Evidence map›Paper›PMID 41863714›Full record

ArticleMedical & biological engineering & computing2026

Uncertainty quantification of conduction velocity in models of cardiac spread of activation.

Anna Busatto, Lindsay C R Tanner, Jake A Bergquist, Gernot Plank, Karli Gillette, Akil Narayan, Rob S MacLeod

Abstract read
PubMed Publisher
In one paragraph

Article in Medical & biological engineering & computing, 2026. 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
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.

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

7 authors.

Anna BusattoScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA. anna.busatto@utah.edu.ORCID http://orcid.org/0000-0002-3577-460X
Lindsay C R TannerScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA.ORCID http://orcid.org/0000-0002-2688-7688
Jake A BergquistScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA.ORCID http://orcid.org/0000-0002-4586-6911
Gernot PlankDivision of Biophysics and Medical Physics, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.ORCID http://orcid.org/0000-0002-7380-6908
Karli GilletteScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA.ORCID http://orcid.org/0000-0002-0420-5375
Akil NarayanScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA.
Rob S MacLeodScientific Computing and Imaging Institute, University of Utah, 72 S Central Campus Dr, Salt Lake City, UT, 84112, USA.ORCID http://orcid.org/0000-0002-0000-0356

Funding

TRAINING IN CARDIOVASCULAR RESEARCHT32HL007576 · NHLBI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Stavros George Drakos, Robin M Shaw · 1985 to 2026
$10.6M
TRD - VisualizationP41GM103545 · NIGMS · UNIVERSITY OF UTAH · PI JURRUS, ELIZABETH · 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
Austrian Science Fund ESP 592Foundation for the National Institutes of Health U24EB029012NHLBI NIH HHS T32 HL007576NIGMS NIH HHS P41 GM103545NIGMS NIH HHS R24 GM136986
6 · The paper itself

Abstract

This study quantified the effect of conduction velocity (CV) variability on cardiac electrical activation patterns, a key factor for cardiac digital twins. We examined how myocardial and endocardial longitudinal, transverse, and sheet CVs influence ventricular activation across multiple pacing sites. Three porcine biventricular heart models, each including a fast-conducting endocardial layer, were used to simulate electrical activation with an eikonal approach. Uncertainty quantification with polynomial chaos expansion systematically varied six CV parameters within physiological ranges. In total, 1,868 simulations from eight ventricular pacing sites were analyzed for activation time, variability, and global sensitivities. Myocardial longitudinal CV showed the greatest influence on activation timing (global sensitivity up to 0.98). Endocardial-layer longitudinal CV was similarly important for endocardial stimuli, while transverse and sheet CVs had minimal effects. Activation-time variability reached 15 ms, increasing with distance from the pacing origin. Longitudinal CVs, particularly myocardial and endocardial-layer, dominate ventricular activation dynamics and should be prioritized when personalizing cardiac digital twins. Accounting for CV uncertainty is essential for accurate prediction and therapy optimization.

Indexed as

HeartHeart Conduction SystemModels, CardiovascularAnimalsComputer SimulationEndocardiumSwineUncertaintyBiological simulationsCardiac digital twinCardiac electrophysiologyConduction velocityUncertainty quantification

Identifiers

What OpenQuestion holds

Textmetadata
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.