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Differentiating Between Cancer and Inflammation: A Metabolic-Based Method for Functional Computed Tomography Imaging.

ACS nano (2016-02-18)
Menachem Motiei, Tamar Dreifuss, Oshra Betzer, Hana Panet, Aron Popovtzer, Jordan Santana, Galith Abourbeh, Eyal Mishani, Rachela Popovtzer
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 [(18)F]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.

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N-Hydroxysulfosuccinimide sodium salt, ≥98% (HPLC)