Evidence map›Paper›PMID 25148771›Full record

ArticleProgress in biophysics and molecular biology2014

Methodology for image-based reconstruction of ventricular geometry for patient-specific modeling of cardiac electrophysiology.

A Prakosa, P Malamas, S Zhang, F Pashakhanloo, H Arevalo, D A Herzka, A Lardo, H Halperin, E McVeigh, N Trayanova and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Progress in biophysics and molecular biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Trial
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  3. Observational
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  9. Review
  10. Article
  11. 4D cardiac electromechanical activation imaging.Computers in biology and medicine · 2019
    Article
  12. Article
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  14. Article
  15. Article
  16. Article
  17. Review
  18. A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction.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 · 2016
    Article
  19. Article
  20. 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

11 authors.

A PrakosaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
P MalamasInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
S ZhangDepartment of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
F PashakhanlooDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
H ArevaloDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.
D A HerzkaSchool of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
A LardoDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
H HalperinDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
E McVeighDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
N TrayanovaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA. Electronic address: ntrayanova@jhu.edu.
F VadakkumpadanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.

Funding

Improved Targeting and Assessment of Electrophysiology InterventionR01HL094610 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI HALPERIN, HENRY R · 2009 to 2018
$15.5M
Virtual Electrophysiology LaboratoryDP1HL123271 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2013 to 2017
$4.0M
Resynchronizing the Failing Heart: Insights from a Multiscale Cardiac ModelR01HL103428 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2011 to 2014
$2.3M
NCCDPHP CDC HHS DP1HL123271NHLBI NIH HHS DP1 HL123271NHLBI NIH HHS R01 HL094610NHLBI NIH HHS R01 HL103428NHLBI NIH HHS R01-HL103428
6 · The paper itself

Abstract

Patient-specific modeling of ventricular electrophysiology requires an interpolated reconstruction of the 3-dimensional (3D) geometry of the patient ventricles from the low-resolution (Lo-res) clinical images. The goal of this study was to implement a processing pipeline for obtaining the interpolated reconstruction, and thoroughly evaluate the efficacy of this pipeline in comparison with alternative methods. The pipeline implemented here involves contouring the epi- and endocardial boundaries in Lo-res images, interpolating the contours using the variational implicit functions method, and merging the interpolation results to obtain the ventricular reconstruction. Five alternative interpolation methods, namely linear, cubic spline, spherical harmonics, cylindrical harmonics, and shape-based interpolation were implemented for comparison. In the thorough evaluation of the processing pipeline, Hi-res magnetic resonance (MR), computed tomography (CT), and diffusion tensor (DT) MR images from numerous hearts were used. Reconstructions obtained from the Hi-res images were compared with the reconstructions computed by each of the interpolation methods from a sparse sample of the Hi-res contours, which mimicked Lo-res clinical images. Qualitative and quantitative comparison of these ventricular geometry reconstructions showed that the variational implicit functions approach performed better than others. Additionally, the outcomes of electrophysiological simulations (sinus rhythm activation maps and pseudo-ECGs) conducted using models based on the various reconstructions were compared. These electrophysiological simulations demonstrated that our implementation of the variational implicit functions-based method had the best accuracy.

Indexed as

Anatomic LandmarksAnimalsBody Surface Potential MappingDogsHeart Conduction SystemHeart VentriclesHumansImage Interpretation, Computer-AssistedImaging, Three-DimensionalMultimodal ImagingPatient-Specific ModelingSwineCardiac electrophysiologyCardiac ventricular geometry reconstructionInterpolationValidationVariational implicit functions

Identifiers

PMID25148771
PMCPMC4253866

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.