Simultaneous PET/fMRI for imaging neuroreceptor dynamics
Author(s)Sander, Christin Y. (Christin Yen-Ming)
Simultaneous positron emission tomography/functional magnetic resonance imaging for imaging neuroreceptor dynamics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Bruce R. Rosen and Joseph B. Mandeville.
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Whole-brain neuroimaging is a key technique for studying brain function and connectivity. Recent advances in combining two imaging modalities - magnetic resonance imaging (MRI) and positron emission tomography (PET) - into one integrated scanner, have created the opportunity to explore the underlying neurochemistry of brain function in more detail. Imaging these dynamics plays an important role for understanding drug action and function of neurochemical pathways in the brain and is crucial, yet largely unexplored, for creating and evaluating treatment of neurological and psychiatric disorders. In this thesis, we first address technological challenges in simultaneous PET/MRI by designing, building and evaluating PET compatible MR probes for brain imaging, which enable highly sensitive dual modality imaging. We then develop simultaneous imaging methods with PET and functional MRI to assess and validate relationships between receptor occupancy and changes in brain activity due to pharmacological challenges targeting the dopamine system. Our results indicate that dopamine receptor occupancies and vascular responses are correlated in anatomical space and with pharmacological dose. Moreover, the temporal dynamics of the signals show that a direct neurovascular coupling between receptor occupancy and hemodynamics exists and that a temporal divergence between PET and fMRI can be used to investigate previously unexplored neurochemical parameters and adaptation mechanisms in vivo. Overall, our findings provide insight into dopaminergic receptor dynamics and their effects on high-level brain function, paving a way to address receptor-specific brain dysfunction effectively.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 147-158).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.