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Dive into the research topics where Patrick W. Goodwill is active.

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Featured researches published by Patrick W. Goodwill.


IEEE Transactions on Medical Imaging | 2010

The X-Space Formulation of the Magnetic Particle Imaging Process: 1-D Signal, Resolution, Bandwidth, SNR, SAR, and Magnetostimulation

Patrick W. Goodwill; Steven M. Conolly

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 bandwidth 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.


IEEE Transactions on Medical Imaging | 2011

Multidimensional X-Space Magnetic Particle Imaging

Patrick W. Goodwill; Steven M. Conolly

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-invariant 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.


IEEE Transactions on Medical Imaging | 2009

Narrowband Magnetic Particle Imaging

Patrick W. Goodwill; Greig C. Scott; Pascal P. Stang; Steven M. Conolly

The magnetic particle imaging (MPI) method directly images the magnetization of super-paramagnetic iron oxide (SPIO) nanoparticles, which are contrast agents commonly used in magnetic resonance imaging (MRI). MPI, as originally envisioned, requires a high-bandwidth receiver coil and preamplifier, which are difficult to optimally noise match. This paper introduces Narrowband MPI, which dramatically reduces bandwidth requirements and increases the signal-to-noise ratio for a fixed specific absorption rate. We employ a two-tone excitation (called intermodulation) that can be tailored for a high-Q, narrowband receiver coil. We then demonstrate a new MPI instrument capable of full 3-D tomographic imaging of SPIO particles by imaging acrylic and tissue phantoms.


IEEE Transactions on Medical Imaging | 2015

Magnetic Particle Imaging With Tailored Iron Oxide Nanoparticle Tracers

R. Matthew Ferguson; Amit P. Khandhar; Scott J. Kemp; Hamed Arami; Emine Ulku Saritas; Laura R. Croft; Justin J. Konkle; Patrick W. Goodwill; Aleksi Halkola; Jürgen Rahmer; Jörn Borgert; Steven M. Conolly

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.


IEEE Transactions on Medical Imaging | 2012

Projection X-Space Magnetic Particle Imaging

Patrick W. Goodwill; Justin J. Konkle; Bo Zheng; Emine Ulku Saritas; Steven M. Conolly

Projection magnetic particle imaging (MPI) can improve imaging speed by over 100-fold over traditional 3-D MPI. In this work, we derive the 2-D x-space signal equation, 2-D image equation, and introduce the concept of signal fading and resolution loss for a projection MPI imager. We then describe the design and construction of an x-space projection MPI scanner with a field gradient of 2.35 T/m across a 10 cm magnet free bore. The system has an expected resolution of 3.5 × 8.0 mm using Resovist tracer, and an experimental resolution of 3.8 × 8.4 mm resolution. The system images 2.5 cm × 5.0 cm partial field-of views (FOVs) at 10 frames/s, and acquires a full field-of-view of 10 cm × 5.0 cm in 4 s. We conclude by imaging a resolution phantom, a complex “Cal” phantom, mice injected with Resovist tracer, and experimentally confirm the theoretically predicted x-space spatial resolution.


Nature Nanotechnology | 2014

Biogenic Gas Nanostructures as Ultrasonic Molecular Reporters

Mikhail G. Shapiro; Patrick W. Goodwill; Arkosnato Neogy; Melissa Yin; F. Stuart Foster; David V. Schaffer; Steven M. Conolly

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.


Theranostics | 2016

Quantitative Magnetic Particle Imaging Monitors the Transplantation, Biodistribution, and Clearance of Stem Cells In Vivo

Bo Zheng; Marc von See; Elaine Yu; Beliz Gunel; Kuan Lu; Tandis Vazin; David V. Schaffer; Patrick W. Goodwill; Steven M. Conolly

Stem cell therapies have enormous potential for treating many debilitating diseases, including heart failure, stroke and traumatic brain injury. For maximal efficacy, these therapies require targeted cell delivery to specific tissues followed by successful cell engraftment. However, targeted delivery remains an open challenge. As one example, it is common for intravenous deliveries of mesenchymal stem cells (MSCs) to become entrapped in lung microvasculature instead of the target tissue. Hence, a robust, quantitative imaging method would be essential for developing efficacious cell therapies. Here we show that Magnetic Particle Imaging (MPI), a novel technique that directly images iron-oxide nanoparticle-tagged cells, can longitudinally monitor and quantify MSC administration in vivo. MPI offers near-ideal image contrast, depth penetration, and robustness; these properties make MPI both ultra-sensitive and linearly quantitative. Here, we imaged, for the first time, the dynamic trafficking of intravenous MSC administrations using MPI. Our results indicate that labeled MSC injections are immediately entrapped in lung tissue and then clear to the liver within one day, whereas standard iron oxide particle (Resovist) injections are immediately taken up by liver and spleen. Longitudinal MPI-CT imaging also indicated a clearance half-life of MSC iron oxide labels in the liver at 4.6 days. Finally, our ex vivo MPI biodistribution measurements of iron in liver, spleen, heart, and lungs after injection showed excellent agreement (R2 = 0.943) with measurements from induction coupled plasma spectrometry. These results demonstrate that MPI offers strong utility for noninvasively imaging and quantifying the systemic distribution of cell therapies and other therapeutic agents.


Scientific Reports | 2015

Magnetic Particle Imaging tracks the long-term fate of in vivo neural cell implants with high image contrast.

Bo Zheng; Tandis Vazin; Patrick W. Goodwill; Anthony Conway; Aradhana Verma; Emine Ulku Saritas; David V. Schaffer; Steven M. Conolly

We demonstrate that Magnetic Particle Imaging (MPI) enables monitoring of cellular grafts with high contrast, sensitivity, and quantitativeness. MPI directly detects the intense magnetization of iron-oxide tracers using low-frequency magnetic fields. MPI is safe, noninvasive and offers superb sensitivity, with great promise for clinical translation and quantitative single-cell tracking. Here we report the first MPI cell tracking study, showing 200-cell detection in vitro and in vivo monitoring of human neural graft clearance over 87 days in rat brain.


Applied Physics Letters | 2011

Ferrohydrodynamic relaxometry for magnetic particle imaging

Patrick W. Goodwill; A. Tamrazian; Laura R. Croft; Changgui Lu; E. M. Johnson; R. Pidaparthi; R. M. Ferguson; Amit P. Khandhar; Steven M. Conolly

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.


IEEE Transactions on Medical Imaging | 2013

Magnetostimulation Limits in Magnetic Particle Imaging

Emine Ulku Saritas; Patrick W. Goodwill; George Zhang; Steven M. Conolly

For magnetic particle imaging (MPI), specific absorption rate (SAR) and more critically magnetostimulation (i.e., dB/dt) safety limits will determine the optimal scan parameters, such as the drive field strength and frequency. These parameters will impact the scanning speed, field-of-view (FOV) and signal-to-noise ratio in MPI. Understanding the potential safety hazards of the drive field is critical for scaling MPI for human use. In this work, we demonstrate that magnetostimulation is the primary magnetic safety consideration in MPI, and we describe the first human-subject magnetostimulation threshold experiments for MPI using homogeneous coils. Our experiments, performed on the arm and leg, indicate that magnetostimulation thresholds monotonically decrease with increasing frequency. Additionally, we show for the first time that a strong inverse correlation exists between the threshold and the body part size. The chronaxie time, on the other hand, did not vary with body part size. We conclude with an estimation of the magnetostimulation thresholds for a full-body MPI scanner: a mean asymptotic threshold of 14.3 mT-pp (peak-to-peak) with a mean chronaxie time of 289 μs, which correspond to a magnetostimulation threshold of about 15 mT-pp for frequencies between 25 and 50 kHz. These findings will have a great impact on the optimization of MPI parameters, especially in determining the number of partial FOVs required to cover a region of interest.

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Bo Zheng

University of California

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Daniel Hensley

University of California

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Kuan Lu

University of California

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Laura R. Croft

University of California

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Zhi Wei Tay

University of California

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