Evidence map›Paper›PMID 29541576›Full record

ArticleNeuroImage. Clinical2018

A comparison of functional and tractography based networks in cerebral small vessel disease.

Andrew J Lawrence, Daniel J Tozer, Emmanuel A Stamatakis, Hugh S Markus

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  12. Advanced MRI in cerebral small vessel disease.International journal of stroke : official journal of the International Stroke Society · 2023
    Review
  13. Article
  14. Article
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  16. Longitudinal Relation Between Structural Network Efficiency, Cognition, and Gait in Cerebral Small Vessel Disease.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022
    Article
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  18. Review
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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

4 authors at 1 institution in 1 country.

Andrew J LawrenceStroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
Daniel J TozerStroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. Electronic address: djt54@medschl.cam.ac.uk.
Emmanuel A StamatakisDivision of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. Electronic address: eas46@cam.ac.uk.
Hugh S MarkusStroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. Electronic address: hsm32@medschl.cam.ac.uk.
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: MRI measures of network integrity may be useful disease markers in cerebral small vessel disease (SVD). We compared the sensitivity and reproducibility of MRI derived structural and functional network measures in healthy controls and SVD subjects. Methods: Diffusion tractography and resting state fMRI were used to create connectivity matrices from 26 subjects with symptomatic MRI confirmed lacunar stroke and 19 controls. Matrices were constructed at multiple scales based on a multi-resolution cortical atlas and at multiple thresholds for the matrix density. Network parameters were calculated over the multiple resolutions and thresholds. In addition the reproducibility of structural and functional network parameters was determined in a subset of the subjects (15 SVD, 10 controls) who were scanned twice. Results: Structural networks showed a highly significant loss of network integrity in SVD cases compared to controls, for all network measures. In contrast functional networks showed no difference between SVD and controls. Structural network measures were highly reproducible in both cases and controls, with ICC values consistently over 0.8. In contrast functional network measures showed much poorer reproducibility with ICC values in the range 0.4-0.6 overall, and even lower in SVD cases. Conclusions: Structural networks identify impaired network integrity, and are highly reproducible, in SVD, supporting their use as markers of SVD disease severity. In contrast, functional networks showed low reproducibility, particularly in SVD cases, and were unable to detect differences between SVD cases and controls with this sample size.

Indexed as

Diffusion Tensor ImagingMagnetic Resonance ImagingAgedCerebral Small Vessel DiseasesCorrelation of DataFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedNeural PathwaysNeuropsychological TestsReproducibility of ResultsWhite MatterFunctional connectivityMRINetwork analysisReproducibility diffusion imagingSmall vessel disease

Identifiers

PMID29541576
PMCPMC5849860
OpenAlexW2792141202

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.