Abstract #1269

Multi-compartment susceptibility source separation (mc-chi-separation) using GRE data only: Integrated model of QSM and myelin water imaging

Hyeong-Geol Shin^1,2, Shiv Saidha³, Jongho Lee⁴, Peter A. Calabresi³, Peter van Zijl^1,2,5, and Xu Li^2,5

¹Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States, ³Department of Neurology, Johns Hopkins University, Baltimore, MD, United States, ⁴Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea, Republic of, ⁵Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States

Synopsis

Keywords: Electromagnetic Tissue Properties, Susceptibility

Motivation: Chi-separation enables separate estimation of diamagnetic myelin and paramagnetic iron, but requires quantitative R2 measurements, limiting its application.

Goal(s): To develop a new chi-separation method combining both macroscopic and microscopic field perturbation information to perform chi-separation using only GRE data.

Approach: We propose multi-compartment chi-separation (mc-chi-separation) that models effects of myelin and water compartmentalization on transverse relaxation (as in myelin water imaging [MWI]) as well as their contributions to bulk susceptibility (as in QSM).

Results: Mc-chi-separation successfully estimates iron and myelin distributions with higher SNR and reduced sensitivity to B₀-field inhomogeneity compared to MWI, while maintaining contrast comparable to conventional chi-separation.

Impact: Mc-chi-separation enhances susceptibility source separation by enabling chi-separation using GRE data only, expanding its applications to clinical settings and pre-acquired data lacking R2 measurements. This may also facilitate better monitoring of iron and myelin-related neurodegenerative disease with reduced inter-site variability.

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