Article (Scientific journals)
Application of Raman Spectroscopy for Detection of Histologically Distinct Areas in Formalin-fixed Paraffin-embedded (FFPE) Glioblastoma
Klamminger, Gilbert Georg; Gerardy, Jean-Jacques; Jelke, Finn et al.
2021In Neuro-Oncology Advances
Peer Reviewed verified by ORBi


Full Text
Author preprint (894.68 kB)

All documents in ORBilu are protected by a user license.

Send to


Keywords :
Raman spectroscopy; Glioma; Machine Learning
Abstract :
[en] Background Although microscopic assessment is still the diagnostic gold standard in pathology, non-light microscopic methods such as new imaging methods and molecular pathology have considerably contributed to more precise diagnostics. As an upcoming method, Raman spectroscopy (RS) offers a "molecular fingerprint" which could be used to differentiate tissue heterogeneity or diagnostic entities. RS has been successfully applied on fresh and frozen tissue, however more aggressively, chemically treated tissue such as formalin-fixed, paraffin-embedded (FFPE) samples are challenging for RS. Methods To address this issue, we examined FFPE samples of morphologically highly heterogeneous glioblastoma (GBM) using RS in order to classify histologically defined GBM areas according to RS spectral properties. We have set up a SVM (support vector machine)-based classifier in a training cohort and corroborated our findings in a validation cohort. Results Our trained classifier identified distinct histological areas such as tumor core and necroses in GBM with an overall accuracy of 70.5% based on spectral properties of RS. With an absolute misclassification of 21 out of 471 Raman measurements, our classifier has the property of precisely distinguishing between normal appearing brain tissue and necrosis. When verifying the suitability of our classifier system in a second independent dataset, very little overlap between necrosis and normal appearing brain tissue can be detected. Conclusion These findings show that histologically highly variable samples such as GBM can be reliably recognized by their spectral properties using RS. As a conclusion, we propose that RS may serve useful as a future method in the pathological toolbox.
Disciplines :
Human health sciences: Multidisciplinary, general & others
Author, co-author :
Klamminger, Gilbert Georg
Gerardy, Jean-Jacques ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Jelke, Finn
Mirizzi, Giulia
Slimani, Rédouane
Klein, Karoline
Husch, Andreas  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience
Hertel, Frank ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC)
Mittelbronn, Michel ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Kleine-Borgmann, Felix B.
External co-authors :
Language :
Title :
Application of Raman Spectroscopy for Detection of Histologically Distinct Areas in Formalin-fixed Paraffin-embedded (FFPE) Glioblastoma
Publication date :
Journal title :
Neuro-Oncology Advances
Publisher :
Oxford University Press, United Kingdom
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
Funders :
Fondation Cancer
Available on ORBilu :
since 02 July 2021


Number of views
107 (3 by Unilu)
Number of downloads
44 (0 by Unilu)

Scopus citations®
Scopus citations®
without self-citations
WoS citations


Similar publications

Contact ORBilu