Evidence map›Paper›PMID 39946790›Full record

ArticleComputers in biology and medicine2025

Defining myocardial fiber bundle architecture in atrial digital twins.

Roberto Piersanti, Ryan Bradley, Syed Yusuf Ali, Alfio Quarteroni, Luca Dede', Natalia A Trayanova

Abstract read
In one paragraph

Article in Computers in biology and medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Roberto PiersantiMOX - Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Milano, Italy; ADVANCE - Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, USA. Electronic address: roberto.piersanti@polimi.it.
Ryan BradleyADVANCE - Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, USA; Research Computing, Lehigh University, Bethlehem, PA, USA.
Syed Yusuf AliDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, USA.
Alfio QuarteroniMOX - Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Milano, Italy; Mathematics Institute, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Luca Dede'MOX - Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Milano, Italy.
Natalia A TrayanovaADVANCE - Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, USA.

Funding

Artificial intelligence analysis of atrial remodeling evolution in patients with atrial fibrillation: Towards optimal ablation strategiesR01HL166759 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Eugene Kholmovski, David Spragg · 2023 to 2026
$3.2M
Heart Digital Twin Analysis of Arrhythmias due to Infiltrating AdiposityR01HL174440 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI NATALIA A. TRAYANOVA · 2024 to 2026
$2.1M
NHLBI NIH HHS R01 HL166759NHLBI NIH HHS R01 HL174440
6 · The paper itself

Abstract

A key component in developing atrial digital twins (ADT) - virtual representations of patients' atria - is the accurate prescription of myocardial fibers which are essential for the tissue characterization. Due to the difficulty of reconstructing atrial fibers from medical imaging, a widely used strategy for fiber generation in ADT relies on mathematical models. Existing methodologies utilize semi-automatic approaches, are tailored to specific morphologies, and lack rigorous validation against imaging fiber data. In this study, we introduce a novel atrial Laplace-Dirichlet-Rule-Based Method (LDRBM) for prescribing highly detailed myofiber orientations and providing robust regional annotation in bi-atrial morphologies of any complexity. The robustness of our approach is verified in eight extremely detailed bi-atrial geometries, derived from a sub-millimeter Diffusion-Tensor-Magnetic-Resonance Imaging (DTMRI) human atrial fiber dataset. We validate the LDRBM by quantitatively recreating each of the DTMRI fiber architectures: a comprehensive comparison with DTMRI ground truth data is conducted, investigating differences between electrophysiology (EP) simulations provided by either LDRBM and DTMRI fibers. Finally, we demonstrate that the novel LDRBM outperforms current state-of-the-art (LDRBMs and Universal Atrial Coordinates) fiber models, confirming the exceptional accuracy of our methodology and the critical importance of incorporating detailed fiber orientations in EP simulations. Ultimately, this work represents a fundamental step towards the development of physics-based digital twins of the human atria, establishing a new standard for prescribing fibers in ADT.

Indexed as

Heart AtriaImage Processing, Computer-AssistedModels, CardiovascularMyocardiumDiffusion Tensor ImagingHumansMaleCardiac digital twinCardiac fiber architectureComputational modelingNumerical simulationsPrecision medicine

Identifiers

PMID39946790
PMCPMC11966639

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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.