Abstract #0692

Can NODDI provide a better characterisation of microstructural changes in ALS than DTI?

Matt Gabel¹, Rebecca Broad², Daniel C. Alexander³, Hui Zhang³, Nicholas G. Dowell¹, Peter Nigel Leigh², and Mara Cercignani¹

¹Clinical Imaging Sciences Centre, Brighton & Sussex Medical School, Falmer, United Kingdom, ²Trafford Centre for Medical Research, Brighton & Sussex Medical School, Falmer, United Kingdom, ³Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom

NODDI is a multi-compartment model of diffusion MRI that overcomes some of the limitations of DTI. Our aim was to assess whether voxelwise analysis of NODDI parameters could provide a more comprehensive picture than DTI in assessing the microstructural changes associated with ALS. We analysed NODDI and DTI parameters for 17 patients with ALS and 19 healthy controls using Advanced Normalization Tools (ANTs) 2.1.0 and SPM12, with age included as a covariate. Both NODDI and DTI indices are sensitive to pathological changes in ALS, but NODDI provides more specific tissue microstructure characterisation.

This abstract and the presentation materials are available to members only; a login is required.

Join Here