Accurate detection and characterization of the electrophysiological substrate underlying atrial tachycardia (AT) represent a critical frontier in improving outcomes for patients with supraventricular arrhythmias. The intricate interplay between structural remodeling, fibrosis, inflammation, and localized conduction abnormalities contributes to a complex arrhythmogenic substrate, posing significant challenges for diagnosis and treatment. Recent technological advancements in electroanatomic mapping, high-density mapping catheters, cardiac imaging, signal analysis, and computational modeling have significantly enhanced our understanding of the mechanisms driving AT, facilitating the development of more targeted and effective therapeutic strategies.
This Research Topic aims to compile cutting-edge original research, reviews, clinical studies, and perspectives that explore the current and future landscape of atrial tachycardia substrate detection. It seeks to showcase translational and clinical advances that deepen mechanistic insights, improve mapping precision, and boost procedural success in addressing both focal and macroreentrant atrial tachycardia.
To gather further insights into the strategies for detecting the substrate of atrial tachycardia, we welcome articles addressing, but not limited to, the following themes:
o Advanced Mapping Techniques: Utilization of high-resolution electroanatomic mapping, non-contact mapping systems, and automated algorithms to identify arrhythmogenic substrates.
o Imaging Modalities: Incorporation of cardiac MRI, CT, and ultrasound techniques for detecting atrial fibrosis, scar formation, and structural predictors of AT.
o Computational and Signal Analysis: Employment of signal processing, machine learning, and computational modeling to decipher substrate complexity and predict arrhythmia circuits.
o Translational and Clinical Implications: Assessment of the impact of precise substrate detection on ablation strategies, procedural planning, and long-term arrhythmia management.
o Future Directions: Exploration of emerging technologies and multidisciplinary approaches for substrate identification, including AI and next-generation mapping systems.
By encouraging research at the confluence of technology, clinical electrophysiology, and translational science, this Research Topic aims to refine the diagnosis and management of atrial tachycardia, ultimately fostering advancements in precision medicine for cardiac arrhythmias.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Clinical Trial
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Clinical Trial
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Review
Study Protocol
Systematic Review
Keywords: Atrial Tachycardia, Arrhythmia Substrate, Electroanatomic Mapping, Cardiac Imaging, Electrophysiology, Ablation, Fibrosis, Machine Learning, Signal Analysis, Precision Medicine
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.