Farida Grinberg1,2, Xiang Gao1, Ezequiel Farrher1, and N. Jon Shah1,2
1Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH, Juelich, Germany, 2Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
Between-group comparisons of diffusion tensor and diffusion kurtosis
imaging metrics are important for elucidation of differences between pathology
and healthy state. However, thus far, the methodology of such comparisons has
not been well established. Frequently used methods, such as region-of-interest
analysis or atlas-based analysis are subject to errors due to partial volume effects,
whereas the track-based spatial statistics reduces consideration to a small
amount of voxels along the skeleton, thus diminishing useful information. In
this work we represent a simple, robust diffusion-kurtosis-informed template effectively
reducing partial volume effects in the atlas-based analysis using less
restrictive approach.
