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Population based MRI and DTI templates of the adult ferret brain and tools for voxelwise analysis.

Abstract：

:Non-invasive imaging has the potential to play a crucial role in the characterization and translation of experimental animal models to investigate human brain development and disorders, especially when employed to study animal models that more accurately represent features of human neuroanatomy. The purpose of this study was to build and make available MRI and DTI templates and analysis tools for the ferret brain as the ferret is a well-suited species for pre-clinical MRI studies with folded cortical surface, relatively high white matter volume and body dimensions that allow imaging with pre-clinical MRI scanners. Four ferret brain templates were built in this study - in-vivo MRI and DTI and ex-vivo MRI and DTI - using brain images across many ferrets and region of interest (ROI) masks corresponding to established ferret neuroanatomy were generated by semi-automatic and manual segmentation. The templates and ROI masks were used to create a web-based ferret brain viewing software for browsing the MRI and DTI volumes with annotations based on the ROI masks. A second objective of this study was to provide a careful description of the imaging methods used for acquisition, processing, registration and template building and to demonstrate several voxelwise analysis methods including Jacobian analysis of morphometry differences between the female and male brain and bias-free identification of DTI abnormalities in an injured ferret brain. The templates, tools and methodological optimization presented in this study are intended to advance non-invasive imaging approaches for human-similar animal species that will enable the use of pre-clinical MRI studies for understanding and treating brain disorders.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Hutchinson EB,Schwerin SC,Radomski KL,Sadeghi N,Jenkins J,Komlosh ME,Irfanoglu MO,Juliano SL,Pierpaoli C

doi

10.1016/j.neuroimage.2017.03.009

subject

Has Abstract

pub_date

2017-05-15 00:00:00

pages

575-589

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(17)30217-3

journal_volume

152

pub_type

杂志文章

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