Evidence map›Paper›PMID 28452522›Full record

ArticlePhysical review letters2017

Imaging Local Diffusive Dynamics Using Diffusion Exchange Spectroscopy MRI.

Dan Benjamini, Michal E Komlosh, Peter J Basser

Open access · greenAbstract read
In one paragraph

Article in Physical review letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
13.2field-weighted citation impact, top 2% 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

32 citing papers in PubMed, 47 citations in OpenAlex.

  1. Localization-driven exchange contrast in diffusion exchange spectroscopy.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2026
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  18. Multidimensional correlation MRI.NMR in biomedicine · 2020
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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

3 authors at 2 institutions in 1 country.

Dan BenjaminiSection on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, Maryland 20892, USA.
Michal E KomloshSection on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, Maryland 20892, USA.
Peter J BasserSection on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, Maryland 20892, USA.
National Institutes of Health · USCenter for Neuroscience and Regenerative Medicine · US

Funding

Imaging Water Diffusion in the Brain and in Other Soft TissuesZIAHD000266 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI BASSER, PETER J. · 2009 to 2017
$3.3M
Magnetic Resonance Diffusion Tensor Imaging (DT-MRI) of the BrainZ01HD000266 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI BASSER, PETER J. · 1998 to 2008
$512k
Intramural NIH HHS Z01 HD000266Intramural NIH HHS ZIA HD000266
6 · The paper itself

Abstract

The movement of water between microenvironments presents a central challenge in the physics of soft matter and porous media. Diffusion exchange spectroscopy (DEXSY) is a powerful 2D nuclear magnetic resonance method for measuring such exchange, yet it is rarely used because of its long scan time requirements. Moreover, it has never been combined with magnetic resonance imaging (MRI). Using probability theory, we vastly reduce the required data, making DEXSY MRI feasible for the first time. Experiments are performed on a composite nerve tissue phantom with restricted and free water-exchanging compartments.

Indexed as

DiffusionMagnetic Resonance ImagingMagnetic Resonance SpectroscopyNeuronsPhantoms, ImagingPorosityWaterWater

Identifiers

PMID28452522
PMCPMC11079612
OpenAlexW2605471729

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.