Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

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 exam...

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Main Authors:	Yeh, Fang-Cheng, Verstynen, Timothy D., Wang, Yibao, Fernández-Miranda, Juan C., Tseng, Wen-Yih Isaac
Format:	Online
Language:	English
Published:	Public Library of Science 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3858183/

id	pubmed-3858183
recordtype	oai_dc
spelling	pubmed-38581832013-12-12 Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy Yeh, Fang-Cheng Verstynen, Timothy D. Wang, Yibao Fernández-Miranda, Juan C. Tseng, Wen-Yih Isaac Research Article 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 T1-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. Public Library of Science 2013-11-15 /pmc/articles/PMC3858183/ /pubmed/24348913 http://dx.doi.org/10.1371/journal.pone.0080713 Text en © 2013 Yeh et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Yeh, Fang-Cheng Verstynen, Timothy D. Wang, Yibao Fernández-Miranda, Juan C. Tseng, Wen-Yih Isaac
spellingShingle	Yeh, Fang-Cheng Verstynen, Timothy D. Wang, Yibao Fernández-Miranda, Juan C. Tseng, Wen-Yih Isaac Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
author_facet	Yeh, Fang-Cheng Verstynen, Timothy D. Wang, Yibao Fernández-Miranda, Juan C. Tseng, Wen-Yih Isaac
author_sort	Yeh, Fang-Cheng
title	Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
title_short	Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
title_full	Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
title_fullStr	Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
title_full_unstemmed	Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
title_sort	deterministic diffusion fiber tracking improved by quantitative anisotropy
description	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 T1-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.
publisher	Public Library of Science
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3858183/
_version_	1612037007162212352

Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

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