Evidence map›Paper›PMID 26633913›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2015

Image-based Reconstruction of 3D Myocardial Infarct Geometry for Patient Specific Applications.

Eranga Ukwatta, Martin Rajchl, James White, Farhad Pashakhanloo, Daniel A Herzka, Elliot McVeigh, Albert C Lardo, Natalia Trayanova, Fijoy Vadakkumpadan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2015. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

9 authors.

Eranga UkwattaInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States ; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Martin RajchlDepartment of Computing, Imperial College London, London, United Kingdom.
James WhiteStephenson Cardiovascular MR Centre, University of Calgary, Calgary, AB, Canada.
Farhad PashakhanlooInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States ; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Daniel A HerzkaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Elliot McVeighDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Albert C LardoDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States ; School of Medicine, Johns Hopkins University, Baltimore, MD, United States.
Natalia TrayanovaInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States ; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States ; School of Medicine, Johns Hopkins University, Baltimore, MD, United States.
Fijoy VadakkumpadanInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States ; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.

Funding

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
LV Structural Predictors of Sudden Cardiac DeathR01HL103812 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI WU, KATHERINE C · 2010 to 2013
$1.4M
NHLBI NIH HHS DP1 HL123271NHLBI NIH HHS R01 HL103428NHLBI NIH HHS R01 HL103812
6 · The paper itself

Abstract

Accurate reconstruction of the three-dimensional (3D) geometry of a myocardial infarct from two-dimensional (2D) multi-slice image sequences has important applications in the clinical evaluation and treatment of patients with ischemic cardiomyopathy. However, this reconstruction is challenging because the resolution of common clinical scans used to acquire infarct structure, such as short-axis, late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) images, is low, especially in the out-of-plane direction. In this study, we propose a novel technique to reconstruct the 3D infarct geometry from low resolution clinical images. Our methodology is based on a function called logarithm of odds (LogOdds), which allows the broader class of linear combinations in the LogOdds vector space as opposed to being limited to only a convex combination in the binary label space. To assess the efficacy of the method, we used high-resolution LGE-CMR images of 36 human hearts

Indexed as

Image-based ReconstructionInterpolationLogarithm of OddsMyocardial Infarct

Identifiers

PMID26633913
PMCPMC4664077

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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.