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Statistical differences in the white matter tracts in subjects with depression by using different skeletonized voxel-wise analysis approaches and DTI fitting procedures
Laureate Institute for Brain Research, Tulsa, OK, USA.
Roosevelt University, Department of Industrial and Organizational Psychology, Chicago, IL, USA.
Laureate Institute for Brain Research, Tulsa, OK, USA.
Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
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2017 (English)In: Brain Research, ISSN 0006-8993, E-ISSN 1872-6240, Vol. 1669, p. 131-140Article in journal (Refereed) Published
Abstract [en]

Major depressive disorder (MDD) is one of the most significant contributors to the global burden of illness. Diffusion tensor imaging (DTI) is a procedure that has been used in several studies to characterize abnormalities in white matter (WM) microstructural integrity in MDD. These studies, however, have provided divergent findings, potentially due to the large variety of methodological alternatives available in conducting DTI research. In order to determine the importance of different approaches to coregistration of DTI-derived metrics to a standard space, we compared results from two different skeletonized voxel-wise analysis approaches: the standard TBBS pipeline and the Advanced Normalization Tools (ANTs) approach incorporating a symmetric image normalization (SyN) algorithm and a group-wise template (ANTs TBSS). We also assessed effects of applying twelve different fitting procedures for the diffusion tensor. For our dataset, lower fractional anisotropy (FA) and axial diffusivity (AD) in depressed subjects compared with healthy controls were found for both methods and for all fitting procedures. No group differences were found for radial and mean diffusivity indices. Importantly, for the AD metric, the normalization methods and fitting procedures showed reliable differences, both in the volume and in the number of significant between-groups difference clusters detected. Additionally, a significant voxel-based correlation, in the left inferior fronto-occipital fasciculus, between AD and self-reported stress was found only for one of the normalization procedure (ANTs TBSS). In conclusion, the sensitivity to detect group-level effects on DTI metrics might depend on the DTI normalization and/or tensor fitting procedures used.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 1669, p. 131-140
Keywords [en]
ANTs; DTI fitting algorithms; Diffusion tensor imaging; Major depressive disorder; TBSS
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:liu:diva-146289DOI: 10.1016/j.brainres.2017.06.013ISI: 000406729700016PubMedID: 28629742OAI: oai:DiVA.org:liu-146289DiVA, id: diva2:1195919
Available from: 2018-04-07 Created: 2018-04-07 Last updated: 2019-02-11

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Hamilton, Paul J.

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