Evidence map›Paper›PMID 32123687›Full record

ArticleComputing in cardiology2019

Validation of Intramural Wavefront Reconstruction and Estimation of 3D Conduction Velocity.

Wilson W Good, Karli K Gillette, Jake A Bergquist, Brian Zenger, Jess Tate, Lindsay C Rupp, Devan Anderson, Gernot Plank, Rob S MacLeod

Open access · greenAbstract read
PubMed Full text at PMC Publisher
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 71% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

9 authors at 2 institutions in 2 countries.

Wilson W GoodScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Karli K GilletteInstitute of Biophysics, Medical University of Graz, Graz, Austria.
Jake A BergquistScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Brian ZengerScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Jess TateScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Lindsay C RuppScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Devan AndersonScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
Gernot PlankInstitute of Biophysics, Medical University of Graz, Graz, Austria.
Rob S MacLeodScientific Computing and Imaging Institute, Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
University of Utah · USMedical University of Graz · AT

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI MACLEOD, ROB S. · 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

introductionChanges in conduction velocity are indicative of a wide variety of cardiac abnormalities yet measuring conduction velocity is challenging, especially within the myocardial volume. In this study we investigated a novel technique to reconstruct activation fronts and estimate three-dimensional (3D) conduction velocity (CV) from experimental intramural recordings.

methodsFrom the intermittently sampled electrograms we both reconstruct the activation profile and compute the reciprocal of the gradient of activation times and a series of streamlines that allows for the CV estimation.

resultsThe reconstructed activation times agreed closely with simulated values, with 50% to 70% of the nodes ≤ 1ms of absolute error. We found close agreement between the CVs calculated using reconstructed versus simulated activation times. Across the reconstructed stimulation sites we saw that the reconstructed CV was on average 3.8% different than the ground truth CV. DISCUSSION: This study used simulated datasets to validate our methods for reconstructing 3D activation fronts and estimating conduction velocities. Our results indicate that our method allows accurate reconstructions from sparse measurements, thus allowing us to examine changes in activation induced by experimental interventions such as acute ischemia, ectopic pacing, or drugs.

Identifiers

PMID32123687
PMCPMC7051050
OpenAlexW3000703475

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.