ArticleNMR in biomedicine2017
Precision and accuracy of diffusion kurtosis estimation and the influence of b-value selection.
Article in NMR in biomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Neurodegeneration and energy depletion in MS: Links between tissue integrity loss and microvascular changes in white matter disease.Neuroimage. Reports · 2026Article
- Quantitative pancreatic MRI in diabetes mellitus: current advances and future directions.Frontiers in endocrinology · 2026Review
- 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
- Prognostic Value of Pre-Treatment Diffusion Kurtosis Imaging for Progression-Free Survival Prediction in Advanced Nasopharyngeal Carcinoma.Cancer medicine · 2025Article
- Diffusion MRI with double diffusion encoding and variable mixing times disentangles water exchange from transient kurtosis.Scientific reports · 2025Article
- Brain white matter development in 8-year-old children is associated with maternal mental health during pregnancy.Frontiers in human neuroscience · 2025Article
- Surface-based Analyses of Diffusional Kurtosis Imaging in Amyotrophic Lateral Sclerosis: Relationship with Onset Subtypes.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Tuned exchange imaging: Can the filter exchange imaging pulse sequence be adapted for applications with thin slices and restricted diffusion?NMR in biomedicine · 2024Article
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- Efficient PCA denoising of spatially correlated redundant MRI data.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Diffusion MRI with pulsed and free gradient waveforms: Effects of restricted diffusion and exchange.NMR in biomedicine · 2023Article
- Optimization of quasi-diffusion magnetic resonance imaging for quantitative accuracy and time-efficient acquisition.Magnetic resonance in medicine · 2022Article
- Improved diffusion parameter estimation by incorporating TNeuroImage · 2022Article
- Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology.Magnetic resonance in medicine · 2022Article
- Evidence for microscopic kurtosis in neural tissue revealed by correlation tensor MRI.Magnetic resonance in medicine · 2021Article
- Toward more robust and reproducible diffusion kurtosis imaging.Magnetic resonance in medicine · 2021Article
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3 authors.
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Abstract
Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging that accounts for leading non-Gaussian diffusion effects. In DKI studies, a wide range of different gradient strengths (b-values) is used, which is known to affect the estimated diffusivity and kurtosis parameters. Hence there is a need to assess the accuracy and precision of the estimated parameters as a function of b-value. This work examines the error in the estimation of mean of the kurtosis tensor (MKT) with respect to the ground truth, using simulations based on a biophysical model for both gray (GM) and white (WM) matter. Model parameters are derived from densely sampled experimental data acquired in ex vivo rat brain and in vivo human brain. Additionally, the variability of MKT is studied using the experimental data. Prevalent fitting protocols are implemented and investigated. The results show strong dependence on the maximum b-value of both net relative error and standard deviation of error for all of the employed fitting protocols. The choice of b-values with minimum MKT estimation error and standard deviation of error was found to depend on the protocol type and the tissue. Protocols that utilize two terms of the cumulant expansion (DKI) were found to achieve minimum error in GM at b-values less than 1 ms/μm
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