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HIS has the potential to be an easy and fast aid in the preoperative delineation of ill-defined BCCs, but further adjustment and larger studies are warranted for an optimal outcome.

Pigmented basal cell carcinomas can be difficult to distinguish from melanocytic tumours. Hyperspectral imaging is a non-invasive imaging technique that measures the reflectance spectra of skin in vivo . The aim of this prospective pilot study was to use a convolutional neural network classifier in hyperspectral images for differential diagnosis between pigmented basal cell carcinomas and melanoma. A total of 26 pigmented lesions (10 pigmented basal cell carcinomas, 12 melanomas in situ , 4 invasive melanomas) were imaged with hyperspectral imaging and excised for histopathological diagnosis. For 2-class classifier (melanocytic tumours vs pigmented basal cell carcinomas) using the majority of the pixels to predict the class of the whole lesion, the results showed a sensitivity of 100% (95% confidence interval 81–100%), specificity of 90% (95% confidence interval 60–98%) and positive predictive value of 94% (95% confidence interval 73–99%). These results indicate that a convolutional neural network classifier can differentiate melanocytic tumours from pigmented basal cell carcinomas in hyperspectral images. Further studies are warranted in order to confirm these preliminary results, using larger samples and multiple tumour types, including all types of melanocytic lesions.

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Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. In this second part of a three-phase pilot study, we used a novel hand-held SICSURFIS Spectral Imager with an adaptable field of view and target-wise selectable wavelength channels to provide detailed spectral and spatial data for lesions on complex surfaces. The hyperspectral images (33 wavelengths, 477–891 nm) provided photometric data through individually controlled illumination modules, enabling convolutional networks to utilise spectral, spatial, and skin-surface models for the analyses. In total, 42 lesions were studied: 7 melanomas, 13 pigmented and 7 intradermal nevi, 10 basal cell carcinomas, and 5 squamous cell carcinomas. All lesions were excised for histological analyses. A pixel-wise analysis provided map-like images and classified pigmented lesions with a sensitivity of 87% and a specificity of 93%, and 79% and 91%, respectively, for non-pigmented lesions. A majority voting analysis, which provided the most probable lesion diagnosis, diagnosed 41 of 42 lesions correctly. This pilot study indicates that our non-invasive hyperspectral imaging system, which involves shape and depth data analysed by convolutional neural networks, is feasible for differentiating between malignant and benign pigmented and non-pigmented skin tumours, even on complex skin surfaces.

Background In the photodynamic therapy (PDT) of non-aggressive basal cell carcinomas (BCCs), 5-aminolevulinic acid nanoemulsion (BF-200ALA) has shown non-inferior efficacy when compared with methyl aminolevulinate (MAL), a widely used photosensitizer. Hexyl aminolevulinate (HAL) is an interesting alternative photosensitizer. To our knowledge, this is the first study using HAL-PDT in the treatment of BCCs. Objectives To compare the histological clearance, tolerability (pain and post-treatment reaction) and cosmetic outcome of MAL, BF-200 ALA and low-concentration HAL in the PDT of non-aggressive BCCs. Methods Ninety-eight histologically verified non-aggressive BCCs met the inclusion criteria, and 54 patients with 95 lesions completed the study. The lesions were randomized to receive LED-PDT in two repeated treatments with MAL, BF-200 ALA or HAL. Efficacy was assessed both clinically and confirmed histologically at three months by blinded observers. Furthermore, cosmetic outcome, pain, post-treatment reactions fluorescence and photobleaching were evaluated. Results According to intention-to-treat analyses, the histologically confirmed lesion clearance was 93.8% (95% confidence interval [CI] = 79.9-98.3) for MAL, 90.9% (95% CI = 76.4-96.9) for BF-200 ALA and 87.9% (95% CI = 72.7-95.2) for HAL, with no differences between the arms (P = 0.84). There were no differences between the arms as regards pain, post-treatment reactions or cosmetic outcome. Conclusions Photodynamic therapy with low-concentration HAL and BF-200 ALA has a similar efficacy, tolerability and cosmetic outcome compared to MAL. HAL is an interesting new option in dermatological PDT, since good efficacy is achieved with a low concentration.

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