Steve Conolly’s research while affiliated with University of California, Berkeley and other places

Magnetic particle imaging is an emerging tomographic technique with the potential for simultaneous high-resolution, high-sensitivity, and real-time imaging. Magnetic particle imaging is based on the unique behavior of superparamagnetic iron oxide nanoparticles modeled by the Langevin theory, with the ability to track and quantify nanoparticle concentrations without tissue background noise. It is a promising new imaging technique for multiple applications, including vascular and perfusion imaging, oncology imaging, cell tracking, inflammation imaging, and trauma imaging. In particular, many neuroimaging applications may be enabled and enhanced with magnetic particle imaging. In this review, we will provide an overview of magnetic particle imaging principles and implementation, current applications, promising neuroimaging applications, and practical considerations.

Superparamagnetic iron oxide (SPIO) nanoparticles with optimized and well-characterized properties are critical for Magnetic Particle Imaging (MPI). MPI is a novel in vivo imaging modality that promises to integrate the speed of X-ray CT, safety of MRI and sensitivity of PET. Since SPIOs are the source of MPI signal, both the core and surface properties must be optimized to enable efficient in vivo imaging with pharmacokinetics tailored for specific imaging applications. Existing SPIOs like Resovist (ferucarbotran) provide a suboptimal MPI signal, and further limit MPI's in vivo utility due to rapid systemic clearance. An SPIO agent with a long blood half-life (t1/2) would be a versatile MPI tracer with widespread applications. Here we show that a long circulating polyethylene glycol (PEG)-coated SPIO tracer, LS-008, provides excellent colloidal stability and a persistent intravascular MPI signal, showing its potential as the first blood pool tracer optimized for MPI. We evaluated variations of PEG coating and found that colloidal stability of tracers improved with the increasing PEG molecular weight (keeping PEG loading constant). Blood circulation in mice, evaluated using Magnetic Particle Spectrometry (MPS), showed that the t1/2 of SPIO tracers varied with both PEG molecular weight and loading. LS-008, coated with 20 kDa PEG at 18.8% loading capacity, provided the most promising long-term colloidal stability with a t1/2 of about 105 minutes in mice. In vivo MPI imaging with LS-008 using a 7 T/m/μ0 3D x-space MPI mouse scanner revealed a prolonged intravascular signal (3-5 hours) post-injection. Our results show the optimized magnetic properties and long systemic retention of LS-008 making it a promising blood pool MPI tracer, with potential to enable MPI imaging in cardio- and cerebrovascular disease models, and solid tumor quantification and imaging via enhanced permeation and retention.

Introduction Numerous perfusion imaging techniques have been developed based on nuclear medicine, MRI, CT, and ultrasound.1 A key enabler of perfusion imaging is the high contrast inherent to nuclear medicine, which sees only a tracer and does not see tissue. Magnetic Particle Imaging (MPI) is an emerging molecular imaging modality that, like nuclear medicine, sees only a tracer and does not see tissue.2–5 Because of MPI’s high contrast, high sensitivity, and signal linearity independent of depth, we believe MPI will excel at perfusion imaging. As we push MPI towards quantitative perfusion imaging (blood volume, blood flow, mean transit time), we must first demonstrate high contrast imaging of the blood volume. Continued technical development to reduce scan times will enable quantitative measurement of blood flow and mean transit time. Here we demonstrate the first step, blood volume imaging, in vivo in rats with a tailored MPI-specific nanoparticle tracer. Methods 1mg LodeSpin SPIOs were injected into the tail vein of anesthetized Fischer 344 rats and imaged in a home-built MPI scanner with respiratory gating or imaged following sacrifice. Images were reconstructed using x-space reconstruction and equalized or deconvolved. All experiments were conducted under an approved animal protocol. Results Preliminary results for MPI blood pool imaging are shown in Figure 1. In Figure 1A, we see an MPI image of the thorax image of a live animal. In Figure 1B, we see the brain of the same animal following sacrifice two hours after injection. Figure 1C, we see brain vasculature, the jugular veins, the outline of the heart wall, and the lungs in an animal sacrificed immediately following injection. In Figure 1E we see the lungs, the liver, and the kidneys of the same animal. Conclusion MPI shows great promise as a sensitive, high-contrast, and radiation-free technique for measuring brain perfusion, brain vasculature, and organ perfusion. Acknowledgments The authors acknowledge support from the following research grants: NIH 5R01EB013689–03, CIRM RT2–01893, Keck Foundation 034317, NIH 1R24MH106053–01, NIH 1R01EB019458–01, ACTG 037829, and NIH 2R42EB013520–02A1. References Disclosures P. Goodwill: 4; C; Magnetic Insight, Inc. 5; C; Magnetic Insight, Inc. M. Ferguson: 4; C; LodeSpin Labs. E. Yu: None. B. Zheng: None. K. Lu: None. A. Khandhar: 4; C; LodeSpin Labs. S. Kemp: 4; C; LodeSpin Labs. K. Krishnan: 4; C; LodeSpin Labs. S. Conolly: 4; C; Magnetic Insight, Inc.

In this work,a method to achieve higher, more isotropic resolution for x-space MPI through analyzing various FFP trajectories and developing multidimensional transmit/receive hardware was presented. However, many parameters remain to be optimized for this technique, including the various tradeoffs between pFOV coverage, scanning speed, and resolution. Additional hardware challenges include precise control of the FFP through controlling the phase of the transmit fields and compensating for received particle signal based the anisotropic sensitivity profiles of the transmit and receive coils.

MPI is intrinsically a linear and shift-invariant (LSI) system as described in x-space theory [3,4] assuming perfect signal acquisition and that the imaging equation can be written as a convolution in realspace. However, the received MPI signal is corrupted by a direct feedthrough signal from the excitation source at the drive frequency, which is 106 times larger than the nanoparticle signal. Hardware filtering is required to suppress the feedthroughsignalbutalso inevitably removes this frequency component from the particle signal. This signal loss in the received particle signalbreaks the LSI propertiesof x-space MPI. This study will investigate the impact of losing the fundamental frequency component in the image domain and propose an algorithm to recover the lost information. Finally, experimental results demonstrate that LSI propertiescan be restored after applying a simple and robust baseline recovery algorithm.