Analytical and Bioanalytical Chemistry

, Volume 403, Issue 3, pp 719–725 | Cite as

Unsupervised unmixing of Raman microspectroscopic images for morphochemical analysis of non-dried brain tumor specimens

  • Norbert Bergner
  • Christoph Krafft
  • Kathrin D. Geiger
  • Matthias Kirsch
  • Gabriele Schackert
  • Jürgen Popp
Original Paper


Raman microspectroscopic imaging provides molecular contrast in a label-free manner with subcellular spatial resolution. These properties might complement clinical tools for diagnosis of tissue and cells in the future. Eight Raman spectroscopic images were collected with 785 nm excitation from five non-dried brain specimens immersed in aqueous buffer. The specimens were assigned to molecular and granular layers of cerebellum, cerebrum with and without scattered tumor cells of astrocytoma WHO grade III, ependymoma WHO grade II, astrocytoma WHO grade III, and glioblastoma multiforme WHO grade IV with subnecrotic and necrotic regions. In contrast with dried tissue section, these samples were not affected by drying effects such as crystallization of lipids or denaturation of proteins and nucleic acids. The combined data sets were processed by use of the hyperspectral unmixing algorithms N-FINDR and VCA. Both unsupervised approaches calculated seven endmembers that reveal the abundance plots and spectral signatures of cholesterol, cholesterol ester, nucleic acids, carotene, proteins, lipids, and buffer. The endmembers were correlated with Raman spectra of reference materials. The focus of the single mode laser near 1 μm and the step size of 2 μm were sufficiently small to resolve morphological details, for example cholesterol ester islets and cell nuclei. The results are compared for both unmixing algorithms and with previously reported supervised spectral decomposition techniques.


Morphological details in tissue sections are resolved by Raman imaging and might contribute together with chemical information to improved diagnosis.


Raman imaging Brain tumors Non-dried specimens Hyperspectral unmixing 



This work was funded by the European Union via the “Europäischer Fonds für Regionale Entwicklung” (EFRE), the “Thüringer Ministerium für Bildung, Wissenschaft und Kultur” (project B714-07037), and the “Bundesministerium für Bildung und Forschung” (BMBF) within the MediCARS project (FKZ: 13N10774).


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Norbert Bergner
    • 1
  • Christoph Krafft
    • 1
  • Kathrin D. Geiger
    • 2
  • Matthias Kirsch
    • 3
  • Gabriele Schackert
    • 3
  • Jürgen Popp
    • 1
    • 4
  1. 1.Institute of Photonic TechnologyJenaGermany
  2. 2.Institute of Pathology, Department of NeuropathologyUniversity Hospital Carl Gustav Carus DresdenDresdenGermany
  3. 3.Clinic of NeurosurgeryUniversity Hospital Carl Gustav Carus DresdenDresdenGermany
  4. 4.Institute of Physical Chemistry and Abbe Center of PhotonicsFriedrich Schiller University JenaJenaGermany

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