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.