The magnetic particle imaging (MPI) imaging process is a new method of medical imaging with great promise. In this paper we derive the 1-D MPI signal, resolution, bandwidth requirements, signal-to-noise ratio (SNR), specific absorption rate, and slew rate limitations. We conclude with experimental data measuring the point spread function for commercially available SPIO nanoparticles and a demonstration of the principles behind 1-D imaging using a static offset field. Despite arising from the nonlinear temporal response of a magnetic nanoparticle to a changing magnetic field, the imaging process is linear in the magnetization distribution and can be described as a convolution. Reconstruction in one dimension is exact and has a well-behaved quasi-Lorentzian point spread function.The spatial resolution improves cubically with increasing diameter of the SPIO domain, inverse to absolute temperature, linearly with saturation magnetization, and inversely with gradient. The band width requirements approach a megahertz for reasonable imaging parameters and millimeter scale resolutions, and the SNR increases with the scanning rate. The limit to SNR as we scale MPI to human sizes will be patient heating. SAR and magnetostimulation limits give us surprising relations between optimal scanning speeds and scanning frequency for different types of scanners.

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Ultrasound is among the most widely used non-invasive imaging modalities in biomedicine1, but plays a surprisingly small role in molecular imaging due to a lack of suitable molecular reporters on the nanoscale. Here we introduce a new class of reporters for ultrasound based on genetically encoded gas nanostructures from microorganisms, including bacteria and archaea. Gas vesicles are gas-filled protein-shelled compartments with typical widths of 45–250 nm and lengths of 100–600 nm that exclude water and are permeable to gas2, 3. We show that gas vesicles produce stable ultrasound contrast that is readily detected in vitro and in vivo, that their genetically encoded physical properties enable multiple modes of imaging, and that contrast enhancement through aggregation permits their use as molecular biosensors.

Image-guided treatment of cancer enables physicians to localize and treat tumors with great precision. Here, we present in vivo results showing that an emerging imaging modality, magnetic particle imaging (MPI), can be combined with magnetic hyperthermia into an image-guided theranostic platform. MPI is a noninvasive 3D tomographic imaging method with high sensitivity and contrast, zero ionizing radiation, and is linearly quantitative at any depth with no view limitations. The same superparamagnetic iron oxide nanoparticle (SPIONs) tracers imaged in MPI can also be excited to generate heat for magnetic hyperthermia. In this study, we demonstrate a theranostic platform, with quantitative MPI image guidance for treatment planning and use of the MPI gradients for spatial localization of magnetic hyperthermia to arbitrarily selected regions. This addresses a key challenge of conventional magnetic hyperthermia-SPIONs delivered systemically accumulate in off-target organs ( e.g., liver and spleen), and difficulty in localizing hyperthermia results in collateral heat damage to these organs. Using a MPI magnetic hyperthermia workflow, we demonstrate image-guided spatial localization of hyperthermia to the tumor while minimizing collateral damage to the nearby liver (1-2 cm distance). Localization of thermal damage and therapy was validated with luciferase activity and histological assessment. Apart from localizing thermal therapy, the technique presented here can also be extended to localize actuation of drug release and other biomechanical-based therapies. With high contrast and high sensitivity imaging combined with precise control and localization of the actuated therapy, MPI is a powerful platform for magnetic-based theranostics.

Magnetic particle imaging (MPI) is a promising new medical imaging tracer modality with potential applications in human angiography, cancer imaging, in vivo cell tracking, and inflammation imaging. Here we demonstrate both theoretically and experimentally that multidimensional MPI is a linear shift-in-variant imaging system with an analytic point spread function. We also introduce a fast image reconstruction method that obtains the intrinsic MPI image with high signal-to-noise ratio via a simple gridding operation in x-space. We also demonstrate a method to reconstruct large field-of-view (FOV) images using partial FOV scanning, despite the loss of first harmonic image information due to direct feedthrough contamination. We conclude with the first experimental test of multidimensional x-space MPI.