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Abstract #3290

Sensitivity of NODDI and two-compartment SMT parameter maps in multiple sclerosis

Daniel Johnson1,2, Antonio Ricciardi1,3,4, Wallace Brownlee1, Baris Kanber1,5, Ferran Prados1,5,6, Sara Collorone1, Enrico Kaden3, Ahmed Toosy1,7, Daniel Alexander3, Claudia Angela Gandini Wheeler-Kingshott1,8,9, Olga Ciccarelli1,7, and Francesco Grussu1,3

1Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 2Croydon University Hospital, London, United Kingdom, 3Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 4Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 5Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 6Universitat Oberta de Catalunya, Barcelona, Spain, 7NIHR UCLH Biomedical Research Centre, London, United Kingdom, 8Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, 9Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy

We make a novel comparison of two diffusion MRI techniques modelling white matter microstructure: neurite orientation dispersion and density imaging (NODDI) and spherical mean technique (SMT) in 63 Multiple Sclerosis (MS) patients and 28 healthy controls using tract based spatial statistics. Both techniques show that there is a reduction in the intracellular volume fraction and an increase in neurite orientation dispersion in lesions and normal appearing white matter in MS patients when compared to controls. Additionally, SMT appears more sensitive to these differences, identifying a larger number of voxels showing significant differences between patients and controls in the studied parameters.

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