ArticleFrontiers in neuroscience2018
Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging.
Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Retinal layer assessments as potential biomarkers for brain atrophy in the Rhineland Study.Scientific reports · 2022Trial
- Effects of Physical Activity on Brain White Matter Integrity Are Region-, Dose-, and Age-Dependent: Findings From the Population-Based Rhineland Study.Aging cell · 2026Article
- Versatile MRI acquisition and processing protocol for population-based neuroimaging.Nature protocols · 2025Review
- Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease.Molecular psychiatry · 2024Article
- Geometric deep learning for diffusion MRI signal reconstruction with continuous samplings (DISCUS).Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Research Progress in Diffusion Spectrum Imaging.Brain sciences · 2023Review
- Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI.NeuroImage · 2023Article
- Visual impairment and retinal and brain neurodegeneration: A population-based study.Human brain mapping · 2023Article
- Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status.Brain : a journal of neurology · 2023Review
- Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging.bioRxiv : the preprint server for biology · 2023Article
- Optimization of quasi-diffusion magnetic resonance imaging for quantitative accuracy and time-efficient acquisition.Magnetic resonance in medicine · 2022Article
- Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI.NeuroImage · 2022Article
- Safety of Tattoos, Permanent Make-Up, and Medical Implants in Population-Based 3T Magnetic Resonance Brain Imaging: The Rhineland Study.Frontiers in neurology · 2022Article
- High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation.NeuroImage · 2021Article
- Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography.NeuroImage · 2021Article
- Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain.NeuroImage · 2020Article
- Comparison of q-Space Reconstruction Methods for Undersampled Diffusion Spectrum Imaging Data.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2020Article
- Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method.NeuroImage · 2020Article
- Learning-based segmentation of diffusion-weighted MR images with arbitraryImaging 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high
Indexed as
Identifiers
What OpenQuestion holds
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.