Title | Susceptibility source separation from gradient echo data using magnitude decay modeling. |
Publication Type | Journal Article |
Year of Publication | 2022 |
Authors | Dimov AV, Nguyen TD, Gillen KM, Marcille M, Spincemaille P, Pitt D, Gauthier SA, Wang Y |
Journal | J Neuroimaging |
Volume | 32 |
Issue | 5 |
Pagination | 852-859 |
Date Published | 2022 Sep |
ISSN | 1552-6569 |
Keywords | Biomarkers, Humans, Magnetic Resonance Imaging, Multiple Sclerosis, Myelin Sheath, Water |
Abstract | BACKGROUND AND PURPOSE: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. |
DOI | 10.1111/jon.13014 |
Alternate Journal | J Neuroimaging |
PubMed ID | 35668022 |
Grant List | R01 NS102267 / NS / NINDS NIH HHS / United States R01 NS105144 / NS / NINDS NIH HHS / United States R21 AG067466 / AG / NIA NIH HHS / United States S10 OD021782 / OD / NIH HHS / United States |