Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution di...

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Published in2013 IEEE 10th International Symposium on Biomedical Imaging pp. 1134 - 1137
Main Authors Liang Zhan, Jahanshad, Neda, Yan Jin, Toga, Arthur W., McMahon, Katie L., de Zubicaray, Greig I., Martin, Nicholas G., Wright, Margaret J., Thompson, Paul M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2013
Subjects
Online AccessGet full text
ISBN1467364568
9781467364560
ISSN1945-7928
DOI10.1109/ISBI.2013.6556679

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Abstract As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70 × 70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4 th -8 th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.
AbstractList As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70 × 70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4 th -8 th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.
Author Jahanshad, Neda
McMahon, Katie L.
Liang Zhan
Wright, Margaret J.
de Zubicaray, Greig I.
Yan Jin
Martin, Nicholas G.
Thompson, Paul M.
Toga, Arthur W.
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  organization: Sch. of Med., Lab. of Neuro Imaging, UCLA, Los Angeles, CA, USA
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Snippet As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how...
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StartPage 1134
SubjectTerms Anatomical connectivity
brain
diffusion imaging
efficiency
Graph theory
Magnetic resonance imaging
networks
Optical fiber networks
Optical fiber theory
Probabilistic logic
random effects analysis
tractography
Transforms
Title Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects
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