GENERALIZED EFFICIENT NMR SPECTRAL LOCALIZATION

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The broad, long-term objectives of this project are to extend and perfect a general solution to the problem of localizing nuclear magnetic resonance spectra for biomedical research and clinical applications. Existing partial solutions to this problem attempt to define one or more regions whose shapes are determined by the nature of the equipment or technique, and to place these within the organ or lesion of interest. The method proposed here can use anatomical information, as obtained routinely by standard MRI methods, to define any number of volumes of any shape. If desired, it can be used to define the rectangular volume elements characteristic of more specialized techniques as well. Decisions concerning boundaries, locations and numbers of regions can be changed retrospectively. This information may be combined mathematically with spectroscopic data, such as those from 31P spectra of phosphorus metabolites, 1H spectra of lactate and neurotransmitters and 13C spectra of metabolites, to give the spectra and concentration of these substances in all anatomical regions simultaneously, but in a much shorter time than required for conventional chemical shift imaging. This can be accomplished with fewer and less stringent demands on the imaging system than those made by less general methods, requiring no hardware changes and minimal changes in operating procedures (pulse sequences). Only modest additions to signal processing software are required. Careful study of optimum procedures and data analysis are required to make the full possibilities of these new techniques reliably available for practical use, so that in vivo spectroscopy can become a routine part of many magnetic resonance imaging procedures. Careful studies will be made, using computer simulations and phantoms, of the reliability and generality of the method and of its advantages and disadvantages when compared with other methods. The specific aims are: 1) to complete the mathematical analysis of optimal methods for combining imaging and spectroscopic data; 2) to fully analyze the quantitative accuracy of these methods; 3) to create computer programs for the routine use of these new methods in research, and 4) to carry out the necessary tests to verify the effectiveness and reliability of this general solution to the problem of in vivo spectroscopy.