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 the power to identify single tumor cells. 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.

Contact:
Professor Dr. Joachim Klode
University Hospital Essen Department of Dermatology
Hufelandstraße 55, 45147 Essen, Germany
Phone.: +49 201 723-1812 Fax: +49 201 723-5424
E-Mail: joachim.klode@uk-essen.de

Professor Dr. Matthias Gunzer
University Hospital Essen Institute for Experimental Immunology and Imaging
Hufelandstraße 55, 45147 Essen, Germany
Phone: +49 201 183 6640 Fax: +49 201 183 6642
E-Mail: matthias.gunzer@uni-due.de