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Abstract #2037

Validation of MRI-based axon radius index estimation using large-scale light microscopy and deep learning

Mohammad Ashtarayeh1, Laurin Mordhorst1, Maria Morozova2,3, Tobias Streubel1,2, Jan Malte Oeschger1, Joao Periquito4, Andreas Pohlmann4, Henriette Rusch3, Carsten Jäger2, Thoralf Niendorf4, Nikolaus Weiskopf2,5, Markus Morawski2,3, and Siawoosh Mohammadi1,2
1Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 2Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, 4Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany, 5Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany

We used a new method for validation of MRI-based axon radius index (ARI) mapping using large-scale light microscopy (lsLM) that provides a good representation of the fraction of large axons - the main contributors to the MRI-based ARI. The proposed method captures 100-1000 times more axons than current standard small field of view microscopy. We showed that the one-to-one correspondence between MRI-based ARI and lsLM-based effective axon radius is superior to the current standard method.

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