Toward improving fine needle aspiration cytology by applying Raman microspectroscopy

Melanie Becker-Putsche; Thomas Bocklitz; Joachim H. Clement; Petra Rösch; Jürgen Popp

doi:10.1117/1.JBO.18.4.047001

1 April 2013 Toward improving fine needle aspiration cytology by applying Raman microspectroscopy

Melanie Becker-Putsche, Thomas Bocklitz, Joachim H. Clement, Petra Rösch, Jürgen Popp

Author Affiliations +

Journal of Biomedical Optics, Vol. 18, Issue 4, 047001 (April 2013). https://doi.org/10.1117/1.JBO.18.4.047001

Abstract

Medical diagnosis of biopsies performed by fine needle aspiration has to be very reliable. Therefore, pathologists/cytologists need additional biochemical information on single cancer cells for an accurate diagnosis. Accordingly, we applied three different classification models for discriminating various features of six breast cancer cell lines by analyzing Raman microspectroscopic data. The statistical evaluations are implemented by linear discriminant analysis (LDA) and support vector machines (SVM). For the first model, a total of 61,580 Raman spectra from 110 single cells are discriminated at the cell-line level with an accuracy of 99.52% using an SVM. The LDA classification based on Raman data achieved an accuracy of 94.04% by discriminating cell lines by their origin (solid tumor versus pleural effusion). In the third model, Raman cell spectra are classified by their cancer subtypes. LDA results show an accuracy of 97.45% and specificities of 97.78%, 99.11%, and 98.97% for the subtypes basal-like, HER2+/ER− , and luminal, respectively. These subtypes are confirmed by gene expression patterns, which are important prognostic features in diagnosis. This work shows the applicability of Raman spectroscopy and statistical data handling in analyzing cancer-relevant biochemical information for advanced medical diagnosis on the single-cell level.

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Melanie Becker-Putsche, Thomas Bocklitz, Joachim H. Clement, Petra Rösch, and Jürgen Popp "Toward improving fine needle aspiration cytology by applying Raman microspectroscopy," Journal of Biomedical Optics 18(4), 047001 (1 April 2013). https://doi.org/10.1117/1.JBO.18.4.047001

Published: 1 April 2013

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KEYWORDS

Raman spectroscopy

Breast cancer

Fine needle aspiration

Tumors

Cancer

Imaging spectroscopy

Breast

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