Evidence map›Paper›PMID 26528188›Full record

ArticleFrontiers in physiology2015

Accuracy of prediction of infarct-related arrhythmic circuits from image-based models reconstructed from low and high resolution MRI.

Dongdong Deng, Hermenegild Arevalo, Farhad Pashakhanloo, Adityo Prakosa, Hiroshi Ashikaga, Elliot McVeigh, Henry Halperin, Natalia Trayanova

Abstract read
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Article in Frontiers in physiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Article
  2. Article
  3. Patient selection, ventricular tachycardia substrate delineation, and data transfer for stereotactic arrhythmia radioablation: a clinical consensus statement of the European Heart Rhythm Association of the European Society of Cardiology and the Heart Rhythm Society.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Article
  4. Review
  5. Review
  6. Article
  7. Arrhythmogenic vulnerability of re-entrant pathways in post-infarct ventricular tachycardia assessed by advanced computational modelling.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023
    Article
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  10. 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

8 authors.

Dongdong DengDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University Baltimore, MD, USA.
Hermenegild ArevaloDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University Baltimore, MD, USA.
Farhad PashakhanlooDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University Baltimore, MD, USA.
Adityo PrakosaDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University Baltimore, MD, USA.
Hiroshi AshikagaDivision of Cardiology, Department of Medicine, Johns Hopkins Medical Institute Baltimore, MD, USA ; Department of Biomedical Engineering, Johns Hopkins University Baltimore, MD, USA.
Elliot McVeighDepartment of Biomedical Engineering, Johns Hopkins University Baltimore, MD, USA.
Henry HalperinDivision of Cardiology, Department of Medicine, Johns Hopkins Medical Institute Baltimore, MD, USA.
Natalia TrayanovaDepartment of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of optimal ablation sites in hearts with infarct-related ventricular tachycardia (VT) remains difficult to achieve with the current catheter-based mapping techniques. Limitations arise from the ambiguities in determining the reentrant pathways location(s). The goal of this study was to develop experimentally validated, individualized computer models of infarcted swine hearts, reconstructed from high-resolution ex-vivo MRI and to examine the accuracy of the reentrant circuit location prediction when models of the same hearts are instead reconstructed from low clinical-resolution MRI scans. To achieve this goal, we utilized retrospective data obtained from four pigs ~10 weeks post infarction that underwent VT induction via programmed stimulation and epicardial activation mapping via a multielectrode epicardial sock. After the experiment, high-resolution ex-vivo MRI with late gadolinium enhancement was acquired. The Hi-res images were downsampled into two lower resolutions (Med-res and Low-res) in order to replicate image quality obtainable in the clinic. The images were segmented and models were reconstructed from the three image stacks for each pig heart. VT induction similar to what was performed in the experiment was simulated. Results of the reconstructions showed that the geometry of the ventricles including the infarct could be accurately obtained from Med-res and Low-res images. Simulation results demonstrated that induced VTs in the Med-res and Low-res models were located close to those in Hi-res models. Importantly, all models, regardless of image resolution, accurately predicted the VT morphology and circuit location induced in the experiment. These results demonstrate that MRI-based computer models of hearts with ischemic cardiomyopathy could provide a unique opportunity to predict and analyze VT resulting for from specific infarct architecture, and thus may assist in clinical decisions to identify and ablate the reentrant circuit(s).

Indexed as

arrhythmiacomputational modelingMRI reconstructionmyocardial infarctionreentry

Identifiers

PMID26528188
PMCPMC4602125

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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.