Disease changes the bio-chemical composition of cells and tissues, before morphological or structural variations occur. Thus, a fingerprint spectral method, such as infrared microspectroscopy in conjunction with sophisticated mathematical methods for spectral analysis, can be used to detect and diagnose disease in human tissues and cells more accurately, reproducibly and faster than present methods of histopathology and cytopathology. Infrared spectroscopy monitors a snapshot of the inherent vibrational spectra of the biochemical constituents of cells and tissue. These spectra vary between different tissue types, between normal and diseased tissue, and between different states of maturation and differentiation of individual cells. For the diagnosis of cells and tissue, infrared spectral hypercubes are collected microscopically with a spatial resolution determined by the diffraction limit, which is about 10 μm. Schematic diagrams and views of the instrument are shown in Figure 1.
Figure 1. (A) schematic and view (B) of Perkin Elmer Spotlight Infrared Micro-spectrometer: IS: Infrared source, MI: Michelson interferometer, C1, C2: Cassegrain condenser and objective, S: Sample, MCT: HgCdTe single or focal plane array (FPA) detector
Data analysis of the spectral hypercubes is carried out by supervised and unsupervised methods of multivariate analysis to provide pseudo-color maps of tissue sections. Correlation of these spectral maps and histopathology yields spectra which are characteristic of a tissue type. These spectra are used to train artificial neural networks which can be used to analyze unknown data sets. For individual cell spectra, these analysis provide information on cell origin, disease, cellular activity etc.