Automated Voxel-Wise Brain DTI Analysis of Fitness and Aging
Zhexing Liu1, Mahshid Farzinfar*, 1, Laurence M. Katz2, Hongtu Zhu3, Casey B. Goodlett4, Guido Gerig4, Martin Styner5, Bonita L. Marks6
Identifiers and Pagination:Year: 2012
First Page: 80
Last Page: 88
Publisher Id: TOMIJ-6-80
Article History:Received Date: 3/10/2011
Revision Received Date: 10/02/2012
Acceptance Date: 15/02/2012
Electronic publication date: 1/6/2012
Collection year: 2012
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Diffusion Tensor Imaging (DTI) has become a widely used MR modality to investigate white matter integrity in the brain. This paper presents the application of an automated method for voxel-wise group comparisons of DTI images in a study of fitness and aging. The automated processing method consists of 3 steps: 1) preprocessing including image format converting, image quality control, eddy-current and motion artifact correction, skull stripping and tensor image estimation, 2) study-specific unbiased DTI atlas computation via diffeomorphic fluid-based and demons deformable registration and 3) voxel-wise statistical analysis via heterogeneous linear regression and a wild bootstrap technique for correcting for multiple comparisons. Our results show that this fully automated method is suitable for voxel-wise group DTI analysis. Furthermore, in older adults, the results suggest a strong link between reduced fractional anisotropy (FA) values, fitness and aging.