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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.

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