Author
Listed:
- Zijian Zhou
(State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University
Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
- Rui Tian
(State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University
Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
- Zhenyu Wang
(Xiamen University)
- Zhen Yang
(Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
- Yijing Liu
(Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
- Gang Liu
(State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University)
- Ruifang Wang
(Xiamen University)
- Jinhao Gao
(State Key Laboratory of Physical Chemistry of Solid Surfaces, The Key Laboratory for Chemical Biology of Fujian Province, College of Chemistry and Chemical Engineering, Xiamen University)
- Jibin Song
(Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
- Liming Nie
(State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University)
- Xiaoyuan Chen
(Laboratory of Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)
Abstract
Clustering of magnetic nanoparticles (MNPs) is perhaps the most effective, yet intriguing strategy to enhance T2 relaxivity in magnetic resonance imaging (MRI). However, the underlying mechanism is still not fully understood and the attempts to generalize the classic outersphere theory from single particles to clusters have been found to be inadequate. Here we show that clustering of MNPs enhances local field inhomogeneity due to reduced field symmetry, which can be further elevated by artificially involving iron oxide NPs with heterogeneous geometries in terms of size and shape. The r2 values of iron oxide clusters and Landau–Lifshitz–Gilbert simulations confirmed our hypothesis, indicating that solving magnetic field inhomogeneity may become a powerful way to build correlation between magnetization and T2 relaxivity of MNPs, especially magnetic clusters. This study provides a simple yet distinct mechanism to interpret T2 relaxivity of MNPs, which is crucial to the design of high-performance MRI contrast agents.
Suggested Citation
Zijian Zhou & Rui Tian & Zhenyu Wang & Zhen Yang & Yijing Liu & Gang Liu & Ruifang Wang & Jinhao Gao & Jibin Song & Liming Nie & Xiaoyuan Chen, 2017.
"Artificial local magnetic field inhomogeneity enhances T2 relaxivity,"
Nature Communications, Nature, vol. 8(1), pages 1-10, August.
Handle:
RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15468
DOI: 10.1038/ncomms15468
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