contribute to dermatological care disparities in patients with darker skin phototypes, including the misdiagnosis of wound healing progression and escalated dermatological disease severity. This study introduces (1) an optical sensor measuring reflected light across 410-940 nm, (2) an unsupervised K-means algorithm for skin phototype classification using broadband optical data, and (3) methods to optimize classification across the Near-ultraviolet-A, Visible, and Near-infrared spectra. The differentiation capability of the algorithm was compared to human assessment based on FSPC in a diverse participant population (n = 30) spanning an even distribution of the full FSPC scale. The FSPC assessment distinguished between light and dark skin phototypes (e.g., FSPC I vs. VI) at 560, 585, and 645 nm but struggled with more similar phototypes (e.g., I vs. II). The K-means algorithm demonstrated stronger differentiation across a broader range of wavelengths, resulting in better classification resolution and supporting its use as a quantifiable and reproducible method for skin type classification. We also demonstrate the optimization of this method for specific bandwidths of interest and their associated clinical implications.

Skin Protection by Carotenoid Pigments

Sunlight, despite its benefits, can pose a threat to the skin, which is a natural protective barrier. Phototoxicity caused by overexposure, especially to ultraviolet radiation (UVR), results in burns, accelerates photoaging, and causes skin cancer formation. Natural substances of plant origin, i.e., polyphenols, flavonoids, and photosynthetic pigments, can protect the skin against the effects of radiation, acting not only as photoprotectors like natural filters but as antioxidant and anti-inflammatory remedies, alleviating the effects of photodamage to the skin. Plant-based formulations are gaining popularity as an attractive alternative to synthetic filters. Over the past 20 years, a large number of studies have been published to assess the photoprotective effects of natural plant products, primarily through their antioxidant, antimutagenic, and anti-immunosuppressive activities. This review selects the most important data on skin photodamage and photoprotective efficacy of selected plant carotenoid representatives from in vivo studies on animal models and humans, as well as in vitro experiments performed on fibroblast and keratinocyte cell lines. Recent research on carotenoids associated with lipid nanoparticles, nanoemulsions, liposomes, and micelles is reviewed. The focus was on collecting those nanomaterials that serve to improve the bioavailability and stability of carotenoids as natural antioxidants with photoprotective activity.