How Size and Composition of Cobalt Doped Iron Oxide Nanoparticle Tracers Enhance Magnetic Particle Imaging Performance

Magnetic particle imaging (MPI) is a promising diagnostic imaging technique that enables direct and precise tracking of magnetic tracers. The optimization of iron oxide-based nanoparticle tracers is of utmost importance in MPI for attaining high sensitivity and good spatial resolution. Currently, the state-of-the-art MPI tracers utilize undoped, magnetite iron oxide nanoparticles (NPs). In this study, we present the first comprehensive analysis of how doping with cobalt influences the MPI performance of iron oxide-based NPs. We observed a 1.4–1.7-fold and 1.2–1.3-fold enhancement in the saturation magnetization (Msat) value by doping Co into 9 and 20 nm magnetite NPs, respectively. The amplification in the maximum point spread function (PSF) signal showed a significant increase, ranging from 1.6 to 1.8 times higher for both 9 and 20 nm NPs when subjected to doping with 12 at. % Co. Importantly, in NPs with a higher degree of doping of 22 at. % Co, the augmentation in maximum PSF signal was even more remarkable, achieving a 2-fold increase when compared to undoped magnetite NPs. By introducing Co doping, we show that tracers can be created that have excellent MPI performance while achieving a smaller size, making them highly suitable for a wide range of in vivo applications.

Authors

Institutions

Publication Details

Journal
Chemistry of Materials
Published
2024-09-10
DOI
https://doi.org/10.1021/acs.chemmater.4c01484
Citations
6
Primary Topic
Characterization and Applications of Magnetic Nanoparticles
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How Size and Composition of Cobalt Doped Iron Oxide Nanoparticle Tracers Enhance Magnetic Particle Imaging Performance

Soshan Cheong, Lucy Gloag, Ashkan Abdibastami, Saeed Shanehsazzadeh et al.
6 citations
Chemistry of Materials
Characterization and Applications of Magnetic Nanoparticles
1.11
article

How Size and Composition of Cobalt Doped Iron Oxide Nanoparticle Tracers Enhance Magnetic Particle Imaging Performance

Soshan Cheong, Lucy Gloag, Ashkan Abdibastami, Saeed Shanehsazzadeh, Guy N. L. Jameson, J. Justin Gooding, André Bongers, Richard David Tilley, Nicholas M. Bedford, Scott A. Sulway, Haira G. Hackbarth, Hong Thien Kim Duong, Jhair Peña Prada
article en
6 citations

Abstract

Magnetic particle imaging (MPI) is a promising diagnostic imaging technique that enables direct and precise tracking of magnetic tracers. The optimization of iron oxide-based nanoparticle tracers is of utmost importance in MPI for attaining high sensitivity and good spatial resolution. Currently, the state-of-the-art MPI tracers utilize undoped, magnetite iron oxide nanoparticles (NPs). In this study, we present the first comprehensive analysis of how doping with cobalt influences the MPI performance of iron oxide-based NPs. We observed a 1.4–1.7-fold and 1.2–1.3-fold enhancement in the saturation magnetization (Msat) value by doping Co into 9 and 20 nm magnetite NPs, respectively. The amplification in the maximum point spread function (PSF) signal showed a significant increase, ranging from 1.6 to 1.8 times higher for both 9 and 20 nm NPs when subjected to doping with 12 at. % Co. Importantly, in NPs with a higher degree of doping of 22 at. % Co, the augmentation in maximum PSF signal was even more remarkable, achieving a 2-fold increase when compared to undoped magnetite NPs. By introducing Co doping, we show that tracers can be created that have excellent MPI performance while achieving a smaller size, making them highly suitable for a wide range of in vivo applications.

Chemistry of Materials
Australian National University (AU), The University of Melbourne (AU), UNSW Sydney (AU), ARC Centre of Excellence in Advanced Molecular Imaging (AU)
Australian Research Council
Openalex Percentile: Top 24%
Characterization and Applications of Magnetic Nanoparticles
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.