Keywords: Low-Field MRI, Brain Connectivity, Connectomics
Motivation: Neuroscience MRI research, including assessment of structural connectomics, has been largely limited to high-resource settings.
Goal(s): To democratise assessment of brain connectivity by demonstrating the first ever diffusion-weighted imaging (DWI)-based connectomics at 64 mT.
Approach: 15-direction DWI data were acquired at 64 mT. Whole-brain tractograms were recovered after deep learning based denoising and constrained spherical deconvolution. Whole-brain adjacency matrices and graph-theory parameters were extracted, and their test-retest agreement and variability assessed. For one subject, results were compared to high-field MRI.
Results: Global graph-theory parameters (e.g., small-worldness) showed high test-retest agreement. However, inter-hemispheric connectivity was overestimated at 64 mT compared to high-field results.
Impact: Our unique combinations of low-field (64 mT) diffusion-weighted imaging, denoising, spherical deconvolution and connectomics opens up new research opportunities, allowing the assessment of structural connectivity and network neuroscience studies of under-served populations where this has never previously been possible.
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