Loading…

First Superferromagnetic Remanence Characterization and Scan Optimization for Super-Resolution Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a sensitive, high-contrast tracer modality that images superparamagnetic iron oxide nanoparticles, enabling radiation-free theranostic imaging. MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10× res...

Full description

Saved in:
Bibliographic Details
Published in:Nano letters 2023-03, Vol.23 (5), p.1717-1725
Main Authors: Fung, K. L. Barry, Colson, Caylin, Bryan, Jacob, Saayujya, Chinmoy, Mokkarala-Lopez, Javier, Hartley, Allison, Yousuf, Khadija, Kuo, Renesmee, Lu, Yao, Fellows, Benjamin D., Chandrasekharan, Prashant, Conolly, Steven M.
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Magnetic particle imaging (MPI) is a sensitive, high-contrast tracer modality that images superparamagnetic iron oxide nanoparticles, enabling radiation-free theranostic imaging. MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10× resolution and signal improvements with dramatically sharper M–H curves. Experiments show a dependence on interparticle interactions, conforming to literature definitions of superferromagnetism. We thus call our tracers superferromagnetic iron oxide nanoparticles (SFMIOs). While SFMIOs provide excellent signal and resolution, they exhibit hysteresis with non-negligible remanence and coercivity. We provide the first quantitative measurements of SFMIO remanence decay and reformation using a novel multiecho pulse sequence. We characterize MPI scanning with remanence decay and coercivity and describe an SNR-optimized pulse sequence for SFMIOs under human electromagnetic safety limitations. The resolution from SFMIOs could enable clinical MPI with 10× reduced scanner selection fields, reducing hardware costs by up to 100×.
ISSN:1530-6984
1530-6992
DOI:10.1021/acs.nanolett.2c04404