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<p>Reflectance confocal microscopy (RCM) is a&#xa0;noninvasive imaging technique offering high lateral resolution and is increasingly used in dermatology for differentiating benign from malignant melanocytic skin lesions such as nevi, melanoma, and lentigo maligna. By directing focused laser light into the skin and capturing reflected signals through a&#xa0;confocal aperture, horizontal optical sections of the epidermis and upper dermis can be generated with a&#xa0;resolution of 1–3 µm. Hallmarks of malignancy—such as pagetoid cells, nonedged papillae, and irregular nests—can be detected in vivo. The penetration depth of the technique is limited to approximately 250–300 µm. One of the key strengths of RCM lies in its ability to delineate tumor margins in lentigo maligna prior to surgical or laser-based therapy. In addition to reflectance imaging, fluorescence-based visualization is possible following topical or intradermal administration of contrast agents. Recent advances integrate artificial intelligence (AI) to assist in the automated analysis of RCM images. Early AI-based systems, such as MED-Net, have demonstrated promising sensitivity and specificity for identifying melanocytic structures. Overall, RCM—especially when combined with validated AI algorithms—represents a&#xa0;valuable extension of diagnostic capabilities in modern dermatologic oncology.</p>

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In vivo konfokale Lasermikroskopie und melanozytäre Tumoren

  • 期刊论文

  • 发表日期：

    2025年9月29日

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  • Charlotte Gust,
  • Elke Sattler

摘要

Reflectance confocal microscopy (RCM) is a noninvasive imaging technique offering high lateral resolution and is increasingly used in dermatology for differentiating benign from malignant melanocytic skin lesions such as nevi, melanoma, and lentigo maligna. By directing focused laser light into the skin and capturing reflected signals through a confocal aperture, horizontal optical sections of the epidermis and upper dermis can be generated with a resolution of 1–3 µm. Hallmarks of malignancy—such as pagetoid cells, nonedged papillae, and irregular nests—can be detected in vivo. The penetration depth of the technique is limited to approximately 250–300 µm. One of the key strengths of RCM lies in its ability to delineate tumor margins in lentigo maligna prior to surgical or laser-based therapy. In addition to reflectance imaging, fluorescence-based visualization is possible following topical or intradermal administration of contrast agents. Recent advances integrate artificial intelligence (AI) to assist in the automated analysis of RCM images. Early AI-based systems, such as MED-Net, have demonstrated promising sensitivity and specificity for identifying melanocytic structures. Overall, RCM—especially when combined with validated AI algorithms—represents a valuable extension of diagnostic capabilities in modern dermatologic oncology.