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Abstract #4843

Discovery of two novel deep gray matter brain iron networks through an Independent Component Analysis of Quantitative Susceptibility Maps

Jack A Reeves1, Niels Bergsland1,2, Dejan Jakimovski1, Fahad Salman1, Juliane Damm1, Nicklas Meineke1, Michael G Dwyer1,3, Robert Zivadinov1,3, and Ferdinand Schweser1,3
1Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, 2MR Research Laboratory, IRCCS, Don Gnocchi Foundation ONLUS, Milan, Italy, 3Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States


Magnetic resonance imaging (MRI) studies have shown age and neurological disease affect iron concentrations in the deep gray matter (DGM). However, it is unknown whether iron accumulation occurs independently across DGM regions or in inter-regional patterns, i.e. “iron networks”. Here, we identified two highly reproducible, inter-regional DGM iron networks by applying independent component analysis (ICA) to quantitative susceptibility maps (QSM) from healthy volunteers. Areas of network overlap had relatively high iron concentrations and each network was related to separate environmental variables, indicating they have independent mechanisms of iron change. Our results advance the understanding of brain iron physiology.

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