Multivoid Magnetic Nanoparticles as High-Performance Magnetic Particle Imaging Tracers for Precise Glioma Detection

Precise glioma detection is a critical challenge in the clinic. Magnetic particle imaging (MPI) is an emerging, highly sensitive medical imaging technique that has the potential to accurately detect glioma at the molecular and cellular levels. Magnetic nanoparticles (MNPs) provide an effective approach for targeted imaging to specific regions, and the morphology of MNPs plays a vital role in determining their MPI performance. MNPs with various shapes have been developed to pursue sensitive MPI, while the effect of the multivoid structure on MPI tracers is still unrevealed. Herein, we systematically investigate the impact of multivoid, yolk-shell, and completely hollow structures on the MPI signal. We identify that an increased number of magnetic cores per unit volume, decreased coercivity, and reduced full width at half-maximum of the magnetization derivative caused by the multivoid structure are the key factors that endow tracers with high MPI sensitivity. Moreover, further Arginine-Glycine-Aspartic Acid peptide modification ensures that the multivoid nanotracer exhibits high affinity and targeting to tumor cells and tissues, providing an obvious MPI signal to achieve precise glioma detection. This work enables a fundamental understanding of the effect of the multivoid structure on the MPI signal, lending guidance for designing high-performance MPI tracers for biomedical applications and promoting precise disease diagnosis.

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Publication Details

Journal
Bioconjugate Chemistry
Published
2025-11-24
DOI
https://doi.org/10.1021/acs.bioconjchem.5c00527
Citations
10
Primary Topic
Characterization and Applications of Magnetic Nanoparticles
Type
article
Field-Weighted Citation Impact
6.74
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article

Multivoid Magnetic Nanoparticles as High-Performance Magnetic Particle Imaging Tracers for Precise Glioma Detection

Zhenqi Jiang, Xue Yang, Zhenghuan Zhao, Wenjia Zhang et al.
10 citations
Bioconjugate Chemistry
Characterization and Applications of Magnetic Nanoparticles
6.74
article

Multivoid Magnetic Nanoparticles as High-Performance Magnetic Particle Imaging Tracers for Precise Glioma Detection

Zhenqi Jiang, Xue Yang, Zhenghuan Zhao, Wenjia Zhang, Qian Liang, Jie Tian, Jie Zeng, Yang Du
article en
10 citations

Abstract

Precise glioma detection is a critical challenge in the clinic. Magnetic particle imaging (MPI) is an emerging, highly sensitive medical imaging technique that has the potential to accurately detect glioma at the molecular and cellular levels. Magnetic nanoparticles (MNPs) provide an effective approach for targeted imaging to specific regions, and the morphology of MNPs plays a vital role in determining their MPI performance. MNPs with various shapes have been developed to pursue sensitive MPI, while the effect of the multivoid structure on MPI tracers is still unrevealed. Herein, we systematically investigate the impact of multivoid, yolk-shell, and completely hollow structures on the MPI signal. We identify that an increased number of magnetic cores per unit volume, decreased coercivity, and reduced full width at half-maximum of the magnetization derivative caused by the multivoid structure are the key factors that endow tracers with high MPI sensitivity. Moreover, further Arginine-Glycine-Aspartic Acid peptide modification ensures that the multivoid nanotracer exhibits high affinity and targeting to tumor cells and tissues, providing an obvious MPI signal to achieve precise glioma detection. This work enables a fundamental understanding of the effect of the multivoid structure on the MPI signal, lending guidance for designing high-performance MPI tracers for biomedical applications and promoting precise disease diagnosis.

Bioconjugate ChemistryVol. 37(1)
Beijing Institute of Technology (CN), Peking University (CN), Society of Nuclear Medicine and Molecular Imaging (US), College of Medical Sciences (NP), Affiliated Hospital of Southwest Medical University (CN), Society of Interventional Radiology (US), Shandong Institute of Automation (CN), Zhongda Hospital Southeast University (CN), Institute of Automation (CN), Department of Physics, Mathematics and Informatics (BY), Peking University People's Hospital (CN), University of Chinese Academy of Sciences (CN), Beihang University (CN), Chongqing Medical University (CN), Ministry of Industry and Information Technology (CN)
Openalex Percentile: Top 3%
Characterization and Applications of Magnetic Nanoparticles
6.74
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