Evaluation of diffusion imaging protocols for the Alzheimer's disease neuroimaging initiative

L. Zhan, M. A. Bernstein, B. Borowski, Clifford R. Jack, P. M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Diffusion-weighted imaging (DWI) provides information on brain integrity and connectivity, based on mapping the directional diffusion of water along the brain's neural pathways. The latest stage of the Alzheimer's Disease Neuroimaging Initiative, ADNI-2, added a 9-minute 41-gradient DWI protocol. To study the potential benefits of adjusting the number of diffusion-weighted gradients, here we scanned 3 young adults with the ADNI DWI protocol and 3 variants reducing the voxel size, increasing the repetition time (TR), and increasing the number of diffusion-weighted directions. In a small pilot evaluation, we compared the signal-to-noise ratio (SNR) of diffusion tensor-derived fractional anisotropy (FA), as well as three standard graph theory measures, to assess protocol effects on anatomical network efficiency, clustering and modularity. The protocol with smaller voxels gave rise to more detected fibers in whole-brain tractography, but no protocol advantages were detectable in the small sample; all gave comparable FA SNR, connectivity and network measures.

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages710-713
Number of pages4
ISBN (Electronic)9781467319591
DOIs
StatePublished - 29 Jul 2014
Externally publishedYes
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 29 Apr 20142 May 2014

Publication series

Name2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/TerritoryChina
CityBeijing
Period29/04/142/05/14

Keywords

  • Anisotropy
  • Brain network
  • Connectivity
  • Diffusion MRI
  • Protocol
  • SNR

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