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Cited by 581Advanced Neuroimaging Techniques and ApplicationsNMR spectroscopy and applicationsAdvanced MRI Techniques and Applications

Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation

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Novikov, Dmitry S., Fieremans, Els, Jespersen, Sune N., Kiselev, Valerij G.·2019·NMR in Biomedicine
DOI 10.1002/nbm.3998PMC PMC6481929
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Abstract

We review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse‐graining over an increasing diffusion length scale. From this perspective, we view research on quantifying brain microstructure as occurring along three major avenues. The first avenue focusses on transient, or time‐dependent, effects in diffusion. These effects signify the gradual coarse‐graining of tissue structure, which occurs qualitatively differently in different brain tissue compartments. We show that transient effects contain information about the relevant length scales for neuronal tissue, such as the packing correlation length for neuronal fibers, as well as the degree of structural disorder along the neurites. The second avenue corresponds to the long‐time limit, when the observed signal can be approximated as a sum of multiple nonexchanging anisotropic Gaussian components. Here, the challenge lies in parameter estimation and in resolving its hidden degeneracies. The third avenue employs multiple diffusion encoding techniques, able to access information not contained in the conventional diffusion propagator. We conclude with our outlook on future directions that could open exciting possibilities for designing quantitative markers of tissue physiology and pathology, based on methods of studying mesoscopic transport in disordered systems.

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  • Restricted and hindered diffusion mechanisms coexist within each voxel, generating non-Gaussian and time-dependent diffusion behavior.

    “These mechanisms coexist within each voxel, generating non-Gaussian and time-dependent diffusion behavior (Fieremans et al., 2016; Novikov et al., 2019).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Novikov et al., 2019

    The Standard Model section describes intra-neurite and extra-neurite diffusion contributions within a voxel, and the Time-Dependent Diffusion in Neuronal Tissue section says a sum of Gaussian contributions can be non-Gaussian. But it also says their coexistence alone does not make the overall diffusion coefficient time-dependent; that requires time dependence within at least one compartment. Page numbers were not available in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The more ambitious the biological claim, the stronger the need for external validation.

    “the more ambitious the biological claim, the stronger the need for external validation (Jelescu & Budde, 2017; Novikov et al., 2019).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Novikov et al., 2019

    In “Open questions: Precision and branch selection” (page unavailable), the review says that parameter-estimation challenges require careful validation and multiple measurements, while achieving compartmental specificity remains difficult. This supports caution about specific biological interpretations, but the paper does not state the broader rule that increasingly ambitious biological claims require correspondingly stronger external validation. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • As diffusion time increases, water molecules probe larger portions of the tissue environment and encounter more barriers or opportunities for exchange.

    “As diffusion time increases, water molecules probe larger portions of the tissue environment and encounter more barriers or opportunities for exchange (Le Bihan, 1995; Novikov et al., 2019).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Novikov et al., 2019

  • Brain diffusion MRI must be interpreted simultaneously through physics, biology, image contrast, and inverse problem theory.

    “Brain diffusion MRI must, therefore, be interpreted simultaneously through physics, biology, image contrast, and inverse problem theory, making it a rich and powerful imaging modality (Jelescu & Budde, 2017; Le Bihan, 1995; Novikov et al., 2019).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Novikov et al., 2019

  • Diffusion MRI can provide a mesoscopic assay of tissue geometry, provided that model complexity is matched to the acquisition protocol and that the resulting parameters are interpreted as model-dependent estimates rather than direct histological measurements.

    “These observations reinforce the broader view that diffusion MRI can provide a mesoscopic assay of tissue geometry, provided that model complexity is matched to the acquisition protocol and that the resulting parameters are interpreted as model-dependent estimates rather than direct histological measurements (Jelescu & Budde, 2017; Jelescu et al., 2016; Novikov et al., 2019).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Novikov et al., 2019

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Authors
Novikov, D. S., Fieremans, E., Jespersen, S. N., & Kiselev, V. G.
Affiliations
  • NYU Langone Health (US)
  • Aarhus University (DK)
  • University of Freiburg (DE)
Corresponding author
Novikov, Dmitry S.
ORCID
Venue
NMR in Biomedicine
Publisher
Wiley
Published
2018-10-15
Volume
32
Issue
4
Pages
e3998-e3998
ISSN
  • 0952-3480 (ISSN-L)
  • 1099-1492
DOI
10.1002/nbm.3998
PMC
PMC6481929
OpenAlex
W2581687280
Cited by
581
References
13
Citations by year
2026: 55 · 2025: 81 · 2024: 76 · 2023: 64 · 2022: 66 · 2021: 78 · 2020: 68 · 2019: 48 · 2018: 27 · 2017: 17 · 2013: 1
FWCI
8.62
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • NMR in Biomedicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • National Institute of Neurological Disorders and Stroke of the NIH (R01NS088040)
  • Danish Ministry of Science, Technology and Innovations University Investment (0601-01354B)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords
brain microstructure, diffusion MRI, diffusion models, coarse-graining, structural disorder, parameter estimation, degeneracy, mesoscopic transport, disordered systems
MeSH terms
Algorithms, Brain, Humans, Models, Theoretical, Neurons, Anisotropy, Diffusion Magnetic Resonance Imaging

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