Previous work, predominantly on in-vitro tissue, has studied the amount of 1H and 31P in tissue using magnetic resonance spectroscopy. These are abundant in both the underlying tissue and in metabolites which also allows the activity of tissue to be studied. There are problems in characterising the spectra obtained and neural networks and other artificial intelligence techniques have commonly been employed. However, the classification success is dependent on the quality of the training set data which potentially limits the application of the technique. In addition, the classification provides no information of the structure of the tissue and it is this information which informs diagnosis.
We have developed a theoretical three compartment model of tissue based on the intracellular fluid, extracellular fluid and the cell membranes. These models relate the concentration of chemical species in different compartments to tissue structure. We are currently exploring the use of these models to characterise the cellular structure of tissue using measurement of tissue cultures using NMR spectroscopy facilities in the Department of Physics.