Impaired glucose homeostasis and mitochondrial dysfunction are key components of neurodegenerative, metabolic, and psychiatric diseases, such as Alzheimer’s, schizophrenia, and depression. Therefore, an affordable, reliable, and easy-to-apply method to measure brain glucose metabolism is emergently needed. The development of the noninvasive technique, which allows objective, dynamic and longitudinal tracking of brain alterations in health, disease, and aging was a primary goal of our work. To date, techniques such as PET allow to solely measure glucose consumption but do not allow to quantify the downstream metabolism of glucose, affected in the brain diseases. To address this issue, we have focused on developing novel quantitative and noninvasive glutamate MR measures. Glutamate (Glu) is the most abundant neurotransmitter and the downstream component of the Glc metabolism thus considered a key marker of oxidative brain metabolism. Indeed, glutamatergic impairments are fundamentally involved in the pathophysiology of several neurological and neuropsychiatric disorders and are a significant target of emerging therapies. A novel ground-breaking accelerated method for ultra-short echo time proton (1H) MRS imaging (UTE-MRSI), developed and fine-tuned for the project by our team at the High-field MR Centre, Medical University of Vienna, indeed offers critical sensitivity improvements for Glu quantification compared to conventional SV-MRS and previous MRSI approaches. Hence, the proposed improved version of the UTE-MRSI technique will allow image-based multi-slice measurements of baseline Glu concentration and tracking Glu responses to brain activation. These measures are essential for accurate mapping of metabolic changes and treatment responses in severe neurological and psychiatric brain diseases such as depression, schizophrenia, epilepsy, and Alzheimer’s disease. In the current project, we established a highly reproducible MRSI technique to map and visualize endogenous Glu in the resting and activated human brain regions. We significantly improved an innovative noninvasive UTE-MRSI method that provided superior spatial resolution and coverage compared to SV-MRS, and we validated its feasibility to detect Glu oscillations in the resting and activated human brain.
