An Algorithmic Dermatoscopic Approach to Non‑Pigmented Skin Tumors

Introduction: Non-pigmented skin tumors represent a major diagnostic challenge in dermoscopy. In the absence of pigment, traditional pattern recognition is often unreliable, increasing the risk of misdiagnosis, particularly for melanoma and other aggressive malignancies. Objectives: To summarize key dermoscopic features of non-pigmented skin tumors and propose structured algorithms for the management of non-pigmented nodular and flat lesions. Methods: A narrative review of the literature was conducted, focusing on dermoscopic criteria relevant to non-pigmented lesions, including vascular morphology, white-colored structures, and ulceration. Based on these features, pragmatic algorithms were developed to guide clinical decision-making. Results: Vascular structures represent the most informative dermoscopic features in non-pigmented tumors, although their specificity is limited. White-colored structures and ulceration provide additional, non-specific clues. For nodular lesions, an exclusion-based algorithm centered on common benign entities supports conservative management only when diagnostic confidence is high; otherwise, excision is recommended. For flat lesions, a stepwise assessment of ulceration, vascular morphology, and surface keratin allows differentiation among superficial basal cell carcinoma, Bowen’s disease, and lesions requiring biopsy. Conclusions: Simple, conservative dermoscopic algorithms may improve the safety and consistency of clinical decision-making in non-pigmented skin tumors, supporting early detection of malignancies while accepting a degree of benign excisions.