Evidence map›Paper›PMID 26705485›Full record

ArticleEuropean heart journal. Cardiovascular Imaging2016

Perfusion dyssynchrony analysis.

Amedeo Chiribiri, Adriana D M Villa, Eva Sammut, Marcel Breeuwer, Eike Nagel

Open access · hybridAbstract readComparative Study
In one paragraph

Article in European heart journal. Cardiovascular Imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Deep-Learning-Based Preprocessing for Quantitative Myocardial Perfusion MRI.Journal of magnetic resonance imaging : JMRI · 2020
    Article
  4. The role of nuclear medicine in assessments of cardiac dyssynchrony.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2018
    Article
  5. 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 at 3 institutions in 3 countries.

Amedeo ChiribiriDivision of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK amedeo.chiribiri@kcl.ac.uk.
Adriana D M VillaDivision of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.
Eva SammutDivision of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.
Marcel BreeuwerPhilips Healthcare, Imaging Systems-MR Eindhoven, The Netherlands.
Eike NagelDivision of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.
King's College London · GBSt Thomas' Hospital · GBPhilips (Netherlands) · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsWe sought to describe perfusion dyssynchrony analysis specifically to exploit the high temporal resolution of stress perfusion CMR. This novel approach detects differences in the temporal distribution of the wash-in of contrast agent across the left ventricular wall. METHODS AND

resultsNinety-eight patients with suspected coronary artery disease (CAD) were retrospectively identified. All patients had undergone perfusion CMR at 3T and invasive angiography with fractional flow reserve (FFR) of lesions visually judged >50% stenosis. Stress images were analysed using four different perfusion dyssynchrony indices: the variance and coefficient of variation of the time to maximum signal upslope (V-TTMU and C-TTMU) and the variance and coefficient of variation of the time to peak myocardial signal enhancement (V-TTP and C-TTP). Patients were classified according to the number of vessels with haemodynamically significant CAD indicated by FFR <0.8. All indices of perfusion dyssynchrony were capable of identifying the presence of significant CAD. C-TTP >10% identified CAD with sensitivity 0.889, specificity 0.857 (P < 0.0001). All indices correlated with the number of diseased vessels. C-TTP >12% identified multi-vessel disease with sensitivity 0.806, specificity 0.657 (P < 0.0001). C-TTP was also the dyssynchrony index with the best inter- and intra-observer reproducibility. Perfusion dyssynchrony indices showed weak correlation with other invasive and non-invasive measurements of the severity of ischaemia, including FFR, visual ischaemic burden, and MPR.

conclusionThese findings suggest that perfusion dyssynchrony analysis is a robust novel approach to the analysis of first-pass perfusion and has the potential to add complementary information to aid assessment of CAD.

Indexed as

AgedAge FactorsAnalysis of VarianceCohort StudiesConfidence IntervalsCoronary AngiographyCoronary StenosisFemaleFractional Flow Reserve, MyocardialHumansMagnetic Resonance AngiographyMagnetic Resonance Imaging, CineMaleMiddle AgedMyocardial Perfusion ImagingObserver Variationadenosinedyssynchrony analysisgadoliniumperfusion

Identifiers

PMID26705485
PMCPMC5155575
OpenAlexW2213053803

What OpenQuestion holds

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LicenceCC BY
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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.