Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

A stereotaxic breed-averaged, symmetric T2w canine brain atlas including detailed morphological and volumetrical data sets

Tools
- Tools
+ Tools

Nitzsche, Björn, Boltze, Johannes, Ludewig, Eberhard, Flegel, Thomas, Schmidt, Martin J., Seeger, Johannes, Barthel, Henryk, Brooks, Olivia W., Gounis, Matthew J., Stoffel, Michael H. and Schulze, Sabine (2019) A stereotaxic breed-averaged, symmetric T2w canine brain atlas including detailed morphological and volumetrical data sets. NeuroImage, 187 . pp. 93-103. doi:10.1016/j.neuroimage.2018.01.066 ISSN 1053-8119.

Research output not available from this repository.

Request-a-Copy directly from author or use local Library Get it For Me service.

Official URL: http://dx.doi.org/10.1016/j.neuroimage.2018.01.066

Request Changes to record.

Abstract

Stereotaxic systems and automatic tissue segmentation routines enable neuronavigation as well as reproducible processing of neuroimage datasets. Such systems have been developed for humans, non-human-primates, sheep, and rodents, but not for dogs. Although dogs share important neurofunctional and -anatomical features with humans, and in spite of their importance in translational neuroscience, little is known about the variability of the canine brain morphology and, possibly related, function. Moreover, we lack templates, tissue probability maps (TPM), and stereotaxic brain labels for implementation in standard software utilities such as Statistical Parametric Mapping (SPM). Hence, objective and reproducible, image-based investigations are currently impeded in dogs. We have created a detailed stereotaxic reference frame for dogs including TPM and tissue labels, enabling inter-individual and cross-study neuroimage analysis.
T2w datasets were acquired from 16 neurologically inconspicuous dogs of different breeds by 3T MRI. The datasets were averaged after initial preprocessing using linear and nonlinear registration algorithms as implemented in SPM8. TPM for gray (GM) and white matter (WM) as well as cerebrospinal fluid (CSF) were created. Different cortical, subcortical, medullary, and CSF regions were manually labeled to create a spatial binary atlas being aligned with the template. A proof-of-concept for automatic determination of morphological and volumetrical characteristics was performed using additional canine datasets (n = 64) including a subgroup of laboratory beagles (n = 24).
Overall, 21 brain regions were labeled using the segmented tissue classes of the brain template. The proof-of-concept trial revealed excellent suitability of the created tools for image processing and subsequent analysis. There was high intra-breed variability in frontal lobe and hippocampus volumes, and noticeable inter-breed corpus callosum volume variation.
The T2w brain template provides important, breed-averaged canine brain anatomy features in a spatial standard coordinate system. TPM allows automatic tissue segmentation using SPM and enables unbiased automatic image processing or morphological characterization in different canine breeds. The reported volumetric and morphometric results may serve as a starting point for further research aimed at in vivo analysis of canine brain anatomy and function.

Item Type: Journal Article
Divisions: Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Journal or Publication Title: NeuroImage
Publisher: Elsevier
ISSN: 1053-8119
Official Date: 15 February 2019
Dates:
DateEvent
15 February 2019Published
31 January 2018Available
25 January 2018Accepted
Volume: 187
Page Range: pp. 93-103
DOI: 10.1016/j.neuroimage.2018.01.066
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us