MP-PCA denoising of kinetic 13C-MR spectra of human liver: performance analysis for synthetic and in vivo data

Motivation: Need to improve determination of kinetics for low-concentration metabolites using X-nuclear MRS. Goal(s): Investigate potential benefits of denoising by Marchenko-Pastur Principal Component Analysis (MP-PCA) for extracting natural-abundance glycogen kinetics from 13C-MRS data. Approach: MP-PCA applied on synthetic and human in-vivo hepatic 13C-MRS time-course datasets. Results: MP-PCA substantially improves apparent SNR and reduces mean linear regression residuals, without introducing bias in slope estimates. MP-PCA is shown to be valuable for the determination of unknown physiologic time-courses of low-concentrated glycogen signals; here, specifically enabling use of lower D-glucose loads in combined deuterium metabolic imaging and 13C-MRS evaluations of hepatic glucose metabolism. Impact: Our findings on MP-PCA's efficacy in enhancing the determination of glycogen kinetics by 13C-MRS broaden the understanding of denoising techniques in MR spectroscopy and ultimately impact researchers and clinicians who develop, assess, or apply MR techniques suffering from low SNR.