Assistant Professor
Strategic program(s):
Biography
My mission is to bring cutting-edge metabolic imaging technologies from the research lab into clinical application. My work sits at the intersection of MR physics, neuro-oncology, and metabolism, and is driven by the conviction that understanding altered metabolic pathways in the human brain will transform how we diagnose and treat neurological disease.
I have a background in biomedical engineering (UTwente) and during my PhD I specialized in MR spectroscopy (Radboud umc, Nijmegen). Trough personal research grants (NWO-VENI and WKZonderzoeksfonds) I was able to built my own research line in which I use various x-nuclei MR spectrscopy techniques (e.g., 31P MRSI, deuterium metabolic imaging, 13C-MRS) to study metabolism in various neurological pathologies.
Research aim
Our research lines incorporate inventions of MR technology to be able to see the unseen for advancing medicine. Our clinical research focus areas are cancer, dementia, cardiovascular, stroke and MSK.
Go to groupResearch aim
We use longitudinal fetal and neonatal neuroimaging and neuromonitoring to study brain development and function, model brain diseases, and improve long term outcome in high-risk infants.
Go to group2023 Co-applicant and WP-leader research grant from the Dutch NWO Perspectief program entitled ‘CHIME: Cerebral HemodynamIcs, Metabolism and clearancE: A comprehensive, non‐invasive brain imaging approach to characterize key biological processes in dementia’
2023 Rudolf Magnus Young Talent Fellowship ‘Identification of epileptogenic brain tissue using deuterium metabolic imaging (DMI)’
2022 Co-PI research grant Dutch cancer society (KWF), entitled: ‘Early detection of brain tumour progression with amide proton transfer weighted CEST MRI’
2021 Personal research grant from the Wilhelmina Children’s Hospital Fund, entitled: ‘Exploring vascular and metabolic maturation of the preterm brain with 7T MRI’
2020 Personal research grant from the Dutch NWO Talent Programme (Veni), entitled: ‘No need to wait? Predicting brain cancer therapy response with metabolic MRI’
