Evidence map›Paper›PMID 40443448›Full record

ArticleFrontiers in physiology2025

Impact of rigid cardiac motion on the accuracy of electrocardiographic imaging.

Xiafeng Zhang, Kaiyu Chen, Yucheng Wang, Wei Li, Tingcun Wei, Shaoxi Wang

Abstract read
In one paragraph

Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Xiafeng ZhangSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.
Kaiyu ChenSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.
Yucheng WangSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.
Wei LiSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.
Tingcun WeiSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.
Shaoxi WangSchool of Microelectronics, Northwestern Polytechnical University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Electrocardiographic Imaging (ECGI) offers a non-invasive approach to reconstruct cardiac electrical activity. However, the inverse problem of ECGI is highly ill-conditioned, making it sensitive to errors. In practice, rigid displacements of the heart during beating introduce geometric errors into the ECGI problem. This study aims to investigate the impact of cardiac rigid motion on the accuracy of ECGI. Methods: We employed the Boundary Element Method (BEM) to solve the forward problem and the Tikhonov method to address the inverse problem. We utilized a dataset from the CRVTI/SCI Institute, which involves Langendorff-perfused dog hearts suspended in a torso-shaped tank. Based on clinical experience, six different types of cardiac movement patterns, including translations and rotations, were designed to assess the impact of various displacements on the accuracy of the ECGI solution. Results: Our study found that among the translational and rotational movements of the heart, rotational motion should be prioritized for attention, as it caused significantly stronger changes in ECGI correlation coefficient (CC) and relative error (RE) than translational motion. Among the translations along the coordinate axes, movement along the y-axis (anterior-posterior movement within the chest cavity) had the least impact. For rotational movements, rolling had the least impact, yaw had moderate impact, and pitch had the greatest impact. Conclusion: The inverse solution of ECGI demonstrates a certain robustness to changes in heart position, with CC changes of less than 2% for 10 mm displacements and less than 5% for 10° rotations. This suggests that ECGI changes due to cardiac geometric motion can be disregarded within a certain range.

Indexed as

cardiac rigid motionelectrocardiographic imaging (ECGI)inverse solutionrotationtranslation

Identifiers

PMID40443448
PMCPMC12119561

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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.