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Abstract #1319

Novel methodology for processing, quality assessment, and artifact mitigation of raw 2D Correlation Spectroscopy data

Laura J Mariano1, Marcia Sahaya Louis2, Benjamin Rowland3, Huijun Liao4, Kristin Heaton5, John Irvine1, and Alexander P Lin3,6

1The Charles Stark Draper Laboratory, Inc., Cambridge, MA, United States, 2Electrical and Computer Engineering, Boston University, Boston, MA, United States, 3Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, United States, 4Psychiatric Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, United States, 5US Army Institute of Environmental Medicine, Natick, MA, United States, 6Harvard Medical Institute, Boston, MA, United States

2D Correlation Spectroscopy (COSY) can be used to identify and study coupled resonances that cannot be observed or distinguished in 1D NMR spectra. However, resources and literature on best practices for processing raw 2D COSY data are limited. In this work, we describe a novel pipeline of signal processing algorithms and visualizations for quality assessment and artifact mitigation designed specifically for raw 2D COSY data, including detection of residual H2O and lipid contamination, correction for drift across averages, and peak location correction to enable more accurate comparisons of metabolites across subjects.

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