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Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors
(2021)
Background
The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT.
Methods
Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software.
Results
The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly.
Conclusion
In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.
Salivary gland tumors are a rare tumor entity within malignant tumors of all tissues. The most common are malignant mucoepidermoid carcinoma, adenoid cystic carcinoma, and acinic cell carcinoma. Pleomorphic adenoma is the most recurrent form of benign salivary gland tumor. Due to their low incidence rates and complex histological patterns, they are difficult to diagnose accurately. Malignant tumors of the salivary glands are challenging in terms of differentiation because of their variability in histochemistry and translocations. Therefore, the primary goal of the study was to review the current literature to identify the recent developments in histochemical diagnostics and translocations for differentiating salivary gland tumors.