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Abstract #4396

Parametric Macromolecular Baseline Assessment Using Prior Knowledge from Inversion Recovery Signals Measured at 9.4 T

Maria Isabel Osorio Garcia1, 2, Diana M. Sima1, 3, Flemming Ulrich Nielsen4, Tom Dresselaers4, Fred Van Leuven5, Sabine Van Huffel1, 2

1Dept. Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Leuven, Belgium; 2IBBT-K.U.Leuven Future Health Department, Leuven, Belgium; 3IBBT-K.U.Leuven Future Health Department, Leuven, Belgium; 4Biomedical Nuclear Magnetic Resonance Unit (MoSAIC), Katholieke Universiteit Leuven, Leuven, Belgium; 5Experimental Genetics Group LEGTEGG, Katholieke Universiteit Leuven, Leuven, Belgium

Besides the metabolites, MRS signals also contain macromolecules and lipids, which are normally observed in the frequency regions between 0.5 and 2 ppm. However, at high magnetic fields, numerous resonances appear along the whole spectrum band. In the frequency domain, these resonances appear as a baseline overlapping with the metabolite peaks, which complicates quantification. In the literature, several advanced acquisition techniques using inversion recovery, parametric and non-parametric methods have been widely used. We propose a parametric way of extracting characteristic resonances from a set of inversion recovery signals using AMARES and include them in the quantification method as additional components.