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Abstract #1253

Model-based frequency-and-phase correction of 1H-MRS data with 2D linear-combination modeling

Dunja Simicic1,2, Helge Jörn Zöllner1,2, Christopher William Davies-Jenkins1,2, and Georg Oeltzschner1,2
1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Synopsis

Keywords: Signal Modeling, Spectroscopy, MRS; Frequency-and-phase correction; linear-combination modeling; 2D-modeling

Motivation: Retrospective frequency-and-phase correction (FPC) methods like spectral registration struggle at low SNR.

Goal(s): To develop model-based correction FPC with simultaneous 2D fitting of all transients. To compare its performance to conventional FPC.

Approach: Inclusion of all transients (without prior FPC) into a 2D linear-combination model with frequency and phase parameters for each transient. Comparison with conventional approach (spectral registration, averaging and 1D modeling). Outcome measures: frequency/phase/amplitude ground truth error & standard deviation, amplitude CRLB.

Results: Model-based FPC is feasible and retrieves frequency/phase variations with high fidelity. At low SNR, frequency and metabolite amplitude estimation is more accurate and precise.

Impact: Direct integration of frequency-and-phase correction into 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, e.g., long TEs, strong diffusion weighting, etc.

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