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Abstract #2687

A methodological study on DTI indices: from preprocessing to analysis with application to multiple sclerosis

Catarina Freitas 1 , Varun Sethi 1 , Nils Muhlert 1 , Olga Ciccarelli 2 , Mara Cercignani 3 , Declan Chard 2 , Hui Zhang 4 , and Claudia Wheeler-Kingshott 1

1 Department of Neuroinflammation, UCL Institute of Neurology, London, United Kingdom, 2 Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, United Kingdom, 3 Department of Neuroscience, University of Sussex, Brighton, United Kingdom, 4 Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom

Misinterpretation of differences in the diffusion tensor (DT) indices between patients and healthy controls (HC) may occur when the geometrical properties of each dataset are not taken into account. Here, we tested a new analysis method that has been suggested to solve this problem, in a group comparison of HCs and patients with multiple sclerosis (MS). In addition, we investigated the effect of registration by using DT-based and fractional anisotropy (FA)-based methods. The analysis showed the new approach may help to reveal WM subtle changes and the importance of determining which registration method is more appropriate to study WM pathology.

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