Single- and Multi-Arm Gadolinium MRI Contrast Agents for Targeted Imaging of Glioblastoma

Abstract

Background: Position of gadolinium atom(s) plays a key role in contrast enhancement of gadolinium-based contrast agents. To gain a better understanding of effects of distance of gadolinium in relation to the nanoconjugate platform, we designed and synthesized single-and multi-arm ("star") gadolinium conjugates equipped with antibody and peptides for targeting. The contrast agents were studied for their tumor imaging performance in a glioma mouse model. Materials and Methods: Antibody- and peptide-targeted nano contrast agents (NCAs) were synthesized using polymalic acid platforms of different sizes. Gadolinium-DOTA and intermediates were attached as amides and targeting agents such as antibodies and peptides as thioethers. For in vivo experiments, we used human U87MG xenografts as glioma models. Magnetic resonance imaging (MRI) was performed on a Bruker BioSpec 94/20USR 9.4 T small-animal scanner. Delivery of contrast agents across the blood-brain barrier was studied by fluorescent microscopy. Results: All contrast agents accumulated into tumor and showed composition-dependent imaging performance. Peptide-targeted mini-NCAs had hydrodynamic diameters in the range 5.2-9.4 nm and antibody-targeted NCAs had diameters in the range 15.8-20.5 nm. Zeta potentials were in the range of -5.4--8.2 mV and -4.6--8.8 mV, respectively. NCAs showed superior relaxivities compared to MultiHance at 9.4 T. The signal enhancement indicated maximum accumulation in tumor 30-60 minutes after intravenous injection of the mouse tail vein. Only targeted NCAs were retained in tumor for up to 3 hours and displayed contrast enhancement. Conclusion: The novel targeted NCAs with star-PEG features displayed improved relaxivity and greater contrast compared with commercial MultiHance contrast agent. The enhancement by mini-NCAs showed clearance of tumor contrast after 3 hours providing a suitable time window for tumor diagnosis in clinics. The technology provides a great tool with the promise of differential MRI diagnosis of brain tumors.