Evidence map›Paper›PMID 28943412›Full record

ArticleNeuroImage2017

Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments.

Dan Benjamini, Peter J Basser

Abstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
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  5. Article
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  7. Article
  8. Joint estimation of compartment-specific TMagnetic resonance in medicine · 2025
    Article
  9. Article
  10. MRI-based virtual pathology of the prostate.Magma (New York, N.Y.) · 2024
    Review
  11. Article
  12. Article
  13. bioRxiv : the preprint server for biology · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Nonparametric 5D D-RJournal of magnetic resonance (San Diego, Calif. : 1997) · 2022
    Article
  18. Review
  19. Article
  20. Review
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

2 authors.

Dan BenjaminiSection on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: dan.benjamini@nih.gov.
Peter J BasserSection on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA.

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
Intramural NIH HHS Z99 HD999999Intramural NIH HHS ZIA HD000266
6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) provides a powerful set of tools with which to investigate biological tissues noninvasively and in vivo. Tissues are heterogeneous in nature; an imaging voxel contains an ensemble of different cells and extracellular matrix components. A long-standing challenge has been to infer the content of and interactions among these microscopic tissue components within a macroscopic imaging voxel. Spatially resolved multidimensional relaxation-diffusion correlation (REDCO) spectroscopy holds the potential to deliver such microdynamic information. However, to date, vast data requirements have mostly relegated these type of measurements to nuclear magnetic resonance applications and prevented them from being widely and successfully used in conjunction with imaging. By using a novel data acquisition and processing strategy in this study, spatially resolved REDCO could be performed in reasonable scanning times with excellent prospects for clinical applications. This new MR imaging framework-which we term "magnetic resonance microdynamic imaging (MRMI)"-permits the simultaneous noninvasive and model-free quantification of multiple subcellular, cellular, and interstitial tissue microenvironments within a voxel. MRMI is demonstrated with a fixed spinal cord specimen, enabling the quantification of microscopic tissue components with unprecedented specificity. Tissue components, such as axons, neuronal and glial soma, and myelin were identified on the basis of their multispectral signature within individual imaging voxels. These tissue elements could then be composed into images and be correlated with immunohistochemistry findings. MRMI provides novel image contrasts of tissue components and a new family of microdynamic biomarkers that could lead to new diagnostic imaging approaches to probe biological tissue alterations accompanied by pathological or developmental changes.

Indexed as

Cellular MicroenvironmentAnimalsFerretsImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMaleSpinal CordDiffusionGliaMADCOMicrodynamicModel-freeMRIRelaxationRelaxometrySpectroscopy

Identifiers

PMID28943412
PMCPMC5716914

What OpenQuestion holds

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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.