3D data related to: Identification and quantification of hidden melanoma metastases in human sentinel lymph nodes using light sheet fluorescence microscopy

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Authors: Simon F. Merz, Philipp Jansen, Ricarda Ulankiewicz, Lea Bornemann, Tobias T. Schimming, Klaus Griewank, Zülal Cibir, Andreas Kraus, Ingo Stoffels, Timo Aspelmeier, Timo Aspelmeier, Sven Brandau
+5 more Dirk Schadendorf, Eva N. Hadaschik, G. Ebel, Matthias Gunzer, Joachim Klode
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Abstract

High resolution imaging of sentinel lymph nodes (SLN) from melanoma patients is a crucial approach to specify staging and determine individuals requiring adjuvant treatment. Current histologic SLN analysis has the substantial drawback that only a small portion of the node is sampled while most of the tissue is discarded which might explain the high false-negative rate of SLN diagnosis. Therefore, we developed an algorithm-enhanced light sheet fluorescence microscopy (LSFM) approach to three-dimensionally reconstruct the entire SLN with single-cell resolution. We comprehensively quantified total tumor volume while simultaneously visualizing cellular and anatomical hallmarks of the associated SLN architecture. In a first-in-human prospective study (21 SLN from 11 melanoma patients), LSFM not only identified all metastases seen histologically, but additionally detected metastases not recognized by routine histology. Thus, our 3-D digital pathology approach can increase sensitivity and accuracy of SLN-metastasis detection and potentially alleviate the need for conventional histopathological assessment in the future.

Fields of Study & Subjects

Cutaneous Melanoma Detection and Management AI in cancer detection Cell Image Analysis Techniques

Publication details

Journal / source
DuEData
Publication date
6 February 2026
Language
EN
Document type
Dataset