A Review of the Forward Problem in Electrocardiographic Imaging

Area of Science:

• Biomedical Engineering
• Computational Electrophysiology
• Medical Imaging

Background:

• Electrocardiographic imaging (ECGI) is a noninvasive method to reconstruct cardiac electrical activity.
• The ECGI forward problem is crucial for accurate reconstruction of electrophysiological data.
• Various forward models exist, influencing the types of cardiac electrical information that can be derived.

Purpose of the Study:

• To review the modeling process and research progress in ECGI forward modeling.
• To systematically summarize mathematical methods used in the ECGI forward problem.
• To provide guidance on the practical applications of different forward models.

Main Methods:

• Classification of ECGI forward problem methods into three representative models: cardiac surface potential (CSP), equivalent double-layer (EDL), and transmembrane voltage (TMV).
• Detailed derivations of the mathematical formulations for each model.
• Discussion of the practical applications and implementation considerations for each model.

Main Results:

• The review categorizes and explains the mathematical underpinnings of CSP, EDL, and TMV models.
• It highlights how the choice of forward model impacts the reconstruction of epicardial/endocardial potentials, activation sequences, and transmembrane voltages.
• Guidance is provided on selecting and applying appropriate models for specific ECGI research and clinical needs.

Conclusions:

• Understanding ECGI forward modeling is essential for accurate cardiac electrical activity reconstruction.
• The CSP, EDL, and TMV models represent key approaches with distinct mathematical foundations and applications.
• This review offers a comprehensive resource for researchers and clinicians utilizing ECGI.