Evidence map›Paper›PMID 37828428›Full record

ArticleBMC bioinformatics2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations.

Pasquale Claudio Africa, Roberto Piersanti, Francesco Regazzoni, Michele Bucelli, Matteo Salvador, Marco Fedele, Stefano Pagani, Luca Dede', Alfio Quarteroni

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  4. Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Review
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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.

Pasquale Claudio AfricaMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Roberto PiersantiMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy. roberto.piersanti@polimi.it.
Francesco RegazzoniMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Michele BucelliMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Matteo SalvadorMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Marco FedeleMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Stefano PaganiMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Luca Dede'MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
Alfio QuarteroniMOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.

Funding

H2020 Excellent Science 740132
6 · The paper itself

Abstract

backgroundSimulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors of various research teams, comprehensive and user-friendly software programs for cardiac simulations, capable of accurately replicating both normal and pathological conditions, are still in the process of achieving full maturity within the scientific community.

resultsThis work introduces [Formula: see text]-ep, a publicly available software for numerical simulations of the electrophysiology activity of the cardiac muscle, under both normal and pathological conditions. [Formula: see text]-ep employs the monodomain equation to model the heart's electrical activity. It incorporates both phenomenological and second-generation ionic models. These models are discretized using the Finite Element method on tetrahedral or hexahedral meshes. Additionally, [Formula: see text]-ep integrates the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, previously released in Africa et al., 2023, within [Formula: see text]-fiber. As an alternative, users can also choose to import myofibers from a file. This paper provides a concise overview of the mathematical models and numerical methods underlying [Formula: see text]-ep, along with comprehensive implementation details and instructions for users. [Formula: see text]-ep features exceptional parallel speedup, scaling efficiently when using up to thousands of cores, and its implementation has been verified against an established benchmark problem for computational electrophysiology. We showcase the key features of [Formula: see text]-ep through various idealized and realistic simulations conducted in both normal and pathological scenarios. Furthermore, the software offers a user-friendly and flexible interface, simplifying the setup of simulations using self-documenting parameter files.

conclusions[Formula: see text]-ep provides easy access to cardiac electrophysiology simulations for a wide user community. It offers a computational tool that integrates models and accurate methods for simulating cardiac electrophysiology within a high-performance framework, while maintaining a user-friendly interface. [Formula: see text]-ep represents a valuable tool for conducting in silico patient-specific simulations.

Indexed as

Electrophysiologic Techniques, CardiacSoftwareAfricaComputer SimulationHumansMyocardiumCardiac electrophysiologyComputational cardiologyFinite element methodHigh-performance computingMathematical modeling

Identifiers

PMID37828428
PMCPMC10571323

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.