IMPORTANCE A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and pathology services. OBJECTIVE To determine the accuracy of an artificial intelligence algorithm in identifying melanoma in dermoscopic images of lesions taken with smartphone and digital single-lens reflex (DSLR) cameras. DESIGN, SETTING, AND PARTICIPANTS This prospective, multicenter, single-arm, masked diagnostic trial took place in dermatology and plastic surgery clinics in 7 UK hospitals. Dermoscopic images of suspicious and control skin lesions from 514 patients with at least 1 suspicious pigmented skin lesion scheduled for biopsy were captured on 3 different cameras. Data were collected from January 2017 to July 2018. Clinicians and the Deep Ensemble for Recognition of Malignancy, a deterministic artificial intelligence algorithm trained to identify melanoma in dermoscopic images of pigmented skin lesions using deep learning techniques, assessed the likelihood of melanoma. Initial data analysis was conducted in September 2018; further analysis was conducted from February 2019 to August 2019. INTERVENTIONS Clinician and algorithmic assessment of melanoma.MAIN OUTCOMES AND MEASURES Area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity of the algorithmic and specialist assessment, determined using histopathology diagnosis as the criterion standard. RESULTSThe study population of 514 patients included 279 women (55.7%) and 484 white patients (96.8%), with a mean (SD) age of 52.1 (18.6) years. A total of 1550 images of skin lesions were included in the analysis (551 [35.6%] biopsied lesions; 999 [64.4%] control lesions); 286 images (18.6%) were used to train the algorithm, and a further 849 (54.8%) images were missing or unsuitable for analysis. Of the biopsied lesions that were assessed by the algorithm and specialists, 125 (22.7%) were diagnosed as melanoma. Of these, 77 (16.7%) were used for the primary analysis.The algorithm achieved an AUROC of 90.1% (95% CI, 86.3%-94.0%) for biopsied lesions and 95.8% (95% CI, 94.1%-97.6%) for all lesions using iPhone 6s images; an AUROC of 85.8% (95% CI, 81.0%-90.7%) for biopsied lesions and 93.8% (95% CI, 91.4%-96.2%) for all lesions using Galaxy S6 images; and an AUROC of 86.9% (95% CI, 80.8%-93.0%) for biopsied lesions and 91.8% (95% CI, 87.5%-96.1%) for all lesions using DSLR camera images. At 100% sensitivity, the algorithm achieved (continued) Key Points Question How accurate is an artificial intelligence-based melanoma detection algorithm, which analyzes dermoscopic images taken by smartphone and digital single-lens reflex cameras, compared with clinical assessment and histopathological diagnosis? Findings In this diagnostic study, 1550 images of suspicious and benign skin lesions were analyzed by an artificial intelligence algorithm. When compared with histopathological diagnosis, ...

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Background Palmoplantar pustulosis (PPP) is a rare, debilitating, chronic inflammatory skin disease that affects the hands and feet. Clinical, immunological and genetic findings suggest a pathogenic role for interleukin (IL)-1. Objectives To determine whether anakinra (an IL-1 receptor antagonist) delivers therapeutic benefit in PPP.

Neurocutaneous melanosis (NCM) is a rare congenital noninheritable phacomatosis characterized by large and/or numerous cutaneous congenital melanocytic naevi (CMN) in combination with melanocytic leptomeningeal tumours. Dandy-Walker malformation (DWM) consists of a cystic dilatation of the fourth ventricle communicating with the posterior fossa, and a high insertion of the tentorium and hypoplasia/aplasia of the cerebellar vermis (partially caused by Zic1(+/-)Zic 4(+/-) on 3q2). An association of NCM and DWM is very rare, with only 15 previously reported cases to our knowledge. We present an 8-year-old girl with multiple CMN and DWM. A ventriculoperitoneal shunt operation was performed when she was 1 day old. Her neurological symptoms to date comprise headaches, nausea and vomiting as a result of ventriculoperitoneal shunt dislocation at the age of 4 years. The diagnosis is provisional asymptomatic multiple CMN-type NCM in association with DWM.

Wells' syndrome (WS) is a very rare condition occurring in adults of any race and gender. The underlying aetiopathogenesis is thought to be a hypersensitivity response to different endogenous and exogenous stimuli. Reported trigger factors include arthropod bites, cutaneous viral, fungal and parasitic infections, medications, vaccinations, eczema, autoimmune disease, carcinoma, leukaemia and myeloproliferative disorders. We report a patient with this rare condition, who improved rapidly with combination treatment of prednisolone and ciclosporin. In our patient, several factors might have played a role in the development of WS.

Subcutaneous fat necrosis in a newborn is a rare, benign and self-limiting panniculitis. Hypercalcemia may develop and has been implicated as the cause of serious complications including seizures, nephrocalcinosis, and death. We report a case of subcutaneous fat necrosis in a newborn associated with asymptomatic and uncomplicated hypercalcemia, which resolved spontaneously.

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