Fully-Automated μMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome

• DOI: 10.1371/journal.pone.0162974
• Publication Date: 2016-09-22T17:41:21Z
• Authors: Nick M. Powell; Marc Modat; M. Jorge Cardoso; Da Ma; Holly E. Holmes; Yichao Yu; James O’Callaghan; Jon O. Cleary; Ben Sinclair; Frances K. Wiseman; Victor L. J. Tybu...; Elizabeth M. C. F...; Mark F. Lythgoe; Sébastien Ourselin
• Keywords: Brain morphometry; Brain atlas; Ex vivo

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to Tc1 model Down syndrome, identify new morphological phenotypes in brain this first transchromosomic animal carrying human chromosome 21. incorporate an accessible approach simultaneously scanning multiple ex vivo brains, requiring only 3D-printed holder, novel image processing steps their separation orientation. employ clinically established multi-atlas techniques-superior single-atlas methods-together with publicly-available atlas databases automatic skull-stripping tissue segmentation, providing high-quality, subject-specific maps. follow these group-wise registration, structural parcellation both Voxel- Tensor-Based Morphometry-advantageous ability highlight differences without laborious delineation regions interest. freely available open-source software developed clinical MRI analysis data: NiftySeg segmentation NiftyReg discuss atlases parameters suitable preclinical paradigm. used compare 29 26 wild-type littermate controls, imaged at 9.4T. unexpected increase total intracranial volume and, controlling this, local grey matter density reductions compared wild-types, most prominently cerebellum, agreement DS previous histological findings.