ArticleNeuroImage2022
Accuracy and reliability of diffusion imaging models.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07024875 (Precision Neuroimaging of Parkinson's Disease), which is not on this map. Cited by 13 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.
Precision Neuroimaging of Parkinson's Disease
Who cites it
13 citing papers in PubMed.
- Advancing neuroprognostication in neonatal encephalopathy: promise and limitations of diffusion kurtosis imaging.Pediatric research · 2026Article
- Structure-function coupling in the first month of life: Associations with age and attention.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Improved pre-surgical localization of epileptogenic tubers in pediatric tuberous sclerosis complex using mean apparent propagator MRI.Neurosurgical review · 2025Article
- Decreased Structural Connectivity Between Thalamic Nuclei and Hippocampus in Temporal Lobe Epilepsy-A Diffusion Tensor Imaging-Based Study.European journal of neurology · 2025Article
- T1 relaxation and axon fibre configuration in human white matter.NMR in biomedicine · 2024Article
- Structure-function coupling in highly sampled individual brains.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Dynamic computational phenotyping of human cognition.Nature human behaviour · 2024Article
- Genetic architecture of the structural connectome.Nature communications · 2024Article
- Individualized targeting is warranted in subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression: A tractography analysis.Human brain mapping · 2023Article
- Article
- Within-subject reproducibility varies in multi-modal, longitudinal brain networks.Scientific reports · 2023Article
- The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives.Frontiers in network physiology · 2023Review
- Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative.Journal of Parkinson's disease · 2023Article
Corrections and comments
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Authors and funding
24 authors.
Funding
Abstract
Diffusion imaging aims to non-invasively characterize the anatomy and integrity of the brain's white matter fibers. We evaluated the accuracy and reliability of commonly used diffusion imaging methods as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). Diffusion imaging methods that allow for crossing fibers (FSL's BedpostX [BPX], DSI Studio's Constant Solid Angle Q-Ball Imaging [CSA-QBI], MRtrix3's Constrained Spherical Deconvolution [CSD]) estimated excess fibers when insufficient data were present and/or when the data did not match the model priors. To reduce such overfitting, we developed a novel Bayesian Multi-tensor Model-selection (BaMM) method and applied it to the popular ball-and-stick model used in BedpostX within the FSL software package. BaMM was robust to overfitting and showed high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, sufficient data and an overfitting resistant analysis method enhance precision diffusion imaging. For potential clinical applications of diffusion imaging, such as neurosurgical planning and deep brain stimulation (DBS), the quantities of data required to achieve diffusion imaging reliability are lower than those needed for functional MRI.
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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.