The pathophysiological processes underlying the development and progression of Alzheimer's disease (AD) on the neuronal level are still unclear. Previous research has hinted at metabolic energy deficits and altered sodium homeostasis with impaired neuronal function as a potential metabolic marker relevant for neurotransmission in AD. Using sodium ( 23 Na) magnetic resonance (MR) imaging on an ultra-high-field 7Tesla MR scanner, we found increased cerebral tissue sodium concentration (TSC) in 17 biomarker-defined AD patients compared to 22 age-matched control subjects in vivo. TSC was highly discriminative between controls and early AD stages and was predictive for cognitive state, and associated with regional tau load assessed with flortaucipir-positron emission tomography as a possible mediator of TSC-associated neurodegeneration. TSC could therefore serve as a non-invasive, stage-dependent, metabolic imaging marker. Setting a focus on cellular metabolism and potentially disturbed interneuronal communication due to energy-dependent altered cell homeostasis could hamper progressive cognitive decline by targeting these processes in future interventions.

Quantitative 23Na MRI provides useful information about brain tissue homeostasis. Most sequences use deterministic non-Cartesian 3D trajectories such as TPI. However, stochastic strategies such as SPARKLING could improve the coverage of k-space. This study evaluates the advantages of SPARKLING versus TPI. From in vivo datasets at 7T, we determined that undersampled SPARKLING acquisitions outperform TPI for (8 mm)3 resolution with a birdcage coil or for (4 mm)3 with a 32-channel coil. Through extrapolation of these results, we predict that at 11.7T/32-channel, 23Na MRI data could be acquired in 90s at (3 mm)3, which could be interesting for sodium fMRI imaging.

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