17 February 2017 Performance of mid infrared spectroscopy in skin cancer cell type identification
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Abstract
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.
Conference Presentation
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Lena Kastl, Björn Kemper, Gavin R. Lloyd, Jayakrupakar Nallala, Nick Stone, Valery Naranjo, Francisco Penaranda, Jürgen Schnekenburger, "Performance of mid infrared spectroscopy in skin cancer cell type identification", Proc. SPIE 10060, Optical Biopsy XV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1006006 (17 February 2017); doi: 10.1117/12.2253314; https://doi.org/10.1117/12.2253314
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