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Abstract #2405

Exploring complementarity in multi-modal imaging of cortex microstructure: a diffusion and relaxometry study

Jean-François Cabana1, Guillaume Gilbert2, Nikola Stikov3,4, Julien Cohen-Adad3, Laurent Létourneau-Guillon5,6,7, and Dang Nguyen6,8,9

1CRCHUM, Université de Montréal, Montreal, QC, Canada, 2MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada, 3NeuroPoly Lab, Ecole Polytechnique, Montreal, QC, Canada, 4Montreal Heart Institute, University of Montreal, Montreal, QC, Canada, 5CHUM Notre-Dame, Montreal, QC, Canada, 6CRCHUM, Montreal, QC, Canada, 7Université de Montréal, Montreal, QC, Canada, 8Division of Neurology, CHUM Notre-Dame, Montreal, QC, Canada, 9Department of Neuroscience, Université de Montréal, Montreal, QC, Canada

We explored the utility and complementarity of different diffusion and relaxometry metrics for cortical imaging. The following metrics were assessed for correlation: mean kurtosis (MK) from diffusion kurtosis imaging, intra-cellular volume fraction (ICVF), from the NODDI model, intra-neurite volume fraction (VINT), from the multi-compartment microscopic diffusion imaging (MCMICRO) model, R1 (=1/T1), R2* (=1/T2*) and the ratio of T1w/T2w images. Some global similarities can be seen between most cortical maps, while some features that suggest complementarity between diffusion and relaxometry maps were also observed. This study emphasizes the importance of better understanding and characterising the relationship between different MRI-derived metrics.

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