Magnetic Particle Imaging (MPI) Tracers for In Vivo Applications
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Arami, Hamed
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Abstract
Magnetic particle imaging (MPI) is a real-time, quantitative and clinically safe imaging technique, potentially applicable for future clinical applications such as cancer imaging, cardiovascular imaging or stem cell labeling and tracking. MPI performance (i.e. spatial resolution and sensitivity) is highly dependent on nanoparticles (NPs) size distribution, magnetization and environment. Therefore, NPs MPI signal is different after distribution into tissues or binding to the cells. In this project, we evaluated the potential capabilities of MPI for tissue targeted imaging applications such as cancer imaging. To do this, we used two preliminary experimental models to predict the performance of the tracers in a tissue equivalent environment and an acidic lysosome-like solution. For efficient targeting and specific binding of the NPs to specific cells (e.g. cancers), it is required to conjugate additional biomolecules that can be recognized by receptors on the membranes of these cells. Therefore, we introduced functional groups (such as amine, carboxyl and maleimide groups) to the surface of our optimized MPI tracers and used them for bonding of a brain cancer targeting peptide (lactoferrin) to the NPs and evaluated the targeting efficacy of these MPI tracers using an in vivo glioma xenograft model. We also conjugated Cy5.5 near infra-red fluorescent (NIRF) molecules to these functional groups and evaluated NPs performance as multimodal MPI tracers. This additional modality enabled us to study the biodistribution and pharmacokinetics of our optimized MPI tracers more accurately, since NIRF revealed more details of microstructural distribution of the NPs in different organs. In addition, we investigated the pharmacokinetics and biodistribution of the intravenously injected NPs and evaluated MPI performance of the NPs after their accumulation in reticuloendothelial system (RES) organs (e.g. liver and spleen), and glioma xenografts.
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Thesis (Ph.D.)--University of Washington, 2015-12
