Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates


Recent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter scale subcortical brain structures in humans. QSM reflects the magnetic susceptibility arising from the spatial distribution of iron, myelin, and calcium in the brain. The simultaneous visualization of cortical, subcortical, and white matter structure remains, however, challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortical and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first established QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analyses methods allowed a similar accurate delineation of subcortical structures in humans. Moreover, applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of the brain tissue types as compared to the single T1 contrast. Furthermore, we validate our dual-contrast fusion approach in humans and similarly demonstrate improvements in automated segmentation of cortical and subcortical structures. We believe the proposed contrast will facilitate translational studies in non-human primates to investigate the pathophysiology of neurodegenerative diseases that affect the subcortical structures of the basal ganglia in humans.

Rakshit Dadarwal
Rakshit Dadarwal
Postdoctoral Researcher

My research focuses on the acquisition and processing of multi-contrast magnetic resonance imaging (MRI) data. I am particularly interested in imaging myelin and iron in the central nervous system and studying healthy aging in non-human primates using Diffusion-weighted Imaging (DWI), Quantitative Susceptibility Mapping (QSM), Magnetization Transfer Imaging, and T1 and T2-relaxometry.