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Deterministic diffusion fiber tracking improved by quantitative anisotropy

Yeh, FC and Verstynen, TD and Wang, Y and Fernández-Miranda, JC and Tseng, WYI (2013) Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS ONE, 8 (11).

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Abstract

Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T 1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics. © 2013 Yeh et al.

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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Yeh, FCfrank.yeh@pitt.eduYEHFC
Verstynen, TD
Wang, Y
Fernández-Miranda, JC
Tseng, WYI
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorZhan, WangUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 15 November 2013
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 8
Number: 11
DOI or Unique Handle: 10.1371/journal.pone.0080713
Schools and Programs: School of Medicine > Neurobiology
Refereed: Yes
Date Deposited: 30 Jan 2014 18:09
Last Modified: 25 Jun 2021 19:55
URI: http://d-scholarship.pitt.edu/id/eprint/20396

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