Literature DB >> 16084741

Neuroanatomical differences between mouse strains as shown by high-resolution 3D MRI.

X Josette Chen1, Natasa Kovacevic, Nancy J Lobaugh, John G Sled, R Mark Henkelman, Jeffrey T Henderson.   

Abstract

The search for new mouse models of human disease requires a sensitive metric to make three-dimensional (3D) anatomical comparisons in a rapid and quantifiable manner. This is especially true in the brain, where changes in complex shapes such as the hippocampus and ventricles are difficult to assess with 2D histology. Here, we report that the 3D neuroanatomy of three strains of mice (129S1/SvImJ, C57/Bl6, and CD1) is significantly different from one another. Using image co-registration, we 'morphed' together nine brains of each strain scanned by magnetic resonance imaging at (60 microm)3 resolution to synthesize an average image. We applied three methods of comparison. First, we used visual inspection and graphically examined the standard deviation of the variability in each strain. Second, we annotated 42 neural structures and compared their volumes across the strains. Third, we assessed significant local deviations in volume and displacement between the two inbred strains, independent of prior anatomical knowledge.

Entities:  

Mesh:

Year:  2005        PMID: 16084741     DOI: 10.1016/j.neuroimage.2005.07.008

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  42 in total

Review 1.  3-dimensional imaging modalities for phenotyping genetically engineered mice.

Authors:  K A Powell; D Wilson
Journal:  Vet Pathol       Date:  2011-12-06       Impact factor: 2.221

2.  The modulation of BOLD variability between cognitive states varies by age and processing speed.

Authors:  Douglas D Garrett; Natasa Kovacevic; Anthony R McIntosh; Cheryl L Grady
Journal:  Cereb Cortex       Date:  2012-03-14       Impact factor: 5.357

3.  Evaluation of Atlas based Mouse Brain Segmentation.

Authors:  Joohwi Lee; Julien Jomier; Stephen Aylward; Mike Tyszka; Sheryl Moy; Jean Lauder; Martin Styner
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2009-02-01

4.  A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

Authors:  Adam Delora; Aaron Gonzales; Christopher S Medina; Adam Mitchell; Abdul Faheem Mohed; Russell E Jacobs; Elaine L Bearer
Journal:  J Neurosci Methods       Date:  2015-10-09       Impact factor: 2.390

5.  AtlasGuide: software for stereotaxic guidance using 3D CT/MRI hybrid atlases of developing mouse brains.

Authors:  Xin Li; Manisha Aggarwal; Johnny Hsu; Hangyi Jiang; Susumu Mori
Journal:  J Neurosci Methods       Date:  2013-08-27       Impact factor: 2.390

6.  A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains.

Authors:  Cheryl L Grady; Andrea B Protzner; Natasa Kovacevic; Stephen C Strother; Babak Afshin-Pour; Magda Wojtowicz; John A E Anderson; Nathan Churchill; Anthony R McIntosh
Journal:  Cereb Cortex       Date:  2009-09-29       Impact factor: 5.357

7.  The importance of being variable.

Authors:  Douglas D Garrett; Natasa Kovacevic; Anthony R McIntosh; Cheryl L Grady
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

8.  Registering and analyzing rat fMRI data in the stereotaxic framework by exploiting intrinsic anatomical features.

Authors:  Hanbing Lu; Clara A Scholl; Yantao Zuo; Steven Demny; William Rea; Elliot A Stein; Yihong Yang
Journal:  Magn Reson Imaging       Date:  2009-07-15       Impact factor: 2.546

9.  Comparison of immunopathology and locomotor recovery in C57BL/6, BUB/BnJ, and NOD-SCID mice after contusion spinal cord injury.

Authors:  Sabina Luchetti; Kevin D Beck; Manuel D Galvan; Richard Silva; Brian J Cummings; Aileen J Anderson
Journal:  J Neurotrauma       Date:  2010-02       Impact factor: 5.269

10.  Mouse embryonic phenotyping by morphometric analysis of MR images.

Authors:  M Zamyadi; L Baghdadi; J P Lerch; S Bhattacharya; J E Schneider; R M Henkelman; J G Sled
Journal:  Physiol Genomics       Date:  2010-08-03       Impact factor: 3.107

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