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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