Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA.
Department of Dermatology, School of Medicine, Wayne State University School of Medicine, Detroit, MI 48201, USA.
Int J Mol Sci. 2020 Dec 16;21(24):9583. doi: 10.3390/ijms21249583.
Melanoma is the deadliest form of skin cancer and remains a diagnostic challenge in the dermatology clinic. Several non-invasive imaging techniques have been developed to identify melanoma. The signal source in each of these modalities is based on the alteration of physical characteristics of the tissue from healthy/benign to melanoma. However, as these characteristics are not always sufficiently specific, the current imaging techniques are not adequate for use in the clinical setting. A more robust way of melanoma diagnosis is to "stain" or selectively target the suspect tissue with a melanoma biomarker attached to a contrast enhancer of one imaging modality. Here, we categorize and review known melanoma diagnostic biomarkers with the goal of guiding skin imaging experts to design an appropriate diagnostic tool for differentiating between melanoma and benign lesions with a high specificity and sensitivity.
黑色素瘤是最致命的皮肤癌形式,在皮肤科诊所仍然是一个诊断挑战。已经开发出几种非侵入性成像技术来识别黑色素瘤。这些模式中的每一种的信号源都基于组织的物理特性从健康/良性到黑色素瘤的改变。然而,由于这些特征并不总是足够特异,目前的成像技术在临床环境中并不适用。更可靠的黑色素瘤诊断方法是用附着在一种成像模式的对比增强剂上的黑色素瘤生物标志物“染色”或有选择地靶向可疑组织。在这里,我们对已知的黑色素瘤诊断生物标志物进行分类和综述,旨在为皮肤成像专家设计一种合适的诊断工具,以区分黑色素瘤和良性病变,具有高特异性和敏感性。