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Abstract #2619

Diffusion metrics correlate with the relaxometric constant Dr of the χ-separation model

Elena Grosso1, Antonio Ricciardi2, Marios C. Yannakas2, Ferran Prados2,3,4, Baris Kanber2,3, Francesco Grussu2,5, Marco Battiston2, Rebecca S. Samson2, Egidio D'Angelo1,6, Carmen Tur2,7, Fulvia Palesi1,6, and Claudia A.M. Gandini Wheeler-Kingshott1,2,6
1Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, 2NMR Research unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, United Kingdom, 3Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, United Kingdom, 4E-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain, 5Radiomics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, 6Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy, 7Neurology-Neuroimmunology Department Multiple Sclerosis Centre of Catalonia (Cemcat), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain

Synopsis

Keywords: Susceptibility/QSM, Microstructure, Modelling, chi-separation method

Motivation: χ-separation method relies on assuming a certain relaxometric constant (Dr) calculated as the mean of a group of healthy subjects. Recently, we demonstrated that it is subject-specific.

Goal(s): The goal of this study was to evaluate the correlation between Dr and microstructural metrics obtained from diffusion tensor and diffusion kurtosis imaging (DTI and DKI).

Approach: We regressed between Dr against DTI and DKI diffusion metrics in a cohort of healthy controls.

Results: Results showed a positive correlation with fractional anisotropy and axial diffusivity, and a negative correlation with mean and radial kurtosis.

Impact: Understanding how the relaxometric constant of the χ-separation method (Dr) depends on microstructural diffusion metrics will define its personalization. This, in turn, will impact on how we assess the presence of different magnetic susceptibility sources in the brain.

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Keywords