1 research outputs found
Differentiating Between Cancer and Inflammation: A Metabolic-Based Method for Functional Computed Tomography Imaging
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 [<sup>18</sup>F]ÂFDG-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