Susceptibility source separation from gradient echo data using magnitude decay modeling

• Published in: Journal of neuroimaging Vol. 32; no. 5; p. 852
• Main Authors: Dimov, Alexey V, Nguyen, Thanh D, Gillen, Kelly M, Marcille, Melanie, Spincemaille, Pascal, Pitt, David, Gauthier, Susan A, Wang, Yi
• Format: Journal Article
• Language: English
• Published: United States 01.09.2022
• Subjects: Biomarkers; Humans; Magnetic Resonance Imaging - methods; Multiple Sclerosis - diagnostic imaging; Multiple Sclerosis - pathology; Myelin Sheath - pathology; Water; iron quantification; myelin quantification; quantitative susceptibility mapping; susceptibility source separation
• ISSN: 1552-6569
• DOI: 10.1111/jon.13014

The objective is to demonstrate feasibility of separating magnetic sources in quantitative susceptibility mapping (QSM) by incorporating magnitude decay rates in gradient echo (GRE) MRI. Magnetic susceptibility source separation was developed using and compared with a prior method using that required an additional sequence to measure the transverse relaxation rate R . Both susceptibility separation methods were compared in multiple sclerosis (MS) patients (n = 17). Susceptibility values of negative sources estimated with -based source separation in a set of enhancing MS lesions (n = 44) were correlated against longitudinal myelin water fraction (MWF) changes. In in vivo data, linear regression of the estimated and susceptibility values between the - and the -based separation methods performed across 182 segmented lesions revealed correlation coefficient r = .96 and slope close .99. Correlation analysis in enhancing lesions revealed a significant positive association between the increase at 1-year post-onset relative to 0 year and the MWF increase at 1 year relative to 0 year (β = -0.144, 95% confidence interval: [-0.199, -0.1], p = .0008) and good agreement between and methods (r = .79, slope = .95). Separation of magnetic sources based solely on GRE complex data is feasible by combining magnitude decay rate modeling and phase-based QSM and change may serve as a biomarker for myelin recovery or damage in acute MS lesions.