Periodic table screening for enhanced positive contrast in MRI and in vivo uptake in glioblastoma

09 November 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The quest for nanomaterial-based imaging probes that can provide positive contrast in MRI is fueled by the necessity of developing novel diagnostic applications with potential for clinical translation that current gold standard probes cannot provide. Although interest in nanomaterials for positive contrast has increased in recent years, their study is less developed than that of traditional negative contrast probes in MRI. In our search for new magnetic materials with enhanced features as positive contrast probes for MRI, we decided to explore the chemical space to comprehensively analyze the effects of different metals on the performance of iron oxide nanomaterials already able to provide positive contrast in MRI. To this end, we synthesized 30 different iron-oxide-based nanomaterials. Thorough characterization was performed, including multivariate analysis, to study the effect of different variables on their relaxometric properties. Based on these results, we identified the best combination of metals for in vivo imaging and tested them in different experiments. First, we tested its performance on magnetic resonance angiography using a concentration ten times lower than that clinically approved for Gd. Finally, we studied the capability of these nanomaterials to cross the affected blood-brain barrier in a glioblastoma model. The results showed that the selected nanomaterials provided excellent positive contrast at large magnetic field and were able to accumulate at the tumor site, highlighting the affected tissue.

Keywords

positive contrast MRI
metal doping
molecular imaging
glioblastoma

Supplementary materials

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Supporting information
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Additional information including methods, XRD, VSM, TGA and FTIR for all the nanoparticles. EDS for GaZn-IONP and additional images for the in vivo MRI experiments in glioblastoma models
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