Correlation between diffusion kurtosis and NODDI metrics in neonates and young children

Shaheen Ahmed, Zhiyue J. Wang, Jonathan M. Chia, Nancy K. Rollins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Diffusion Tensor Imaging (DTI) uses single shell gradient encoding scheme for studying brain tissue diffusion. NODDI (Neurite Orientation Dispersion and Density Imaging) incorporates a gradient scheme with multiple b-values which is used to characterize neurite density and coherence of neuron fiber orientations. Similarly, the diffusion kurtosis imaging also uses a multiple shell scheme to quantify non-Gaussian diffusion but does not assume a tissue model like NODDI. In this study we investigate the connection between metrics used by NODDI and DKI in children with ages from 46 weeks to 6 years. We correlate the NODDI metrics and Kurtosis measures from the same ROIs in multiple brain regions. We compare the range of these metrics between neonates (46 - 47 weeks), infants (2 -10 months) and young children (2 - 6 years).

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510600232
DOIs
StatePublished - 2016
EventMedical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, United States
Duration: Mar 1 2016Mar 3 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9788
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/TerritoryUnited States
CitySan Diego
Period3/1/163/3/16

Keywords

  • Correlation
  • DTI
  • Kurtosis imaging
  • NODDI
  • Neonates

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging
  • Biomaterials

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