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

Zhan, Liang, Jahanshad, Neda, Jin, Yan, Toga, Arthur W., McMahon, Katie L., de Zubicaray, Greig I., Martin, Nicholas G., Wright, Margaret J. and Thompson, Paul M. (2013). Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects. In: ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro. 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013, San Francisco, CA, United States, (1134-1137). 7-11 April 2013. doi:10.1109/ISBI.2013.6556679

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Author Zhan, Liang
Jahanshad, Neda
Jin, Yan
Toga, Arthur W.
McMahon, Katie L.
de Zubicaray, Greig I.
Martin, Nicholas G.
Wright, Margaret J.
Thompson, Paul M.
Title of paper Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects
Conference name 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Conference location San Francisco, CA, United States
Conference dates 7-11 April 2013
Proceedings title ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro   Check publisher's open access policy
Journal name Proceedings - International Symposium on Biomedical Imaging   Check publisher's open access policy
Series Proceedings - International Symposium on Biomedical Imaging
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2013
Year available 2013
Sub-type Fully published paper
DOI 10.1109/ISBI.2013.6556679
ISBN 9781467364546
ISSN 1945-7928
Start page 1134
End page 1137
Total pages 4
Language eng
Abstract/Summary 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 (4th-8th 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.
Subjects 2741 Radiology Nuclear Medicine and imaging
Keyword Engineering, Biomedical
Radiology, Nuclear Medicine & Medical Imaging
Engineering
Radiology, Nuclear Medicine & Medical Imaging
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: 2013 Ieee 10Th International Symposium On Biomedical Imaging (Isbi)
Collections: Queensland Brain Institute Publications
Official 2014 Collection
School of Psychology Publications
Centre for Advanced Imaging Publications
 
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