Evidence map›Paper›PMID 40846508›Full record

ArticleThe Journal of physiology2026

Uncertainty quantification via polynomial chaos expansion of myocardial fibre orientation and cardiac activation patterns.

Lindsay C R Tanner, Anna Busatto, Jake A Bergquist, Wilson W Good, Brian Zenger, Gernot Plank, Akil Narayan, Karli Gillette, Rob S MacLeod

Abstract read
In one paragraph

Article in The Journal of physiology, 2026. 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
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.

  1. Article
  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.

Lindsay C R TannerScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-2688-7688
Anna BusattoScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-3577-460X
Jake A BergquistScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-4586-6911
Wilson W GoodScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-0111-9076
Brian ZengerWashington University School of Medicine, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-0039-9184
Gernot PlankDivision of Biophysics and Medical Physics, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.ORCID https://orcid.org/0000-0002-7380-6908
Akil NarayanScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-5914-4207
Karli GilletteScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-0420-5375
Rob S MacLeodScientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA.ORCID https://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 JOHNSON, CHRISTOPHER R., MACLEOD, ROB S. · 2012 to 2019
$9.7M
Integration of Uncertainty Quantification with SCIRun Bioelectric Field Simulation PipelineU24EB029012 · NIBIB · UNIVERSITY OF UTAH · PI MACLEOD, ROB S. · 2019 to 2021
$1.1M
NHLBI NIH HHS T32 HL007576NIGMS NIH HHS P41 GM103545NIH | National Institute of Biomedical Innovation (NIBIO) U24EB029012Nora Eccles Harrison Foundation for Cardiovascular ResearchNSF | National Science Foundation Graduate Research Fellowship Program (GRFP)
6 · The paper itself

Abstract

Predictive models and computational simulations of cardiac electrophysiology depend on precise anatomical representations, including the local myocardial fibre structure. However, obtaining patient-specific fibre information is challenging. In addition, the influence of physiological variability in fibre orientation on cardiac activation simulations is poorly understood. We implemented rule-based algorithms to generate fibres and robust uncertainty quantification methods to determine model output variability with respect to ventricular activation sequences. We used polynomial chaos, which reduces computational demands by using an emulator to approximate the underlying forward model. Our study examined activation sequences in response to nine stimuli and five metrics quantifying essential features of the activation sequence. The results indicated that the primary fibre orientation impacts the overall spread of activation, which could impact more complex patterns of activation; however, there is minimal impact on the location of discrete activation features, such as breakthrough sites. For free wall stimuli, the standard deviation (STD) was highest near the stimulus site, diminishing with distance. Apical stimuli showed complementary STD patterns, with epicardial pacing maximizing STD in the right basal area and endocardial pacing in the left. Ventricular junction stimuli exhibited symmetrical STD patterns, low near the stimulus but increasing sharply towards the apex, peaking on the left in the apical region. Furthermore, variability in the imbrication or helix angle did not impact the activation sequences. We conclude that in many relevant modelling contexts, the variability in myocardial fibre orientation can play an important role in the resulting activation sequences and should be accounted for. KEY POINTS: The primary fibre orientation has modest impact on activation duration and location of most discrete activation features for ectopic stimuli, but introduces variability in activation sequence. For free wall stimuli, the standard deviation (STD) was highest on the stimulated surface, indicating that deviations are largest in early activation and diminish as activation reaches remote heart regions. For apical stimuli, activation patterns were insensitive to fibre orientation variations, but the STD had complementary maxima, strongly dependent on pacing surface. Epicardial pacing produced largest STD in right basal area while endocardial pacing affected left basal area, indicating strong dependence on fibre structure. For stimuli at both anterior and posterior ventricular junctions, STD patterns were symmetrical, with low values near stimulus and sharp increases towards apex, peaking in left apical region. The helical fibre orientation showed no relevant fluctuations in activation sequence.

Indexed as

HeartModels, CardiovascularAction PotentialsAnimalsComputer SimulationHumansUncertaintybiological simulationscardiac electrophysiologymyocardial fibresuncertainty quantification

Identifiers

PMID40846508
PMCPMC13327771

What OpenQuestion holds

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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.