Clinical Research Directory

Using an Artificial Intelligence (AI) Tool for Melanoma Diagnosis

The purpose of this study is to learn whether a computer-based support tool called DEXI (Dermoscopy EXplainable Intelligence) can help dermatologists decide whether a lesion may be melanoma, a serious type of skin cancer. DEXI uses artificial intelligence, or AI, which means computer technology that looks for patterns in images and information. DEXI works within a software program called the DermaGraphix Visualizer, which displays and organizes skin and lesion images. The goal of this study is to see whether DEXI can help doctors find melanoma and reduce biopsies that may not be needed.

Genetic Basis of Melanocytic Nevi

The objective of this protocol is to further elucidate the genetic mutations that drive melanocytic nevi (benign melanocytic neoplasms, moles). This will be performed by whole genome, whole exome, or targeted sequencing of de-identified specimens. Herein, the investigators plan to isolate DNA from de-identified skin biopsy specimens and blood samples: 1. From melanocytic nevi collected by skin biopsy (a shave or punch biopsy). A part of the tissue will be submitted for routine diagnostic dermatopathology and investigational histomorphologic and immunohistochemical analysis. 2. From corresponding normal tissue (blood). DNA isolated from blood will be used as a normal control when analyzing sequencing data to identify somatic mutations in lesional tissue.

Reflectance Confocal Microscopy and Molecular Correlation in Atypical Melanocytic Lesions

This observational, prospective cohort study aims to evaluate the diagnostic relevance of Reflectance Confocal Microscopy (RCM) features in atypical melanocytic lesions scheduled for surgical excision, and to correlate these imaging features with molecular profiles obtained through Next-Generation Sequencing (NGS). Approximately 200 consecutive lesions, including atypical nevi and early-stage melanomas, will be analyzed from patients attending the Videomicroscopy and Confocal Clinic at the Dermatology Department of the University Hospital of Modena. The primary objective is to assess the diagnostic significance of RCM features-specifically atypical cells and disarrangement of the dermoepidermal junction (DEJ)-for early detection of melanoma. Secondary objectives include correlating RCM morphological patterns with NGS-derived genetic alterations and identifying molecular signatures that differentiate early-stage melanomas from benign nevi. All procedures are performed as part of routine clinical care, including dermoscopic and confocal evaluation, surgical excision, histopathology, and molecular analysis on formalin-fixed, paraffin-embedded blocks. Data will be anonymized, securely stored, and analyzed to determine associations between imaging and genetic variables. This study integrates morphological and molecular data to refine diagnostic workflows and improve early melanoma detection.