PROCEEDINGS ARTICLE | April 24, 2017
Proc. SPIE. 10068, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XV
KEYWORDS: Cancer, Tumors, Tissues, Diagnostics, Raman spectroscopy, Digital imaging, Spectral resolution, Chemometrics, Biological research, Library classification systems
It has been shown that Raman spectroscopy provides superb ability to differentiate individual cell types, and can also be used to detect circulating tumor cells (CTCs).1 CTCs have been recently identified as a main culprit for the development of cancer metastasis in cancer patients.2 It is also well known that the presence of CTCs is negatively associated with the development of metastasis and the progression of cancer. Hence, a reliable method for CTC identification will have a major impact on cancer diagnostic, monitoring of cancer progression, and cancer therapy.
There are, however, two general problems of using Raman spectroscopy for the identification of cells. On the one hand, it is not clear from which cellular location a Raman spectrum that reliably represents the given cell should be acquired. On the other hand, the Raman signal intensity is weak, so that acquisition times of several seconds are required, prohibiting a high-throughput cell sampling.
In this work we firstly show that by rapidly scanning a diffraction-limited spot over the cell and continuously acquiring a Raman spectrum it is possible to overcome the intracellular heterogeneity of a cell. And the resulting chemometric models provide a better and more robust cell classification. Secondly, we can show that the spectral resolution of a Raman spectrum is not as crucial to distinguish between different cell types. By reducing the spectral resolution 6-fold, we can achieve a signal gain 5-fold and still reliably identify single cells.
