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Cell therapies, including mesenchymal stem cells (MSC) and regulatory T cells (Tregs) have shown potent and long-lasting therapeutic benefit in several disease applications. Unfortunately, the effectiveness of these therapies is variable and following administration, it is largely unknown where therapeutic cells traffic and how many persist over time. This thesis aims to advance and compare iron- and fluorine-19 (19F)-based magnetic resonance imaging (MRI) and magnetic particle imaging (MPI) for therapeutic cell tracking. First, we developed a trimodal imaging approach to study MSC fate in vivo. In a mouse model, iron-labeled MSC were detected by MRI and MPI, and each modality provided unique information on MSC quantity (MPI) and anatomical localization (MPI) in vivo. In these same mice, 19F MRI was used to assess inflammatory influx to the injection site after intravenous administration of 19F-perfluorocarbon agent. Next, the sensitivity and cellular detection limits of 19F MRI were compared to MPI. MPI showed superior sensitivity, as fewer iron-labeled cells could be detected with MPI (4000 MSCs) compared to 19F-labeled cells with 19F MRI (256,000 MSCs) using the same imaging time. For cell tracking, estimation of cell number is critical, so we sought to develop and test four methods to select and quantify MPI signal from an image. In this project, it is demonstrated that while MPI signal scales directly linear with the amount of iron present, 3 users showed more accurate and precise quantification when they considered a larger area for each signal in the image. In the final chapter, we demonstrate a clinically-applicable 19F MRI imaging approach for tracking in vivo biodistribution of Tregs. This approach involved a dual tuned MRI surface coil with sensitive bSSFP imaging sequence on a 3 Tesla human MRI. The ability to non-invasively quantify and image injected cells in vivo with high sensitivity will improve the efficacy and safety of cell therapy.

Cellular imaging is a rapidly growing field as novel tracers and imaging techniques are developed. Magnetic particle imaging (MPI) detects superparamagnetic iron oxide (SPIO) particles, which can be used to label cells., The type of SPIO has a critical role in determining MPI sensitivity and resolution. For cell tracking applications, the ideal SPIO should label cells efficiently and retain its sensitivity after cellular uptake. VivoTraxTM, a commercially available and commonly used SPIO for MPI, was recently re-released as VivoTrax+ with an improved size distribution enriched for larger particles. In this study, VivoTrax+ is shown to enhance cellular labeling and improve in vitro/in vivo sensitivity. Importantly, the sensitivity of both SPIO significantly decreased after cellular internalization. The results from this study emphasize the importance of translating SPIO performance in vivo to maintain its utility for cell tracking applications. Int. J. Mag. Part. Imag. 8(2), 2022, Article ID: 2210001, DOI: 10.18416/IJMPI.2022.2210001, International Journal on Magnetic Particle Imaging, Vol 8 No 2 (2022)

Magnetic particle imaging (MPI) is an emerging modality that directly detects SPIOs.our first aim is to quantify the dilution of SPIOs in breast cancer cells in vitro using MPI. MPI signal is generated from a combination of Néel (internal rotation of magnetization) and Brownian (physical rotation of nanoparticle) relaxation. Brownian relaxation of SPIO is influenced by the nanoparticle’s surroundings and we hypothesize this may have implications for detecting partially immobilized intracellular SPIOs. A second aim is to determine how MPI signal and resolution change when SPIOs are intracellular (live cells) compared to free SPIOs (lysed cells). A reduction in MPI signal was measured from SPIO-labeled 4T1 cells following proliferation in vitro. Our measurements of intracellular iron are in close agreement with a theoretical reduction of 66%( day 1) and 87% (day 2). Future work will examine this in vivo. As ferucarbotran was incorporated into MSC, a reduction in MPI sensitivity and improvement in resolution were measured for lysed cells. MPI cell tracking is in its infancy and these studies contribute important knowledge towards monitoring proliferative cells in vivo and optimizing resolution and sensitivity for cell detection

Purpose: Magnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions., Procedures: Six users (3 from each institute) imaged a known amount of Vivotrax+ (10 μg Fe), diluted in a small (10 μL) or large (500 μL) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users x triplicate samples x 2 sample volumes x 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax+ quantification, and ROI selection was compared across users, within and across institutions., Results: MPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax+. Overall quantification yielded measurements that were within ± 20% from ground truth, however SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples., Conclusions: This study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental set up, image acquisition parameters, and ROI selection analysis.