Evidence map›Paper›PMID 32190706›Full record

ArticleComputing in cardiology2019

Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial Ischemia.

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

Abstract 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. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

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

Funding

TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI MACLEOD, ROB S. · 2012 to 2019
$9.7M
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 GM103545
6 · The paper itself

Abstract

introductionMyocardial ischemia is an early clinical indicator of several underlying cardiac pathologies, including coronary artery disease, Takatsobu cardiomyopathy, and coronary artery dissection. Significant progress has been made in computing body-surface potentials from cardiac sources by solving the forward problem of electrocardiography. However, the lack of in vivo studies to validate such computations from ischemic sources has limited the translational potential of such models.

methodsTo resolve this need, we have developed a large-animal experimental model that includes simultaneous recordings within the myocardium, on the epicardial surface, and on the torso surface during episodes of acute, controlled ischemia. Following each experiment, magnetic resonance images were obtained of the anatomy and electrode locations to create a subject-specific model for each animal. From the electrical recordings of the heart, we identified ischemic sources and used the finite element method to solve a static bidomain equation on a geometric model to compute torso surface potentials.

resultsAcross 33 individual heartbeats, the forward computed torso potentials showed only moderate agreement in both pattern and amplitude with the measured values on the torso surface. Qualitative analysis showed a more encouraging pattern of elevations and depressions shared by computed and measured torso potentials. Pearson's correlation coefficient, root mean squared error, and absolute error varied significantly by heartbeat (0.1642 ± 0.223, 0.10 ± 0.03mV, and 0.08 ± 0.03mV, respectively). DISCUSSION: We speculate several sources of error in our computation including noise within torso surface recordings, registration of electrode and anatomical locations, assuming a homogeneous torso conductivities, and imposing a uniform "transition zone" between ischemic and non-ischemic tissues. Further studies will focus on characterizing these sources of error and understanding how they effect the study results.

Identifiers

PMID32190706
PMCPMC7079820
OpenAlexW3000469684

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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.