Evidence map›Paper›PMID 36404493›Full record

ArticleMagnetic resonance in medicine2023

Measuring water exchange on a preclinical MRI system using filter exchange and diffusion time dependent kurtosis imaging.

Chenyang Li, Els Fieremans, Dmitry S Novikov, Yulin Ge, Jiangyang Zhang

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

  1. Article
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  9. Article
  10. Imaging neuroscience (Cambridge, Mass.) · 2025
    Article
  11. bioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Mean Kärger Model Water Exchange Rate in Brain.Imaging neuroscience (Cambridge, Mass.) · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors.

Chenyang LiDepartment of Radiology, Center for Biomedical Imaging, New York, New York, USA.
Els FieremansDepartment of Radiology, Center for Biomedical Imaging, New York, New York, USA.ORCID 0000-0002-1384-8591
Dmitry S NovikovDepartment of Radiology, Center for Biomedical Imaging, New York, New York, USA.ORCID 0000-0002-4213-3050
Yulin GeDepartment of Radiology, Center for Biomedical Imaging, New York, New York, USA.
Jiangyang ZhangDepartment of Radiology, Center for Biomedical Imaging, New York, New York, USA.ORCID 0000-0003-0740-2662

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ADRIANA HEGUY · 1985 to 2026
$83.1M
Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
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
Imaging Neonatal Hypoxic Ischemic InjuryR01HD074593 · NICHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FRANCES J NORTHINGTON, JIANGYANG ZHANG · 2013 to 2026
$6.8M
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
Quantitative Imaging of Mouse Brain DevelopmentR01NS102904 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ZHANG, JIANGYANG · 2018 to 2022
$3.1M
7T Small Animal MRI Scanner Replacement for Translational Imaging ResourceS10OD018337 · OD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BOADA, FERNANDO E · 2014 to 2014
$2.0M
NCI NIH HHS P30 CA016087NIA NIH HHS P30 AG066512NIBIB NIH HHS P41 EB017183NICHD NIH HHS R01 HD074593NIH HHS S10 OD018337NINDS NIH HHS R01 NS088040NINDS NIH HHS R01 NS102904
6 · The paper itself

Abstract

purposeFilter exchange imaging (FEXI) and diffusion time (t)-dependent diffusion kurtosis imaging (DKI(t)) are both sensitive to water exchange between tissue compartments. The restrictive effects of tissue microstructure, however, introduce bias to the exchange rate obtained by these two methods, as their interpretation conventionally rely on the Kärger model of barrier limited exchange between Gaussian compartments. Here, we investigated whether FEXI and DKI(t) can provide comparable exchange rates in ex vivo mouse brains. THEORY AND

methodsFEXI and DKI(t) data were acquired from ex vivo mouse brains on a preclinical MRI system. Phase cycling and negative slice prewinder gradients were used to minimize the interferences from imaging gradients.

resultsIn the corpus callosum, apparent exchange rate (AXR) from FEXI correlated with the exchange rate (the inverse of exchange time, 1/τ

conclusionThe results suggest that FEXI and DKI(t) are sensitive to the same exchange processes in white matter when separated from restrictive effects of microstructure. The complex microstructure in gray matter, with potential exchange among multiple compartments and confounding effects of microstructure, still pose a challenge for FEXI and DKI(t).

Indexed as

WaterWhite MatterAnimalsBrainDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingGray MatterMagnetic Resonance ImagingMiceWaterdiffusiondiffusion kurtosis imagingexchangefilter exchange imagingmagnetic resonance imagingtranslational research

Identifiers

PMID36404493
PMCPMC9892228

What OpenQuestion holds

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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.