Abstract #3290

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

Daniel Johnson^1,2, Antonio Ricciardi^1,3,4, Wallace Brownlee¹, Baris Kanber^1,5, Ferran Prados^1,5,6, Sara Collorone¹, Enrico Kaden³, Ahmed Toosy^1,7, Daniel Alexander³, Claudia Angela Gandini Wheeler-Kingshott^1,8,9, Olga Ciccarelli^1,7, and Francesco Grussu^1,3

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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