ArticleFrontiers in physics2020
Optimizing Diffusion Imaging Protocols for Structural Connectomics in Mouse Models of Neurological Conditions.
Article in Frontiers in physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.
- A systematic review of the relationship between magnetic resonance imaging based resting-state and structural networks in the rodent brain.Frontiers in neuroscience · 2023Pooled it
- Magnetic resonance imaging in multiple sclerosis animal models: A systematic review, meta-analysis, and white paper.NeuroImage. Clinical · 2020Pooled it
- Olfactory-Guided Behavior Uncovers Imaging and Molecular Signatures of Alzheimer's Disease Risk.Brain sciences · 2025Article
- Smelling the Risk: Early Olfactory Deficits, Brain Networks, and Blood Markers of Alzheimer's Disease Risk in Humanized APOE Mice.bioRxiv : the preprint server for biology · 2025Article
- Mapping the impact of age and APOE risk factors for late onset Alzheimer's disease on long range brain connections through multiscale bundle analysis.Brain structure & function · 2025Article
- High-resolution structural connectivity mediates age-related differences in functional connectivity and fluid cognition.Brain communications · 2025Article
- Mapping the impact of age and APOE risk factors for late onset Alzheimer's disease on long range brain connections through multiscale bundle analysis.bioRxiv : the preprint server for biology · 2024Article
- Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment.Sensors (Basel, Switzerland) · 2024Article
- Accelerated Brain Atrophy, Microstructural Decline and Connectopathy in Age-Related Macular Degeneration.Biomedicines · 2024Article
- Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- High-resolution multi-shot diffusion imaging of structural networks in healthy neurocognitive aging.NeuroImage · 2023Article
- Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI.NeuroImage · 2023Article
- Identifying vulnerable brain networks associated with Alzheimer's disease risk.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Article
- Higher spatial resolution diffusion-weighted imaging improves characterization of white matter disconnection in Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.)Article
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8 authors at 2 institutions in 1 country.
Funding
Abstract
Network approaches provide sensitive biomarkers for neurological conditions, such as Alzheimer's disease (AD). Mouse models can help advance our understanding of underlying pathologies, by dissecting vulnerable circuits. While the mouse brain contains less white matter compared to the human brain, axonal diameters compare relatively well (e.g., ~0.6 μm in the mouse and ~0.65-1.05 μm in the human corpus callosum). This makes the mouse an attractive test bed for novel diffusion models and imaging protocols. Remaining questions on the accuracy and uncertainty of connectomes have prompted us to evaluate diffusion imaging protocols with various spatial and angular resolutions. We have derived structural connectomes by extracting gradient subsets from a high-spatial, high-angular resolution diffusion acquisition (120 directions, 43-μm-size voxels). We have simulated protocols with 12, 15, 20, 30, 45, 60, 80, 100, and 120 angles and at 43, 86, or 172-μm voxel sizes. The rotational stability of these schemes increased with angular resolution. The minimum condition number was achieved for 120 directions, followed by 60 and 45 directions. The percentage of voxels containing one dyad was exceeded by those with two dyads after 45 directions, and for the highest spatial resolution protocols. For the 86- or 172-μm resolutions, these ratios converged toward 55% for one and 39% for two dyads, respectively, with <7% from voxels with three dyads. Tractography errors, estimated through dyad dispersion, decreased most with angular resolution. Spatial resolution effects became noticeable at 172 μm. Smaller tracts, e.g., the fornix, were affected more than larger ones, e.g., the fimbria. We observed an inflection point for 45 directions, and an asymptotic behavior after 60 directions, corresponding to similar projection density maps. Spatially downsampling to 86 μm, while maintaining the angular resolution, achieved a subgraph similarity of 96% relative to the reference. Using 60 directions with 86- or 172-μm voxels resulted in 94% similarity. Node similarity metrics indicated that major white matter tracts were more robust to downsampling relative to cortical regions. Our study provides guidelines for new protocols in mouse models of neurological conditions, so as to achieve similar connectomes, while increasing efficiency.
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