Elias, Andrew

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  • Publication
    Chemical and Biological Strategies for Improving the Sensitivity of SPIO-Enhanced MR Imaging
    (2011-08-12) Elias, Andrew
    The prevalence of cancer has seen significant growth over the last three decades, with the American Cancer Society now reporting that one in every three Americans will be afflicted with some form of cancer in their lifetime. The debilitating effects of cancer permeate beyond obvious biological ramifications, often adversely affecting patients on emotional and financial levels as well. While significant progress has been made in diagnosing and treating cancer, advancements are still needed in detecting and treating cancers at earlier stages, where clinical outcomes will be more favorable. The field of cellular and molecular imaging has emerged as a cutting-edge technology that provides a biological toolkit capable of assessing cellular and genetic deviations at their earliest stages, offering a promising new avenue for early stage cancer diagnosis. In particular, the use of magnetic resonance imaging (MRI) contrast agents has garnered significant attention due to the functional information they can provide concomitant with the exquisite anatomical information present in MR images. One class of MRI contrast agents, superparamagnetic iron oxide (SPIO) nanoparticles, offer an especially attractive platform for tumor targeting, owing to their strong magnetic properties, high degree of biocompatibility and ease of post-synthesis functionalization. One of the only limiting factors to these nanoparticles is the relatively poor sensitivity of MRI (i.e. the concentrations of contrast agents required in MRI to elicit an observable signal). We have found that by controlling and altering surface functionalization of SPIO nanoparticles, we are able to significantly improve our ability to target tumor cells both in vitro and in murine tumor models, often overcoming the aforementioned MR sensitivity issues. It is envisioned that these tumor-targeting SPIO nanoparticles could have widespread applicability in both academic and clinical cancer studies, driving improved clinical prognoses and therapeutic assessment of the disease.