Background: In vivo characterisation of breast tumors using protein (1H) MR spectroscopy relies upon in vitro interpretation of tissue samples. The present study has investigated metabolite composition in extracts from breast tumors and non-involved breast tissue. Multivariate data analysis was used to determinate combinations of metabolites important for differentiation.
Materials and methods: Tumor and non-involved breast tissue were obtained from 16 patients undergoing surgical treatment. 1H NMR spectra of perchloric acid tissue extracts were obtained at a BRUKER Avance DRX600 spectrometer. The data was analysed using principal component analysis and probabilistic neural networks.
Results: Low levels of glucose and high content of choline compounds were dominant findings in the tumor spectra. Principal component loadings demonstrated this strong association. The spectra were correctly classified using neural network analysis.
Conclusions: Large differences in the metabolite composition of breast tumors and surrounding breast tissues have been documented.