ArticleMagnetic resonance in medicine2019
Resolving degeneracy in diffusion MRI biophysical model parameter estimation using double diffusion encoding.
Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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
45 citing papers in PubMed.
- Beyond Directions: Symmetry-Aware Rotation Sets for Triaxial Diffusion Encoding by Geometric Filter Optimization.Magnetic resonance in medicine · 2026Article
- Toward Super-Resolution Reconstruction of Diffusion-Relaxation MRI Using Slice Excitation With Random Overlap (SERO).Magnetic resonance in medicine · 2026Article
- 40 Years of diffusion MRI in the brain: From history to emerging frontiers.Imaging neuroscience (Cambridge, Mass.) · 2026Review
- Article
- Implicit neural representations for accurate estimation of the Standard Model of white matter.Communications biology · 2025Article
- Linear rotationally invariant kurtosis measures from double diffusion encoding MRI.Magnetic resonance imaging · 2025Article
- Implicit neural representations for accurate estimation of the standard model of white matter.ArXiv · 2025Article
- Comparison of different neurite density metrics with brain asymmetry evaluation.Zeitschrift fur medizinische Physik · 2025Article
- Local response function estimation in spherical deconvolution for comprehensive tissue representation using diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Characterization of neurite and soma organization in the brain and spinal cord with diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Linking microscopy to diffusion MRI with degenerate biophysical models: An application of the Bayesian EstimatioN of CHange (BENCH) framework.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Radiofrequency Enhancer to Recover Signal Dropouts in 7 Tesla Diffusion MRI.Sensors (Basel, Switzerland) · 2024Article
- The Diffusion Exchange Ratio (DEXR): A minimal sampling of diffusion exchange spectroscopy to probe exchange, restriction, and time-dependence.bioRxiv : the preprint server for biology · 2024Article
- Assessment of precision and accuracy of brain white matter microstructure using combined diffusion MRI and relaxometry.Human brain mapping · 2024Article
- Insights and improvements in correspondence between axonal volume fraction measured with diffusion-weighted MRI and electron microscopy.NMR in biomedicine · 2024Article
- Article
- Mapping tissue microstructure of brain white matter in vivo in health and disease using diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Measuring cardiomyocyte cellular characteristics in cardiac hypertrophy using diffusion-weighted MRI.Magnetic resonance in medicine · 2023Article
- Optimized rectification of fiber orientation density function with background threshold.Magnetic resonance imaging · 2023Article
- Identifying microstructural changes in diffusion MRI; How to circumvent parameter degeneracy.NeuroImage · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeBiophysical tissue models are increasingly used in the interpretation of diffusion MRI (dMRI) data, with the potential to provide specific biomarkers of brain microstructural changes. However, it has been shown recently that, in the general Standard Model, parameter estimation from dMRI data is ill-conditioned even when very high b-values are applied. We analyze this issue for the Neurite Orientation Dispersion and Density Imaging with Diffusivity Assessment (NODDIDA) model and demonstrate that its extension from single diffusion encoding (SDE) to double diffusion encoding (DDE) resolves the ill-posedness for intermediate diffusion weightings, producing an increase in accuracy and precision of the parameter estimation.
methodsWe analyze theoretically the cumulant expansion up to fourth order in b of SDE and DDE signals. Additionally, we perform in silico experiments to compare SDE and DDE capabilities under similar noise conditions.
resultsWe prove analytically that DDE provides invariant information non-accessible from SDE, which makes the NODDIDA parameter estimation injective. The in silico experiments show that DDE reduces the bias and mean square error of the estimation along the whole feasible region of 5D model parameter space.
conclusionsDDE adds additional information for estimating the model parameters, unexplored by SDE. We show, as an example, that this is sufficient to solve the previously reported degeneracies in the NODDIDA model parameter estimation.
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.