Evidence map›Paper›PMID 28838961›Full record

ArticleCirculation. Cardiovascular imaging2017

Cardiovascular Magnetic Resonance to Predict Appropriate Implantable Cardioverter Defibrillator Therapy in Ischemic and Nonischemic Cardiomyopathy Patients Using Late Gadolinium Enhancement Border Zone: Comparison of Four Analysis Methods.

Robert Jablonowski, Uzma Chaudhry, Jesper van der Pals, Henrik Engblom, Håkan Arheden, Einar Heiberg, Katherine C Wu, Rasmus Borgquist, Marcus Carlsson

Open access · bronzeAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Circulation. Cardiovascular imaging, 2017. 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
3.9field-weighted citation impact, top 5% 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, 51 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Prognostic value of late gadolinium enhancement cardiac MRI for ICD therapy in non-ischaemic cardiomyopathy : A 5-year cohort study.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2025
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  11. Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2022
    Article
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  20. The Role of AI in Characterizing the DCM Phenotype.Frontiers in cardiovascular medicine · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Robert JablonowskiFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Uzma ChaudhryFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Jesper van der PalsFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Henrik EngblomFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Håkan ArhedenFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Einar HeibergFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Katherine C WuFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Rasmus BorgquistFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.).
Marcus CarlssonFrom the Clinical Physiology (R.J., H.E., H.A., E.H., M.C.) and Cardiology (U.C., J.v.d.P., R.B.), Department of Clinical Sciences, Lund University, Lund University Hospital, Sweden; Department of Biomedical Engineering and Centre for Mathematical Sciences, Faculty of Engineering, Lund University, Sweden (E.H.); and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W.). Marcus.Carlsson@med.lu.se.
Statistics Sweden · SELund University · SE

Funding

LV Structural Predictors of Sudden Cardiac DeathR01HL103812 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI WU, KATHERINE C · 2010 to 2013
$1.4M
NHLBI NIH HHS R01 HL103812
6 · The paper itself

Abstract

backgroundLate gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms. METHODS AND

resultsICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively;

conclusionsAppropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures.

Indexed as

Decision Support TechniquesDefibrillators, ImplantableMagnetic Resonance Imaging, CinePatient SelectionAgedAlgorithmsArrhythmias, CardiacCardiomyopathiesContrast MediaDisease-Free SurvivalElectric CountershockFemaleGadolinium DTPAHeterocyclic CompoundsHumansImage Processing, Computer-AssistedContrast Mediagadolinium 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetateGadolinium DTPAHeterocyclic CompoundsOrganometallic Compoundscardiac magnetic resonance imagingimplanted cardioverter defibrillatorischemic cardiomyopathylate gadolinium enhancementnonischemic cardiomyopathy

Identifiers

PMID28838961
PMCPMC5580266
OpenAlexW2749401531

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.