RESEARCH ARTICLE


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
1 Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
2 Department of Emergency Medicine and Department of Exercise and Sport Science,University of North Carolina at Chapel Hill, NC,USA
3 Department of Computer Science University of North Carolina at Chapel Hill, NC, USA
4 School of Computing University of Utah, Salt Lake City, Utah, USA
5 Department of Pschiatry and Department of Computer Science University of North Carolina at Chapel Hill, NC, USA
6 Department of Exercise and Sport Science, Department of Emergency Medicine and Department of Allied Health Sciences, University of North Carolina at Chapel Hill, NC, USA

Article Information


Identifiers and Pagination:

Year: 2012
Volume: 6
First Page: 80
Last Page: 88
Publisher Id: TOMIJ-6-80
DOI: 10.2174/1874347101206010080

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

© 2012 Liu et al.

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.

* Address correspondence to this author at the Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA; Tel: +1-919-265 7506; Fax: (919) 966-7659; E-mail: farzinfa@email.unc.edu


Abstract

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.

Keywords: Diffusion tensor imaging, DTI atlas, voxel-wise analysis, nonlinear warping, aging and aerobic fitness.