Raman spectroscopy is a non-destructive label-free technique providing biochemical tissue fingerprint. The objective of the present work was to test if Raman spectroscopy is a suitable tool to differentiate lymph nodes affected by different conditions, such as reactive follicular hyperplasia (benign), follicular lymphoma (low grade primary tumour), diffuse large B cell lymphoma (high grade primary tumour) and tumour metastasis (secondary tumours). Moreover, we tested its ability to discriminate follicular lymphomas by the tumour grade and the BCL2 protein expression. Lymph nodes collected from 20 patients, who underwent surgery for suspected malignancy, were investigated. Imaging of tissue areas from about 400 µm2 up to 2 mm2 was performed collecting Raman maps containing thousands of spectra. Partial least squares discriminant analysis (PLS-DA) - a bilinear classification method - was used to calculate lymph node classification models, in order to discriminate at first between benign and malignant tissues and successively among cancer types, grades and the BCL2 protein expression. This proof-of-concept study paves the way for the development of clinical optical biopsy tools for lymph node cancer diagnosis, complementary to histopathological assessment.
Keywords: Biochemical fingerprint; Chemometric models; Lymph node pathologies; Raman spectroscopy; Tissue imaging.
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