Evidence map›Paper›PMID 32123688›Full record

ArticleComputing in cardiology2019

Optimizing the Reconstruction of Cardiac Potentials Using a Novel High Resolution Pericardiac Cage.

Jake A Bergquist, Wilson W Good, Brian Zenger, Jess D Tate, Rob S MacLeod

Open access · greenAbstract read
In one paragraph

Article in Computing in cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. The electrocardiographic forward problem: A benchmark study.Computers in biology and medicine · 2021
    Article
  4. Article
  5. Article
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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

5 authors at 1 institution in 1 country.

Jake A BergquistScientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Wilson W GoodScientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Brian ZengerScientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Jess D TateScientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
Rob S MacLeodScientific Computing and Imaging Institute, University of Utah, SLC, UT, USA.
University of Utah · US

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI JOHNSON, CHRISTOPHER R. · 2012 to 2019
$9.7M
Center for Integrative Biomedical Computing Legacy TransitionR24GM136986 · NIGMS · UNIVERSITY OF UTAH · PI JOHNSON, CHRISTOPHER R., MACLEOD, ROB S. · 2020 to 2022
$1.6M
Novel Characterization and Detection Techniques for Acute Myocardial IschemiaF30HL149327 · NHLBI · UNIVERSITY OF UTAH · PI ZENGER, BRIAN · 2020 to 2022
$117k
NHLBI NIH HHS F30 HL149327NIGMS NIH HHS P41 GM103545NIGMS NIH HHS R24 GM136986
6 · The paper itself

Abstract

introductionExperimental preparations in which cardiac and torso recordings are made simultaneously typically do not have uniform sampling around the entire surface of the heart. To fill in the resulting gaps in coverage, signals captured from the sampled region are extended to the unsampled region of the heart before being utilized in computational models. The resulting errors have never been evaluated systematically. We explored this relationship using a novel experimental preparation, and compared the resulting measurements against a set of interpolation and optimization methods.

methodsMeasurements came from a modified Langenorff preparation in which we placed a rigid, heart shaped pericardiac cage electrode array around an isolated canine heart within an electrolytic torso-tank. Using the measured cage potentials we optimized a reconstruction from the subset of the cage below the base of the heart (ventricular) to the subset above it (atrial). This optimization minimized the difference between the reconstructed and measured signals. We then compared the reconstruction to a spatial Laplacian interpolation of the same potentials.

resultsQualitative results show a high degree of agreement between optimized reconstructed potentials and measured potentials whereas the Laplacian interpolation resulted in poorer reconstructions in most cases. Calculated mean and maximum error were lower for optimization based approaches than spatial Laplacian interpolation. DISCUSSION: In this study we aimed to utilize novel pericardiac cage recordings to investigate interpolation strategies from sampled signals to unsampled signals. We demonstrate that the sampled ventricular subset of signals is sufficient to reconstruct the atrial subset but that Laplacian interpolation does not achieve the level of accuracy that is possible.

Identifiers

PMID32123688
PMCPMC7051051
OpenAlexW2999944386

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.