View : 16 Download: 0

A Multifunctional Nanoplatform for Imaging, Radiotherapy, and the Prediction of Therapeutic Response

Title
A Multifunctional Nanoplatform for Imaging, Radiotherapy, and the Prediction of Therapeutic Response
Authors
McQuade, CaseyAl Zaki, AjlanDesai, YaanikVido, MichaelSakhuja, TimothyCheng, ZhiliangHickey, Robert J.Joh, DanielPark, So-JungKao, GaryDorsey, Jay F.Tsourkas, Andrew
Ewha Authors
박소정
SCOPUS Author ID
박소정scopus
Issue Date
2015
Journal Title
SMALL
ISSN
1613-6810JCR Link1613-6829JCR Link
Citation
vol. 11, no. 7, pp. 834 - 843
Publisher
WILEY-V C H VERLAG GMBH
Indexed
SCI; SCIE; SCOPUS WOS
Abstract
Gold nanoparticles have garnered interest as both radiosensitzers and computed tomography (CT) contrast agents. However, the extremely high concentrations of gold required to generate CT contrast is far beyond that needed for meaningful radiosensitization, which limits their use as combined therapeutic-diagnostic (theranostic) agents. To establish a theranostic nanoplatform with well-aligned radiotherapeutic and diagnostic properties for better integration into standard radiation therapy practice, a gold-and superparamagnetic iron oxide nanoparticle (SPION)-loaded micelle (GSM) is developed. Intravenous injection of GSMs into tumor-bearing mice led to selective tumoral accumulation, enabling magnetic resonance (MR) imaging of tumor margins. Subsequent irradiation leads to a 90-day survival of 71% in GSM-treated mice, compared with 25% for irradiation-only mice. Furthermore, measurements of the GSM-enhanced MR contrast are highly predictive of tumor response. Therefore, GSMs may not only guide and enhance the efficacy of radiation therapy, but may allow patients to be managed more effectively.
DOI
10.1002/smll.201401927
Appears in Collections:
자연과학대학 > 화학·나노과학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE