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Abstract Magnetic particle imaging (MPI) is a tracer-based tomographic imaging technique utilized in applications such as lung perfusion imaging, cancer diagnosis, stem cell tracking, etc. The goal of translating MPI to clinical use has prompted studies on further improving the spatial-temporal resolutions of MPI through various methods, including image reconstruction algorithm, scanning trajectory design, magnetic field profile design, and tracer design. Iron oxide magnetic nanoparticles (MNPs) are favored for MPI and magnetic resonance imaging (MRI) over other materials due to their high biocompatibility, low cost, and ease of preparation and surface modification. For core–shell MNPs, the tracers’ magnetic core size and non-magnetic coating layer characteristics can significantly affect MPI signals through dynamic magnetization relaxations. Most works to date have assumed an ensemble of MNP tracers with identical sizes, ignoring that artificially synthesized MNPs typically follow a log-normal size distribution, which can deviate theoretical results from experimental data. In this work, we first characterize the size distributions of four commercially available iron oxide MNP products and then model the collective magnetic responses of these MNPs for MPI applications. For an ensemble of MNP tracers with size standard deviations ofσ, we applied a stochastic Langevin model to study the effect of size distribution on MPI imaging performance. Under an alternating magnetic field (AMF), i.e., the excitation field in MPI, we collected the time domain dynamic magnetizations (M-t curves), magnetization-field hysteresis loops (M-H curves), point-spread functions (PSFs), and higher harmonics from these MNP tracers. The intrinsic MPI spatial resolution, which is related to the full width at half maximum (FWHM) of the PSF profile, along with the higher harmonics, serve as metrics to provide insights into how the size distribution of MNP tracers affects MPI performance.
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Advances in Vascular Diagnostics using Magnetic Particle Imaging (MPI) for Blood Circulation Assessment
Abstract Rapid and accurate assessment of conditions characterized by altered blood flow, cardiac blood pooling, or internal bleeding is crucial for diagnosing and treating various clinical conditions. While widely used imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound offer unique diagnostic advantages, they fall short for specific indications due to limited penetration depth and prolonged acquisition times. Magnetic particle imaging (MPI), an emerging tracer‐based technique, holds promise for blood circulation assessments, potentially overcoming existing limitations with reduction in background signals and high temporal and spatial resolution, below the millimeter scale. Successful imaging of blood pooling and impaired flow necessitates tracers with diverse circulation half‐lives optimized for MPI signal generation. Recent MPI tracers show potential in imaging cardiovascular complications, vascular perforations, ischemia, and stroke. The impressive temporal resolution and penetration depth also position MPI as an excellent modality for real‐time vessel perfusion imaging via functional MPI (fMPI). This review summarizes advancements in optimized MPI tracers for imaging blood circulation and analyzes the current state of pre‐clinical applications. This work discusses perspectives on standardization required to transition MPI from a research endeavor to clinical implementation and explore additional clinical indications that may benefit from the unique capabilities of MPI.
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- Award ID(s):
- 2236414
- PAR ID:
- 10520032
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Advanced Healthcare Materials
- ISSN:
- 2192-2640
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/adhm.202400612
