Evidence map›Paper›PMID 40897366›Full record

ArticleThe Journal of physiology2025

Computational modelling of the impact of anatomical changes on ECGs in left ventricular hypertrophy.

Mohammadreza Kariman, Karli Gillette, Matthias A F Gsell, Anton J Prassl, Gernot Plank, Christoph M Augustin

Abstract read
In one paragraph

Article in The Journal of physiology, 2025. 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

6 authors.

Mohammadreza KarimanGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
Karli GilletteGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.ORCID 0000-0002-0420-5375
Matthias A F GsellGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.ORCID 0000-0001-7742-8193
Anton J PrasslGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.ORCID 0000-0002-1920-1377
Gernot PlankGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.ORCID 0000-0002-7380-6908
Christoph M AugustinGottfried Schatz Research Center: Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.ORCID 0000-0001-6341-4014

Funding

Mechanistic Relationships Between Fibrosis, Fibrillation, and Stroke: Multi-Scale, Multi-Physics SimulationsR01HL158667 · NHLBI · UNIVERSITY OF WASHINGTON · PI Patrick M Boyle · 2022 to 2026
$3.1M
Austrian Science Fund (FWF) 10.55776/I4652Austrian Science Fund (FWF) 10.55776/I6540Austrian Science Fund (FWF) 10.55776/P37063NHLBI NIH HHS R01 HL158667
6 · The paper itself

Abstract

Left ventricular hypertrophy (LVH) is characterised by an increase in the mass and volume of the left ventricle, typically manifested as ventricular wall thickening and/or dilation. Due to its potential to cause severe, life-threatening complications, ongoing research continues to explore its underlying mechanisms. This study aimed to determine how wall thickening and dilation specifically impact ECG waveforms, isolating these anatomical alterations without considering potential electrophysiological changes associated with LVH - a scenario achievable only through computational modelling. To accomplish this, eccentric and concentric cardiac models - with growth levels from 10% to 100% mass increase - were generated using a kinematic growth, finite element model derived from a healthy control model. Activation sequences were simulated for each model using a pseudo-bidomain reaction-eikonal approach, and 12-lead ECGs were recorded from the hypertrophy models and compared to the control. Results indicated that activation patterns in eccentric hypertrophy models resembled the healthy model, while concentric hypertrophy models displayed substantial deviations. Both types of hypertrophy types led to prolonged QRS durations by up to 21 ms - a 40% increase from baseline - even in the absence of electrical remodelling. Eccentric hypertrophy increased amplitudes in precordial leads, minimally affecting limb leads, while concentric hypertrophy impacted all 12 leads with varied amplitude changes. Leads aVL, V1 and V5/V6 emerged as the most sensitive to anatomical changes. These findings could enhance the accuracy of LVH diagnosis using ECGs, offering a cost-effective strategy to complement clinical evaluation and imaging, ultimately improving LVH detection and management. KEY POINTS: Computational simulations revealed distinct effects of anatomical changes in eccentric and concentric left ventricular hypertrophy on 12-lead ECG signals. Eccentric hypertrophy primarily affected the precordial leads, showing notable voltage amplitude increases across all precordial lead measurements. Concentric hypertrophy affected all 12 leads without a clear pattern of amplitude change, displaying both increases and decreases. Both eccentric and concentric hypertrophy resulted in a consistent prolongation of the QRS complex, showing up to 40% increase from baseline, even in the absence of electrophysiological remodelling. Leads aVL, III, V1 and V5/V6 were identified as the most sensitive to LVH, with computational results aligning well with independent clinical measurements.

Indexed as

Computer SimulationElectroencephalographyHypertrophy, Left VentricularModels, CardiovascularHeart VentriclesHumansbiomechanicscardiac electrophysiologycardiac functioncomputer modellinghypertrophy

Identifiers

PMID40897366
PMCPMC12487602

What Socratic holds

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LicenceCC BY
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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 Socratic graph.