ArticleMagnetic resonance imaging2019
Water mobility spectral imaging of the spinal cord: Parametrization of model-free Laplace MRI.
Article in Magnetic resonance imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain.Research square · 2026Article
- Separable multidimensional MRI signatures of cellular and structural pathology in Alzheimer's disease.bioRxiv : the preprint server for biology · 2026Article
- Multidimensional MRI reveals cortical astrogliosis linked to dementia in Alzheimer's disease.Brain communications · 2025Article
- Neuronal microstructural changes in the human brain are associated with neurocognitive aging.Aging cell · 2024Article
- Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.Magnetic resonance in medicine · 2024Article
- Neuronal microstructural changes in the human brain are associated with neurocognitive aging.bioRxiv : the preprint server for biology · 2024Article
- Mapping astrogliosis in the individual human brain using multidimensional MRI.Brain : a journal of neurology · 2023Article
- Loss of aquaporin-4 results in glymphatic system dysfunction via brain-wide interstitial fluid stagnation.eLife · 2023Article
- Mapping the individual human cortex using multidimensional MRI and unsupervised learning.Brain communications · 2023Article
- Disentangling the effects of restriction and exchange with diffusion exchange spectroscopy.Frontiers in physics · 2022Article
- Combined diffusion-relaxometry microstructure imaging: Current status and future prospects.Magnetic resonance in medicine · 2021Review
- Multidimensional MRI for Characterization of Subtle Axonal Injury Accelerated Using an Adaptive Nonlocal Multispectral Filter.Frontiers in physics · 2021Article
- Multidimensional correlation MRI.NMR in biomedicine · 2020Article
- Full-Harmonics Phasor Analysis: Unravelling Multiexponential Trends in Magnetic Resonance Imaging Data.The journal of physical chemistry letters · 2020Article
- Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging.NeuroImage · 2020Article
- Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising.NeuroImage · 2020Article
- Retaining information from multidimensional correlation MRI using a spectral regions of interest generator.Scientific reports · 2020Article
- Article
- Widespread gray and white matter microstructural alterations in dual cognitive-motor deficit.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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2 authors.
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Abstract
Diffusion magnetic resonance imaging (dMRI) of biological systems most often results in non-monoexponential signal, due to their complexity and heterogeneity. One approach to interpreting dMRI data without imposing tissue microstructural models is to fit the signal to a multiexponential function, which is sometimes referred to as an inverse Laplace transformation, and to display the coefficients as a distribution of the diffusivities, or water mobility spectra. Until recently, this method has not been used in a voxelwise manner, mainly because of heavy data requirements. With recent advancements in processing and experimental design, voxelwise Laplace MRI approaches are becoming feasible and attractive. The rich spectral information, combined with a three-dimensional image, presents a challenge because it tremendously increases the dimensionality of the data and requires a robust method for interpretation and analysis. In this work, we suggest parameterizing the empirically measured water mobility spectra using a bimodal lognormal function. This approach allows for a compact representation of the spectrum, and it also resolves overlapping spectral peaks, which allows for a robust extraction of their signal fraction. We apply the method on a fixed spinal cord sample and use it to generate robust intensity images of slow- and fast-diffusion components. Using the parametric variables, we create novel image contrasts, among them the information entropy of the water mobility spectrum, which pack unique features of the individual diffusion regimes in the investigated system.
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