Abstract #2855

Optimized truncation to integrate multi-channel MRS data using rank-R singular value decomposition (OpTIMUS)

Dongsuk Sung¹, Benjamin B Risk², Maame Owusu-Ansah³, Xiaodong Zhong⁴, Hui Mao³, and Candace Fleischer^1,3

¹Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States, ²Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States, ³Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States, ⁴MR R&D Collaborations, Siemens Healthcare, Los Angeles, CA, United States

Multi-channel phased array coils facilitate acquisition of fast, localized, and high signal-to-noise ratio (SNR) magnetic resonance spectroscopy (MRS) data. As individual spectra are acquired from multiple coil channels, it is necessary to combine these data to form a final spectrum. Here, we present an improved approach for combining multi-channel phased array data using spectral windowing followed by a rank-R singular value decomposition (SVD). Our approach, termed ‘OpTIMUS’ was evaluated using SNR and compared to combination methods including whitened SVD (WSVD), S/N² weighting, and the vendor-supplied reconstruction. OpTIMUS generated the highest SNR across all methods.

This abstract and the presentation materials are available to members only; a login is required.

Join Here