Evidence map›Paper›PMID 30321478›Full record

ReviewNMR in biomedicine2019

Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation.

Dmitry S Novikov, Els Fieremans, Sune N Jespersen, Valerij G Kiselev

Open access · greenAbstract readReview
In one paragraph

Review in NMR in biomedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 323 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
323citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

323 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

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263 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 3 countries.

Dmitry S NovikovCenter for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY.ORCID 0000-0002-4213-3050
Els FieremansCenter for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY.ORCID 0000-0002-1384-8591
Sune N JespersenCFIN/MINDLab, Department of Clinical Medicine and Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark.ORCID 0000-0003-3146-4329
Valerij G KiselevMedical Physics, Department of Radiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID 0000-0002-5349-5399
New York University · USAarhus University · DKUniversity of Freiburg · DE

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRIR01NS088040 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2014 to 2023
$5.2M
Danish Ministry of Science, Technology and Innovations University Investment 0601-01354BNational Institute of Neurological Disorders and Stroke of the NIH R01NS088040NIBIB NIH HHS P41 EB017183NINDS NIH HHS R01 NS088040
6 · The paper itself

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.

Indexed as

Diffusion Magnetic Resonance ImagingModels, TheoreticalAlgorithmsAnisotropyBrainHumansNeuronsbraincoarse-grainingdiffusionmesoscopic transportmicrostructureMRI

Identifiers

PMID30321478
PMCPMC6481929
OpenAlexW2581687280

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.