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Abstract #0772

Novel biological Gadolinium contrast agents for MRI developed using artificial intelligence

Nir Dayan1, Nicolas Scalzitti1,2, Iliya Miralavy2, Wolfgang Banzhaf2, and Assaf Gilad1,3
1Chemical engineering and materials science, Michigan State University, East Lansing, MI, United States, 2Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, United States, 3Department of Radiology, Michigan State University, East Lansing, MI, United States

Synopsis

Keywords: Contrast Agents, Molecular Imaging

Motivation: MRI contrast agents based on Gadolinium binding peptides with high selectivity for specific targets can increase imaging precision and minimize potential toxicity.

Goal(s): Develop novel Gadolinium binding motifs that can be used for molecular imaging.

Approach: Peptides were incubated with Gadolinium and MRI scanned to quantify their MRI contrast. The results were used as a dataset for POET (an AI algorithm), which iteratively optimized the peptide sequences for Gadolinium-binding.

Results: After two cycles of POET, we found 25 peptides with higher contrast than the initial dataset. The best peptide had 24.3% improvement. The peptides are entirely different than peptides in the initial dataset.

Impact: The Gadolinium binding motifs found in this research will be used to develop biological MRI contrast agents that will allow safer and more effective imaging procedures.

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