ArticleNeuroImage2022
Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- 10.5 T In Vivo Head Imaging With Universal RF Shimming.Magnetic resonance in medicine · 2026Article
- In vivo submillimeter diffusion MRI dataset of 9 macaque brains curated for tractography.Scientific data · 2025Article
- Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging.Magnetic resonance in medicine · 2025Review
- Performance of receive head arrays versus ultimate intrinsic SNR at 7 T and 10.5 T.Magnetic resonance in medicine · 2024Article
- A semi-automated pipeline for finite element modeling of electric field induced in nonhuman primates by transcranial magnetic stimulation.Journal of neuroscience methods · 2024Article
- Anatomical details affect electric field predictions for non-invasive brain stimulation in non-human primates.NeuroImage · 2023Article
- A new open, high-resolution, multishell, diffusion-weighted imaging dataset of the living squirrel monkey.Scientific data · 2023Article
- Germany's journey toward 14 Tesla human magnetic resonance.Magma (New York, N.Y.) · 2023Review
- Multiple routes of communication within the amygdala-mPFC network: A comparative approach in humans and macaques.Current research in neurobiology · 2023Review
- Cardiovascular effects on high-resolution 3D multi-shot diffusion MRI of the rhesus macaque brain.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Retinal nerve fibre layer thickness reflects characteristics of brain grey and white matter.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 2 countries.
Funding
Abstract
Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.
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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.