RESUMO
INTRODUCTION: Rosettes are a cluster of shiny white dots in the shape of a four-leaf clover seen under polarized dermoscopic light. Historically, rosettes were primarily reported in actinic keratoses and squamous cell carcinoma. However, rosettes have also been reported in other conditions. OBJECTIVES: The objective of this systematic review to elucidate the breadth of diagnoses exhibiting this unique dermoscopic phenomenon. METHODS: A review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Literature searches were performed in MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Web of Science, as well as a manual search of the reference lists of screened articles. RESULTS: A total of 73 articles met the inclusion criteria. Out of these, 47 distinct diagnoses with rosette were identified. Among neoplastic conditions, keratinizing neoplasms had the highest number of articles reported (N = 19). Discoid lupus was the most commonly reported diagnosis within the inflammatory category (N = 6). Molluscum contagiosum was the predominant diagnosis among infectious entities (N = 3), while acroangiodermatitis was the sole diagnosis reported in the vascular category (N = 1). CONCLUSIONS: These findings confirm rosettes are not specific to keratinocytic growths and are observed in a wide range of conditions. Knowledge of the breadth of conditions with rosettes may aid clinicians when developing a differential diagnosis of a growth or an eruption with rosettes under dermoscopy.
RESUMO
Background: Skin cancer is the most common form of cancer worldwide. As artificial intelligence (AI) expands its scope within dermatology, leveraging technology may aid skin cancer detection. Objective: To assess the safety and effectiveness of an elastic-scattering spectroscopy (ESS) device in evaluating lesions suggestive of skin cancer. Methods: This prospective, multicenter clinical validation study was conducted at 4 US investigational sites. Patients with skin lesions suggestive of melanoma and nonmelanoma skin cancers were clinically assessed by expert dermatologists and evaluated by a device using AI algorithms comparing current ESS lesion readings with training data sets. Statistical analyses included sensitivity, specificity, AUROC, negative predictive value (NPV), and positive predictive value (PPV). Results: Overall device sensitivity was 97.04%, with subgroup sensitivity of 96.67% for melanoma, 97.22% for basal cell carcinoma, and 97.01% for squamous cell carcinoma. No statistically significant difference was found between the device and dermatologist performance (P = .8203). Overall specificity of the device was 26.22%. Overall NPV of the device was 89.58% and PPV was 57.54%. Conclusion: The ESS device demonstrated high sensitivity in detecting skin cancer. Use of this device may assist primary care clinicians in assessing suspicious lesions, potentially reducing skin cancer morbidity and mortality through expedited and enhanced detection and intervention.
