Evidence map›Paper›PMID 34782651›Full record

ArticleScientific reports2021

Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes.

Syed Salman Shahid, Robert D Johnston, Celine Smekens, Christian Kerskens, Robert Gaul, Brooke Tornifoglio, Alan J Stone, Caitríona Lally

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Syed Salman ShahidDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
Robert D JohnstonTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Celine SmekensTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Christian KerskensTrinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
Robert GaulTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Brooke TornifoglioTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Alan J StoneTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Caitríona LallyTrinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland. lallyca@tcd.ie.

Funding

European Research Council Grant Agreement No. 637674
6 · The paper itself

Abstract

The purpose of this study was to characterize the alterations in microstructural organization of arterial tissue using higher-order diffusion magnetic resonance schemes. Three porcine carotid artery models namely; native, collagenase treated and decellularized, were used to estimate the contribution of collagen and smooth muscle cells (SMC) on diffusion signal attenuation using gaussian and non-gaussian schemes. The samples were imaged in a 7 T preclinical scanner. High spatial and angular resolution diffusion weighted images (DWIs) were acquired using two multi-shell (max b-value = 3000 s/mm

Indexed as

Image Interpretation, Computer-AssistedAlgorithmsAnimalsArteriesBiomarkersCarotid ArteriesData AnalysisDiffusion Magnetic Resonance ImagingImmunohistochemistryModels, TheoreticalSwineBiomarkers

Identifiers

PMID34782651
PMCPMC8593063

What OpenQuestion holds

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LicenceCC BY
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.