Mid infrared spectroscopy samples were developed for the analysis of skin tumor cell types and three dimensional tissue phantoms towards the application of midIR spectroscopy for fast and reliable skin cancer diagnostics.
Marker free optical spectroscopy is a powerful tool for the rapid inspection of pathologically suspicious skin lesions and the non-invasive detection of early skin tumors. This goal can be reached by the combination of signal localization and the spectroscopical detection of chemical cell signatures. We here present the development and application of mid infrared spectroscopy (midIR) for the analysis of skin tumor cell types and three dimensional tissue phantoms towards the application of midIR spectroscopy for fast and reliable skin diagnostics. We developed standardized in vitro skin systems with increasing complexity, from single skin cell types as fibroblasts, keratinocytes and melanoma cells, to mixtures of these and finally three dimensional skin cancer phantoms. The cell systems were characterized with different systems in the midIR range up to 12 μm. The analysis of the spectra by novel data processing algorithms demonstrated the clear separation of all cell types, especially melanoma cells. Special attention and algorithm training was required for closely related mesenchymal cell types as dedifferentiated melanoma cells and fibroblasts. Proof of concept experiments with mixtures of in vivo fluorescence labelled skin cell types allowed the test of the new algorithms performance for the identification of specific cell types. The intense training of the software systems with various samples resulted in a increased sensitivity and specificity of the combined midIR and software system. These data highlight the potential of midIR spectroscopy as sensitive and specific future optical biopsy technology.
The rapid inspection of suspicious skin lesions for pathological cell types is the objective of optical point of care diagnostics technologies. A marker free fast diagnosis of skin malignancies would overcome the limitations of the current gold standard surgical biopsy. The time consuming and costly biopsy procedure requires the inspection of each sample by a trained pathologist, which limits the analysis of potentially malignant lesions. Optical technologies like RAMAN or infrared spectroscopy, which provide both, localization and chemical information, can be used to differentiate malignant from healthy tissue by the analysis of multi cell structures and cell type specific spectra. We here report the application of midIR spectroscopy towards fast and reliable skin diagnostics. Within the European research project MINERVA we developed standardized in vitro skin systems with increasing complexity, from single skin cell types as fibroblasts, keratinocytes and melanoma cells, to mixtures of these and finally three dimensional human skin equivalents. The standards were characterized in the established midIR range and also with newly developed systems for fast imaging up to 12 μm. The analysis of the spectra by novel data processing algorithms demonstrated the clear separation of all cell types, especially the tumor cells. The signals from single cell layers were sufficient for cell type differentiation. We have compared different midIR systems and found all of them suitable for specific cell type identification. Our data demonstrate the potential of midIR spectroscopy for fast image acquisition and an improved data processing as sensitive and specific optical biopsy technology.
FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical
phenomena that require special processing. Little work has been done in the field with the aim of registering
hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained
histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant
structures that the pathologist may identify in the gold standard HE images. A two-step registration framework
is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This
representative image, which must have a spatial contrast as similar as possible to a gray image obtained from
the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the
registration algorithm a similarity transformation is estimated from interest points, which are automatically
detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in
the frequency domain compensates for local anatomical variations between both images. After a proper tuning
of some parameters the proposed registration framework works in an automated way. The method was tested on
7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were
obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).