Abstract #2833

Personalized-NODDI (pNODDI) discriminates between healthy and multiple sclerosis subjects

Elena Grosso¹, Carmen Tur^2,3, Alberto Calvi², Sara Collorone², Francesco Grussu^2,4, Marco Battiston², Ferran Prados Carrasco^2,5,6, Baris Kanber^2,5, Rebecca Samson², Egidio D'Angelo^1,7, Claudia AM Gandini Wheeler-Kingshott^1,2,7, and Fulvia Palesi¹

¹Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ²NMR Research Unit, Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London (UCL), London, United Kingdom, ³Neurology-Neuroimmunology Department Multiple Sclerosis Centre of Catalonia (Cemcat), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ⁴Radiomics Group, Vall d’Hebron Institute of Oncology, Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain, ⁵Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London, London, United Kingdom, ⁶E-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain, ⁷Brain Connectivity Centre Research Unit, IRCCS Mondino Foundation, Pavia, Italy

Synopsis

Keywords: Multiple Sclerosis, Diffusion/other diffusion imaging techniques, personalised-NODDINeurite Orientation Dispersion and Density Imaging (NODDI) is a multi-compartmental model for microstructure characterization utilising diffusion-weighted MRI. Here, a recently proposed personalized-NODDI (pNODDI) modelling technique was used to assess microstructural alterations in a cohort of Multiple Sclerosis (MS) patients. Our findings showed that pNODDI metrics were sensitive to MS pathology and could discriminate between healthy controls and MS. Furthermore, pNODDI metrics of key brain regions increased the discriminative power between the two groups. Overall, pNODDI provides a personalized and clinically feasible model for microstructure, increasing sensitivity to pathological alterations.

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