Abstract

The technique of magic angle spinning (MAS) high resolution (1)H NMR spectroscopy applied to intact tissues provides excellent peak resolution and thus much biochemical information. The use of computer-based pattern recognition techniques to classify human renal cortex tissue samples as normal or tumour based on their (1)H MAS NMR spectra has been investigated. In this preliminary study of 22 paired control and tumour samples, exploratory data analysis using principal components based on NMR spectral intensities showed clear separation of the two classes. Furthermore, using the supervised method of linear discriminant analysis, based on individual data point intensities or on integrated spectral regions, it was possible to distinguish between the normal and tumour kidney cortex tissue with 100% accuracy, including a single example of a metastatic tumour from a primary lung carcinoma. A tumour sample from the collecting duct of the kidney showed a different NMR spectral profile, and pattern recognition indicated that this sample did not classify with the cortical tumours.

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