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 Lin^3,6

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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.