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DOI: 10.1055/s-0042-1746596
Establishment of a tissue processing workflow and analysis of the influence of formalin fixation and paraffin embedding on the spectral bioinformation of salivary gland tumors
Introduction The pre-, intra- and postoperative entity and dignity determination of salivary gland tumors (ST) solely based on histomorphological criteria is often associated with great uncertainties.
The spectra of Raman spectroscopy (RS) and infrared spectroscopy (IS) contain information about the molecular composition of the investigated tissue. The aim of this study was the establishment of a tissue processing workflow and the analysis of the influence of formalin and paraffin fixation on the spectral bioinformation compared to cryofixation. In addition, an overview of the use of RS and IS in head and neck oncology is given.
Material and methods 10 µm thick, consecutive sections from cryo-, formalin-, and paraffin-fixed cystadenolymphomas (n=5) and pleomorphic adenomas (n=4) were examined by the RS and IS and data were evaluated multivariately. The measurements were made in correlation to the histomorphology via a corresponding HE section both in the tumor tissue and in the healthy salivary gland tissue.
Results The mean value spectrum analysis showed a clear paraffin signature, formalin fixation had no significant influence. This could be confirmed by the principal component analysis (PCA). A discrimination of tumor and non-tumor tissue by the PCA and coupled discriminant analysis was also possible with both spectroscopic methods, RS and IS, with a high sensitivity.
Discussion For a translation of spectral processes, knowledge on factors influencing the spectral bioinformation of tissue preparation and fixation is essential. The additive integration of spectral methods into existing work processes is possible. The influence of formalin fixation on the spectral bioinformation is small. The bioinformatic analysis of the extensive data sets is challenging.
IZKF Würzburg
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Artikel online veröffentlicht:
24. Mai 2022
© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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