An FTIR image of an 8 µm section of de-paraffinised bronchial biopsy that shows a histological transition from normal to severe dysplasia/squamous cell carcinoma (SCC) insitu was obtained in transmission by stitching together images of 256 x 256 µm recorded using a 96 x 96 element FPA detector. Each pixel spectrum was calculated from 128 co-added interferograms at 4 cm−1 resolution. In order to improve the signal to noise ratio, blocks of 4x4 adjacent pixels were subsequently averaged. Analyses of this spectral image, after conversion of the spectra to their second derivatives, show that the epithelium and the lamina propria tissue types can be distinguished using the area of troughs at either 1591, 1334, 1275 or 1215 cm−1 or, more effectively, by separation into two groups by hierarchical clustering (HCA) of the 1614-1465 region. Due to an insufficient signal to noise ratio, disease stages within the image could not be distinguished with this extent of pixel averaging. However, after separation of the cell types, disease stages within either the epithelium or the lamina propria could be distinguished if spectra were averaged from larger, manually selected areas of the tissue. Both cell types reveal spectral differences that follow a transition from normal to cancerous histology. For example, spectral changes that occurred in the epithelium over the transition from normal to carcinoma insitu could be seen in the 1200-1000 cm−1 region, particularly as a decrease in the second derivative troughs at 1074 and 1036 cm−1 , consistent with changes in some form of carbohydrate. Spectral differences that indicate a disease transition from normal to carcinoma in the lamina propria could be seen in the 1350-1175 cm−1 and 1125-1030 cm−1 regions. Thus demonstrating that a progression from healthy to severe dysplasia/squamous cell carcinoma (SCC) insitu can be seen using FTIR spectroscopic imaging and multivariate analysis.
Attenuated total reflection (ATR)-FTIR spectroscopy is a convenient technique for analysing biomedical samples because of its sensitivity to subtle compositional changes, speed of data acquisition and ease of sample preparation. We have applied the technology to the detection of disease biomarkers in urine and investigated the translation of these diagnostic methods to simple bench-top spectrometers. To demonstrate the use of ATR-FTIR spectroscopy as a bedside diagnostic tool, we have installed a roomtemperature bench-top infrared spectrometer in the renal unit at the Royal Free Hospital (RFH), London. A nurse recorded spectra of urine from patients with a range of conditions, including diabetes, kidney disease, stone disease and urinary tract infections, and the data were correlated to medical conditions to assess the diagnostic capabilities of the system and to identify potential spectral patterns associated with disease. Two hundred and six spectra have been recorded to date; these show it is possible to detect urea, creatinine, protein, lipids, sugars and other minor metabolites, including potential disease biomarkers. Several spectral peaks of potential diagnostic interest were identified that show variations between normal and disease samples.
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