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An in vivo multi-modal structural template for neonatal piglets using high angular resolution and population-based whole-brain tractography

Authors :
Jidan Zhong
David Qixiang Chen
Matthew Walker
Adam Waspe
Thomas Looi
Karolina Piorkowska
James M. Drake
Mojgan Hodaie
Source :
Frontiers in Neuroanatomy, Vol 10 (2016)
Publication Year :
2016
Publisher :
Frontiers Media S.A., 2016.

Abstract

An increasing number of applications use the postnatal piglet model in neuroimaging studies, however these are based primarily on T1 weighted image templates. There is a growing need for a multimodal structural brain template for a comprehensive depiction of the piglet brain, particularly given the growing applications of diffusion weighted imaging for characterizing tissue microstructures and white matter organization. In this study, we present the first multimodal piglet structural brain template which includes a T1 weighted image with tissue segmentation probability maps, diffusion weighted metric templates with multiple diffusivity maps, and population-based whole-brain fiber tracts for postnatal piglets. These maps provide information about the integrity of white matter that is not available in T1 images alone. The availability of this diffusion weighted metric template will contribute to the structural imaging analysis of the postnatal piglet brain, especially models that are designed for the study of white matter diseases. Furthermore, the population-based whole-brain fiber tracts permit researchers to visualize the white matter connections in the piglet brain across subjects, guiding the delineation of a specific white matter region for structural analysis where current diffusion data is lacking. Researchers are able to augment the tracts by merging tracts from their own data to the population-based fiber tracts and thus improve the confidence of the population-wise fiber distribution.

Details

Language :
English
ISSN :
16625129
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neuroanatomy
Publication Type :
Academic Journal
Accession number :
edsdoj.5c7628e75788461294a3cb3cfc88d289
Document Type :
article
Full Text :
https://doi.org/10.3389/fnana.2016.00092