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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Cardiac Activation Maps Reconstruction: A Comparative Study Between Data-Driven and Physics-Based Methods.

Amel Karoui1,2,3, Mostafa Bendahmane1,2, Nejib Zemzemi1,2,3

  • 1Institute of Mathematics, University of Bordeaux, Bordeaux, France.

Frontiers in Physiology
|September 13, 2021
PubMed
Summary
This summary is machine-generated.

DirectMap, a data-driven approach, significantly improves cardiac arrhythmia diagnosis by estimating activation maps directly from body surface potentials. This method outperforms traditional techniques in accuracy and robustness against noise.

Keywords:
ECGI inverse problemcardiac activation mappingdata-driven approachesdeep learningneural networksphysics-based approaches

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Area of Science:

  • Biomedical Engineering
  • Computational Electrophysiology
  • Medical Imaging

Background:

  • Cardiac arrhythmia diagnosis relies on activation mapping.
  • Electrocardiographic imaging reconstructs heart surface potentials from body surface potentials.
  • Artificial neural networks offer a novel approach for direct activation map estimation.

Purpose of the Study:

  • To compare the performance of a data-driven approach (DirectMap) against traditional noninvasive methods for cardiac activation mapping.
  • To evaluate the accuracy and robustness of DirectMap, Finite element method with L1-norm regularization (FEM-L1), and spatial adaptation of Time-delay neural networks (SATDNN-AT).

Main Methods:

  • A synthetic dataset simulating atrial pacing was used for performance assessment.
  • DirectMap, FEM-L1, and SATDNN-AT were applied to estimate activation maps from body surface potentials.
  • Performance was evaluated using absolute activation time error and correlation coefficient.

Main Results:

  • DirectMap achieved a lower absolute activation time error (7.20 ms) and higher correlation coefficient (93.2%) compared to FEM-L1 (14.60 ms, 76.2%) and SATDNN-AT (13.58 ms, 79.6%).
  • Data-driven methods (DirectMap and SATDNN-AT) demonstrated superior robustness against additive Gaussian noise compared to FEM-L1.

Conclusions:

  • The data-driven DirectMap approach quantitatively outperforms traditional methods for noninvasive cardiac activation mapping.
  • DirectMap offers a promising, accurate, and robust alternative for diagnosing cardiac arrhythmias.