Deuterium metabolic imaging (DMI) is a novel method to obtain images of dynamic metabolism in the living human brain. While DMI is generally simple and robust, small signals from deuterated skull lipids can distort the metabolic information within the brain. Here, we use MRI-based information on brain and skull locations to remove lipid signals from DMI data. With an average 90 % lipid removal, DMI is used to generate distinct and artifact-free metabolic maps on patients with brain tumors.

Detailed interpretation of brain MRI data is hampered by the fact that each imaging voxel comprises several types of cells and tissues. To address this, we adapt signal encoding and data inversion strategies from solid-state and low-field NMR to quantify the sub-voxel heterogeneity of the human brain with 5D relaxation–diffusion distributions wherein distinct tissue components are resolved, individually characterized, and subsequently mapped throughout the volume of the brain.