Laura R. Croft

Magnetic Particle Imaging With Tailored Iron Oxide Nanoparticle Tracers

Magnetic particle imaging (MPI) shows promise for medical imaging, particularly in angiography of patients with chronic kidney disease. As the first biomedical imaging technique that truly depends on nanoscale materials properties, MPI requires highly optimized magnetic nanoparticle tracers to generate quality images. Until now, researchers have relied on tracers optimized for MRI T2*-weighted imaging that are sub-optimal for MPI. Here, we describe new tracers tailored to MPIs unique physics, synthesized using an organic-phase process and functionalized to ensure biocompatibility and adequate in vivo circulation time. Tailored tracers showed up to 3 × greater signal-to-noise ratio and better spatial resolution than existing commercial tracers in MPI images of phantoms.

Ferrohydrodynamic relaxometry for magnetic particle imaging

The ferrohydrodynamic properties of magnetic nanoparticles govern resolution and signal strength in magnetic particle imaging (MPI), a medical imaging modality with applications in small animals and humans. Here, we discuss the development and key results of a magnetic particle relaxometer that measures the core diameter and relaxation constant of magnetic nanoparticles. This instrument enables us to directly measure the one-dimensional MPI point spread function. To elucidate our results, we develop a simplified ferrohydrodynamic model that assumes nanoparticles respond to time varying magnetic fields according to a Debeye model of Brownian relaxation, which we verify with experimental data.

Relaxation in X-Space Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a new imaging modality that noninvasively images the spatial distribution of superparamagnetic iron oxide nanoparticles (SPIOs). MPI has demonstrated high contrast and zero attenuation with depth, and MPI promises superior safety compared to current angiography methods, X-ray, computed tomography, and magnetic resonance imaging angiography. Nanoparticle relaxation can delay the SPIO magnetization, and in this work we investigate the open problem of the role relaxation plays in MPI scanning and its effect on the image. We begin by amending the X-space theory of MPI to include nanoparticle relaxation effects. We then validate the amended theory with experiments from a Berkeley x-space relaxometer and a Berkeley x-space projection MPI scanner. Our theory and experimental data indicate that relaxation reduces SNR and asymmetrically blurs the image in the scanning direction. While relaxation effects can have deleterious effects on the MPI scan, we show theoretically and experimentally that x-space reconstruction remains robust in the presence of relaxation. Furthermore, the role of relaxation in x-space theory provides guidance as we develop methods to minimize relaxation-induced blurring. This will be an important future area of research for the MPI community.

Quantitative stem cell imaging with magnetic particle imaging

MPI stem cell imaging - sensitivity and linearity: 9 pelletized, labeled hESC-derived cell populations (Fig. 2A) with varying cell numbers were imaged successively in the FFL imager. Fig. 2B shows the maximum image intensity from each reconstructed cell pellet image as a function of cell number. When a linear fit was applied, we found a strong linear correlation between MPI signal intensity and cell number, with R2 > 0.99. Additionally, the detection sensitivity of the projection MPI system was found to be slightly over 104 cells. We found no detectable MPI signal from unlabeled cell populations. Mice imaging: A MPI image of postmortem cell injections containing 4×105 and 6×105 is shown in Fig. 2C. The MPI image shows excellent contrast with minimal tissue effects. Additionally, the ratio of total MPI signal between the 6×105 and 4×105 injection regions was found to be 1.5, as expected.

Preliminary experimental X-space color MPI

Previous work has explored the effects of nanoparticle relaxation from the system matrix and x-space reconstruction points of view [1-8]. Here we demonstrate how relaxation can be used to “colorize” an image based on relaxation mechanisms using x-space reconstruction [9] and a pixel-wise linear model.

Low drive field amplitude for improved image resolution in magnetic particle imaging

PURPOSE Magnetic particle imaging (MPI) is a new imaging technology that directly detects superparamagnetic iron oxide nanoparticles. The technique has potential medical applications in angiography, cell tracking, and cancer detection. In this paper, the authors explore how nanoparticle relaxation affects image resolution. Historically, researchers have analyzed nanoparticle behavior by studying the time constant of the nanoparticle physical rotation. In contrast, in this paper, the authors focus instead on how the time constant of nanoparticle rotation affects the final image resolution, and this reveals nonobvious conclusions for tailoring MPI imaging parameters for optimal spatial resolution. METHODS The authors first extend x-space systems theory to include nanoparticle relaxation. The authors then measure the spatial resolution and relative signal levels in an MPI relaxometer and a 3D MPI imager at multiple drive field amplitudes and frequencies. Finally, these image measurements are used to estimate relaxation times and nanoparticle phase lags. RESULTS The authors demonstrate that spatial resolution, as measured by full-width at half-maximum, improves at lower drive field amplitudes. The authors further determine that relaxation in MPI can be approximated as a frequency-independent phase lag. These results enable the authors to accurately predict MPI resolution and sensitivity across a wide range of drive field amplitudes and frequencies. CONCLUSIONS To balance resolution, signal-to-noise ratio, specific absorption rate, and magnetostimulation requirements, the drive field can be a low amplitude and high frequency. Continued research into how the MPI drive field affects relaxation and its adverse effects will be crucial for developing new nanoparticles tailored to the unique physics of MPI. Moreover, this theory informs researchers how to design scanning sequences to minimize relaxation-induced blurring for better spatial resolution or to exploit relaxation-induced blurring for MPI with molecular contrast.

A 7 T/M 3D X-space MPI mouse and rat scanner

This prototype system has already produced high quality images with spatial resolutions very similar to the theoretically predicted resolution across mouse and rat sized FOVs. We have imaged both plastic and biological imaging phantoms, as well as ex vivo mice (not shown). Some early images are shown below in Fig. 1b-c. Imaging times are comparable to micro-MRI: full mouse and rat images (up to 12 cm × 5 cm × 5 cm) require between 2-5 minutes per image.

Third Generation X-Space MPI Mouse and Rat Scanner

Here we describe the construction of our third generation x-space MPI scanner, the fifth MPI scanner built at UC Berkeley. The scanner has two goals, (1) High-resolution native MPI resolution using x-space reconstruction, and (2) extended FOV suitable for mice and rats. In this paper we describe our design criteria, and we show the initial characterizations of the 7 T/m gradient field.

Computational Modeling of Aortic Heart Valves

Computational modeling is an excellent tool with which to investigate the mechanics of the aortic heart valve. The setting of the heart valve presents complex dynamics and mechanical behavior in which solid structures interact with a fluid domain. There currently exists no standard approach, a variety of strategies have been used to address the different aspects of modeling the heart valve. Differences in technique have included the imposition of the load, the portion of the cardiac cycle simulated, the inclusion of the fluid component of the problem, the complexity of anatomical parameters, and the definition of material characteristics. Simplifications reduce computational costs, but could compromise accuracy. As advancements in modeling techniques are made and utilized, more physiologically relevant models are possible. Computational studies of the aortic valve have contributed to an improved understanding of the mechanics of the normal valve, insights on the progression of diseased valves, and predictions of the durability and efficacy of surgical repairs and valve replacements.

Imaging atherosclerotic plaques in vivo using peptide-functionalized iron oxide nanoparticles

Atherosclerosis, or the formation of plaques in the arterial wall, leads to cardiovascular disease, the number one cause of death in the United States. Atherosclerosis develops through multiple stages, which makes it a particularly difficult disease to detect. Markers of these different stages of plaque development have been discovered, however. Our work aims to selectively target and deliver a contrast agent to atherosclerotic plaques through the use of peptides that bind to unique markers of plaque development. Our goal is to use Magnetic Particle Imaging (MPI) to diagnose atherosclerotic plaques.