Abstract
One of the main limitations of the highly used cancer imaging technique, PET-CT, is its inability to distinguish between cancerous lesions and post treatment inflammatory conditions. The reason for this lack of specificity is that [18F]FDG-PET is based on increased glucose metabolic activity, which characterizes both cancerous tissues and inflammatory cells. To overcome this limitation, we developed a nanoparticle-based approach, utilizing glucose-functionalized gold nanoparticles (GF-GNPs) as a metabolically targeted CT contrast agent. Our approach demonstrates specific tumor targeting and has successfully distinguished between cancer and inflammatory processes in a combined tumor-inflammation mouse model, due to dissimilarities in angiogenesis occurring under different pathologic conditions. This study provides a set of capabilities in cancer detection, staging and follow-up, and can be applicable to a wide range of cancers that exhibit high metabolic activity.
Original language | English |
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Pages (from-to) | 3469-3477 |
Number of pages | 9 |
Journal | ACS Nano |
Volume | 10 |
Issue number | 3 |
DOIs | |
State | Published - 22 Mar 2016 |
Bibliographical note
Funding Information:This work was partially supported by the Research and Development Chief Scientist Kamin grant (49544), by the Israel Cancer Research Fund (ICRF), by the Israel Science Foundation grant (749/14), and by the doctoral scholarship for applicable and scientific engineering research, granted to Tamar Dreifuss and Oshra Betzer by the Ministry of Science, Technology & Space, Israel.
Publisher Copyright:
© 2016 American Chemical Society.
Keywords
- CT
- FDG-PET
- cancer
- gold nanoparticles
- metabolic-based imaging