The DOI matches its Crossref record; 265 of the 265 references it cites were found in a registry or an index.
Magnetic Nanoparticles as MRI Contrast Agents
Open accessAbstract
Iron oxide nanoparticles (IONPs) have emerged as a promising alternative to conventional contrast agents (CAs) for magnetic resonance imaging (MRI). They have been extensively investigated as CAs due to their high biocompatibility and excellent magnetic properties. Furthermore, the ease of functionalization of their surfaces with different types of ligands (antibodies, peptides, sugars, etc.) opens up the possibility of carrying out molecular MRI. Thus, IONPs functionalized with epithelial growth factor receptor antibodies, short peptides, like RGD, or aptamers, among others, have been proposed for the diagnosis of various types of cancer, including breast, stomach, colon, kidney, liver or brain cancer. In addition to cancer diagnosis, different types of IONPs have been developed for other applications, such as the detection of brain inflammation or the early diagnosis of thrombosis. This review addresses key aspects in the development of IONPs for MRI applications, namely, synthesis of the inorganic core, functionalization processes to make IONPs biocompatible and also to target them to specific tissues or cells, and finally in vivo studies in animal models, with special emphasis on tumor models.
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1 retracted
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Cited by
Yue, N.-N., Xu, H.-M., Xu, J., Zhu, M.-Z., Zhang, Y., Tian, C.-M., Nie, Y.-Q., Yao, J., Liang, Y.-J., Li, D.-F., et al. (2023) · International Journal of Nanomedicine · doi:10.2147/ijn.s413141 · Cited by 46
Metadata
- Authors
- Avasthi, A., Caro, C., Pozo-Torres, E., Leal, M. P., & García-Martín, M. L.
- Venue
- Topics in Current Chemistry
- Published
- 2020-05-07
- Volume
- 378
- Issue
- 3
- Pages
- 40-40
- ISSN
- 2364-8961 (ISSN-L)
- 2365-0869
- OpenAlex
- W3023796310
- Cited by
- 253
- References
- 265
- FWCI
- 9.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.