4.8 Article

In vivo NIRF and MR dual-modality imaging using glycol chitosan nanoparticles

Journal

JOURNAL OF CONTROLLED RELEASE
Volume 163, Issue 2, Pages 249-255

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jconrel.2012.07.038

Keywords

Cancer; MRI; NIRF imaging; Chitosan nanoparticle; Dual-modality imaging

Funding

  1. KIST-Purdue GRL (Global Research Laboratory) Collaboration, Molecular Imaging and Nanomedicine for Theragnosis using NanoBioMaterials [202979]
  2. Christopher Columbus Foundation
  3. Indiana Clinical and Translational Sciences Institute from the National Institutes of Health, National Center for Research Resources, Clinical and Translational Sciences Award
  4. National Research Foundation of Korea [2007-00093] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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One difficulty of diagnosing and treating cancer is that it is very challenging to detect cancers in the early stages before metastasis occurs. A variety of imaging modalities needs to be used from non-invasive, moderate resolution modalities, such as magnetic resonance imaging (MRI) to very high-resolution (e.g. fluorescence) imaging that can help guide surgeons during a surgical operation. While MRI can have relatively high resolution and deep penetration to visualize soft tissues, low sensitivity of MRI frequently requires tumor imaging agents to enhance the MRI contrast at the tumor site. At the other end of the resolution spectrum, near infrared fluorescence (NIRF) imaging has very high sensitivity but frequently cannot be utilized for initial human in vivo imaging due to its very limited penetration depth. To combine the advantages of each imaging modality we have constructed MRI and NIRF dual-modality nanoparticles using glycol chitosan, Cy5.5, and superparamagnetic iron oxide nanoparticles (SPIOs). We have demonstrated these advantages for dual-modality, in vivo tumor imaging in mice. Our studies suggest the potential use of NIRF and MR dual modality imaging for human cancer diagnosis. (c) 2012 Elsevier B.V. All rights reserved.

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