MRI Research Amsterdam UMC

Neuro MRI

Functional brain imaging: task-based application and interventional studies

Technical advances in functional MRI have allowed us to study dynamic (neurochemical) processes in the brain in response to a task, a pharmacological challenge or physiological intervention. Several hemodynamic MR techniques can be used to assess these functional brain changes, including BOLD functional MRI (fMRI) and Arterial Spin Labelling (ASL). Functional MRI protocols targeting numerous cognitive and behavioral domains have successfully been applied in collaboration with several departments in the Amsterdam UMC (e.g. Internal Medicine, Psychiatry, and Neurology). Furthermore, we focus on validation (e.g., with respect to SPECT/PET imaging) and application of interventions during state-of-the art functional MRI acquisitions (either pharmacological or physiological (e.g. food or exercise)).

Functional Magnetic Resonance Spectroscopy in the brain

Proton Magnetic Resonance Spectroscopy (1H-MRS) can non-invasively measure the concentration of neurometabolites, such as glutamate and lactate. Using this technique, abnormalities in neurometabolite concentrations were demonstrated in numerous psychiatric and neurological disorders, including schizophrenia and adrenoleukodystrophy. Functional magnetic resonance spectroscopy (fMRS) represents an adaptation of the MRS technique that measures the fluctuations of metabolite concentrations while the subject performs a mental task and allows the measurement of changes in the concentration of metabolites during neural activity. This could provide novel insights into abnormal neurometabolite signaling in patients with brain disorders, and we are currently in the process of validating these measurements in a variety of task protocols.

Neuroimaging Processing and Analysis Infrastructure

At Amsterdam UMC, our focus is on developing innovative imaging biomarkers and establishing a robust neuroimaging infrastructure for processing and analyzing such images. For example, in one project we aim to deliver reliable consensus QC metrics and thresholds for neuroimaging biomarkers. These biomarkers, derived from MRI scans, are essential for early diagnosis and staging of neurological disorders. However, their reliability is greatly influenced by image quality, which can be affected by multiple factors. To address this issue, we are developing automated imaging quality control strategies that combine physics and AI-based methods. Our aim is to improve the precision and sensitivity of MRI biomarkers for clinical trials, which will have a significant impact on patient care.

Affiliated with:

Amsterdam Neuroscience