Original scientific paper
Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study
Aleksandra Pavićević
; University of Belgrade, Faculty Physical Chemistry, Belgrade, Serbia of
Sofija Glumac
; University of Belgrade, Faculty Medicine, Institute of Pathology, of Belgrade, Serbia
Jelena Sopta
; University of Belgrade, Faculty Medicine, Institute of Pathology, of Belgrade, Serbia
Ana Popović-Bijelić
; University of Belgrade, Faculty Physical Chemistry, Belgrade, Serbia
Miloš Mojović
; University of Belgrade, Faculty Physical Chemistry, Belgrade, Serbia
Goran Bačić
; University of Belgrade, Faculty Physical Chemistry, Belgrade, Serbia
Abstract
Aim To elucidate whether Raman spectroscopy aided by
extensive spectral database and neural network analysis
can be a fast and confident biomarking tool for the diagnosis
of various types of cancer.
Methods Study included 27 patients with 11 different malignant
tumors. Using Raman microscopy (RM) a total of
540 Raman spectra were recorded from histology specimens
of both tumors and surrounding healthy tissues.
Spectra were analyzed using the principal component
analysis (PCA) and results, along with histopathology data,
were used to train the neural network (NN) learning algorithm.
Independent sets of spectra were used to test the
accuracy of PCA/NN tissue classification.
Results The confident tumor identification for the purpose
of medical diagnosis has to be performed by taking into
account the whole spectral shape, and not only particular
spectral bands. The use of PCA/NN analysis showed overall
sensitivity of 96% with 4% false negative tumor classification.
The specificity of distinguishing tumor types was 80%.
These results are comparable to previously published data
where tumors of only one tissue type were examined and
can be regarded satisfactorily for a relatively small database
of Raman spectra used here.
Conclusion In vitro RM combined with PCA/NN is an almost
fully automated method for histopathology at the
level of macromolecules. Supported by an extensive tumor
spectra database, it could become a customary histological
analysis tool for fast and reliable diagnosis of different
types of cancer in clinical settings
Keywords
Hrčak ID:
94958
URI
Publication date:
15.12.2012.
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