Malignancies are still responsible for a large share of lethalities. Macroscopical
evaluation of the surgical resection margins is uncertain. Big data based imaging
approaches have emerged in the recent decade (mass spectrometry, two-photon microscopy,
infrared and Raman spectroscopy). Indocianine green labelled MS is the most common
approach, however, label free mid-infrared imaging is more promising for future practical
application. We aimed to identify and separate different transformed (A-375, HT-29)
and non-transformed (CCD986SK) cell lines by a label-free infrared spectroscopy method.
Our approach applied a novel set-up for label-free mid-infrared range classification
method. Transflection spectroscopy was used on aluminium coated glass slides. Both
whole range spectra (4000-648 cm(-1)) and hypersensitive fingerprint regions (1800-648
cm(-1)) were tested on the imaged areas of cell lines fixed in ethanol. Non-cell spectra
were possible to be excluded based on mean transmission values being above 90%. Feasibility
of a mean transmission based spectra filtering method with principal component analysis
and linear discriminant analysis was shown to separate cell lines representing different
tissue types. Fingerprint region resulted the best separation of cell lines spectra
with accuracy of 99.84% at 70-75 mean transmittance range. Our approach in vitro was
able to separate unique cell lines representing different tissues of origin. Proper
data handling and spectra processing are key steps to achieve the adaptation of this
dye-free technique for intraoperative surgery. Further studies are urgently needed
to test this novel, marker-free approach.
