ArticlePloS one
Fully-Automated μMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome.
Article in PloS one. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 22 citations in OpenAlex.
- Molecular and imaging biomarker responses to brain mutant HTT lowering in a mouse model of Huntington disease.Molecular therapy. Nucleic acids · 2025Article
- Human mutations inFrontiers in molecular neuroscience · 2024Article
- Investigating brain alterations in the Dp1Tyb mouse model of Down syndrome.Neurobiology of disease · 2023Article
- AAV5-miHTT-mediated huntingtin lowering improves brain health in a Huntington's disease mouse model.Brain : a journal of neurology · 2023Article
- Overexpression screen of chromosome 21 genes reveals modulators of Sonic hedgehog signaling relevant to Down syndrome.Disease models & mechanisms · 2023Article
- Volume of the thalamus and hypothalamus in the Ts1Rhr and Ms1Rhr mouse models relevant to Down syndrome.microPublication biology · 2023Article
- A transchromosomic rat model with human chromosome 21 shows robust Down syndrome features.American journal of human genetics · 2022Article
- Time-dependent diffusion MRI probes cerebellar microstructural alterations in a mouse model of Down syndrome.Brain communications · 2021Article
- Article
- Sammba-MRI: A Library for Processing SmAll-MaMmal BrAin MRI Data in Python.Frontiers in neuroinformatics · 2020Article
- Study the LongitudinalFrontiers in neuroscience · 2019Article
- Correction of cognitive deficits in mouse models of Down syndrome by a pharmacological inhibitor of DYRK1A.Disease models & mechanisms · 2018Article
- Within-subject test-retest reliability of the atlas-based cortical volume measurement in the rat brain: A voxel-based morphometry study.Journal of neuroscience methods · 2018Article
- Rodent models in Down syndrome research: impact and future opportunities.Disease models & mechanisms · 2017Review
- Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease.NeuroImage · 2017Article
- Comparison ofFrontiers in neuroinformatics · 2017Article
Corrections and comments
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Authors and funding
14 authors at 3 institutions in 2 countries.
Funding
Abstract
We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques-superior to single-atlas methods-together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry-advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.