An exploratory randomized clinical trial on negative pressure wound therapy for lower limb full-thickness skin grafts of dermatosurgical patients.

Full-thickness skin graft (FTSG) reconstructions of lower limbs are especially prone to wound complications. Negative pressure wound therapy (NPWT) enhances wound healing, but no broad evidence exists if it promotes graft take of lower leg FTSGs. In this investigator-initiated, prospective, randomised and controlled trial, 20 patients with ambulatory FTSG reconstruction for lower limb skin cancers were randomised for postoperative treatment with either NPWT, or conventional dressings. As outcomes, adherence of the skin graft 1 week postoperatively, any wound complications within 3 months, including ≥3 weeks delayed wound healing, and the number of additional postoperative visits were compared. In both groups, grafts adhered equally well (p = 0.47); 80% of NPWT-treated and 100% of control group grafts adhered >90%. There was no significant difference in the number of postoperative complications/delayed wound healing (p = 0.65); 70% of patients in the NPWT and 50% in the control group developed a wound complication. Both groups had an equal number of patients with at least three additional control visits (p = 1.0). The study was discontinued after 20 patients were recruited, as no benefit from NPWT was seen. To conclude, the study showed no benefit from NPWT for lower limb FTSGs.

Ablative Fractional Laser Enhances Artificial or Natural Daylight Photodynamic Therapy of Actinic Field Cancerization: A Randomized and Investigator-initiated Half-side Comparative Study.

Artificial daylight photodynamic therapy is a near-painless treatment for actinic keratoses, which can be performed indoors using a controlled light dose. Daylight photodynamic therapy is approved only for treatment of grade I-II actinic keratoses. The aim of this study was to evaluate whether fractional laser pre-treatment improves the outcomes of daylight photodynamic therapy for actinic keratoses of all grades. In addition, the study compared the outcomes of artificial and natural daylight photodynamic therapy. This randomized single-blinded split-side comparative study included 60 patients with ≥ 2 actinic keratoses of the head. Fractional laser pre-treatment was assigned randomly for actinic keratoses on 1 side of the head and, subsequently, the entire treatment area was treated with artificial or natural daylight photodynamic therapy. Fractional laser-mediated daylight photodynamic therapy achieved significantly higher complete clearance (50.0% vs 30.3%, p = 0.04), partial clearance (78.6% vs 50.0%, p < 0.01) and lesion-specific clearance (86.2% vs 70.2%, p < 0.01) than daylight photodynamic therapy alone at the 6-month follow-up. No significant differences were found in the outcomes of artificial vs natural daylight photodynamic therapy or grade I lesions vs grade II-III lesions. Thus, fractional laser pre-treatment appears to significantly increase the efficacy of artificial and natural daylight photodynamic therapy, and to be suitable for treatment of actinic keratoses of all grades.

Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions.

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024-0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005-0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

Hyperspectral Imaging Reveals Spectral Differences and Can Distinguish Malignant Melanoma from Pigmented Basal Cell Carcinomas: A Pilot Study.

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 pigment-ed 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 histopatho-logical diagnosis. For 2-class classifier (melano-cytic 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.

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours-A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks.

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.