The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Toward an Image-Guided Microbeam Radiation Therapy Using Gadolinium-Based Nanoparticles
Abstract
Ultrasmall gadolinium-based nanoparticles (GBNs) induce both a positive contrast for magnetic resonance imaging and a radiosentizing effect. The exploitation of these characteristics leads to a greater increase in lifespan of rats bearing brain tumors since the radiosensitizing effect of GBNs can be activated by X-ray microbeams when the gadolinium content is, at the same time, sufficiently high in the tumor and low in the surrounding healthy tissue. GBNs exhibit therefore an interesting potential for image-guided radiotherapy.
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Cites
Cancer nanotechnology: opportunities and challenges
Ferrari, M. (2005) · Nature Reviews Cancer · doi:10.1038/nrc1566 · Cited by 4,558
Renal clearance of quantum dots
Soo Choi, H., Liu, W., Misra, P., Tanaka, E., Zimmer, J. P., Itty Ipe, B., Bawendi, M. G., & Frangioni, J. V. (2007) · Nature Biotechnology · doi:10.1038/nbt1340 · Cited by 4,476
Tumorigenesis and the angiogenic switch
Bergers, G., & Benjamin, L. E. (2003) · Nature reviews. Cancer · doi:10.1038/nrc1093 · Cited by 3,559
Exploiting the enhanced permeability and retention effect for tumor targeting
Iyer, A. K., Khaled, G., Fang, J., & Maeda, H. (2006) · Drug Discovery Today · doi:10.1016/j.drudis.2006.07.005 · Cited by 1,846
Multimodality Imaging Probes: Design and Challenges
Louie, A. (2010) · Chemical Reviews · doi:10.1021/cr9003538 · Cited by 1,044
Design considerations for tumour-targeted nanoparticles
Choi, H. S., Liu, W., Liu, F., Nasr, K., Misra, P., Bawendi, M. G., & Frangioni, J. V. (2010) · Nature Nanotechnology · doi:10.1038/nnano.2009.314 · Cited by 754
Cited by
Emerging Nanotechnology and Advanced Materials for Cancer Radiation Therapy
Song, G., Cheng, L., Chao, Y., Yang, K., & Liu, Z. (2017) · Advanced Materials · doi:10.1002/adma.201700996 · Cited by 771
Xiao, Q., Zheng, X., Bu, W., Ge, W., Zhang, S., Chen, F., Xing, H., Ren, Q., Fan, W., Zhao, K., et al. (2013) · Journal of the American Chemical Society · doi:10.1021/ja404985w · Cited by 554
Engineering of inorganic nanoparticles as magnetic resonance imaging contrast agents
Ni, D., Bu, W., Ehlerding, E. B., Cai, W., & Shi, J. (2017) · Chemical Society Reviews · doi:10.1039/c7cs00316a · Cited by 484
Nanoparticles for Radiation Therapy Enhancement: the Key Parameters
Retif, P., Pinel, S., Toussaint, M., Frochot, C., Chouikrat, R., Bastogne, T., & Barberi-Heyob, M. (2015) · Theranostics · doi:10.7150/thno.11642 · Cited by 385
Verry, C., Dufort, S., Villa, J., Gavard, M., Iriart, C., Grand, S., Charles, J., Chovelon, B., Cracowski, J.-L., Quesada, J.-L., et al. (2021) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2021.04.021 · Cited by 173
Self-citation
Metadata
- Authors
- Le Duc, G., Miladi, I., Alric, C., Mowat, P., Bräuer-Krisch, E., Bouchet, A., Khalil, E., Billotey, C., Janier, M., Lux, F., Epicier, T., Perriat, P., Roux, S., & Tillement, O.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-11-09
- Volume
- 5
- Issue
- 12
- Pages
- 9566-9574
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2328758956
- Cited by
- 248
- References
- 6
- FWCI
- 12.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- Le Duc, G., Miladi, I., Alric, C., Mowat, P., Bräuer-Krisch, E., Bouchet, A., Khalil, E., Billotey, C., Janier, M., Lux, F., Epicier, T., Perriat, P., Roux, S., & Tillement, O. (2011). Toward an Image-Guided Microbeam Radiation Therapy Using Gadolinium-Based Nanoparticles. ACS Nano. https://doi.org/10.1021/nn202797h
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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.
