High-resolution three-dimensional imaging for precise staging in melanoma.

ABSTRACT

INTRODUCTION: Many cancer guidelines include sentinel lymph node (SLN) staging to identify microscopic metastatic disease. Current SLN analysis of melanoma patients is effective but has the substantial drawback that only a small representative portion of the node is sampled, whereas most of the tissue is discarded. This might explain the high clinical false-negative rate of current SLN diagnosis in melanoma. Furthermore, the quantitative assessment of metastatic load and microanatomical localisation might yield prognosis with higher precision. Thus, methods to analyse entire SLNs with cellular resolution apart from tedious sequential physical sectioning are required. PATIENTS AND METHODS: Eleven melanoma patients eligible to undergo SLN biopsy were included in this prospective study. SLNs were fixed, optically cleared, whole-mount stained and imaged using light sheet fluorescence microscopy (LSFM). Subsequently, compatible and unbiased gold standard histopathological assessment allowed regular patient staging. This enabled intrasample comparison of LSFM and histological findings. In addition, the development of an algorithm, RAYhance, enabled easy-to-handle display of LSFM data in a browsable histologic slide-like fashion. RESULTS: We comprehensively quantify total tumour volume while simultaneously visualising cellular and anatomical hallmarks of the associated SLN architecture. In a first-in-human study of 21 SLN of melanoma patients, LSFM not only confirmed all metastases identified by routine histopathological assessment but also additionally revealed metastases not detected by routine histology alone. This already led to additional therapeutic options for one patient. CONCLUSION: Our three-dimensional digital pathology approach can increase sensitivity and accuracy of SLN metastasis detection and potentially alleviate the need for conventional histopathological assessment in the future. GERMAN CLINICAL TRIALS REGISTER (DRKS00015737).