Related Experiment Video
Updated: Oct 22, 2026

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
Published on: July 29, 2011
Evaluation and Classification of Atrial Arrhythmias from Signatures in Electrographic Flow Metrics
Steven Castellano1, Melissa H Kong1, Joshua D'Arcy2
1Cortex, Inc., Menlo Park, CA, USA.
Abstract:
In patients undergoing atrial fibrillation (AF) ablation, it can be difficult at times to distinguish between AF, micro-re-entrant atrial flutters (AFLs), and focal atrial tachycardias (ATs). Understanding the mechanism of arrhythmogenesis can guide ablation lesion sets. Electrographic flow (EGF) mapping displays global atrial wavefront propagations in near-real time. Patterns of EGF can show both regions of stable flow direction over time and disorganized electrical wavefronts. In so doing, it can differentiate mechanisms of arrhythmogenesis. The objective of this study was to evaluate the EGF patterns and metrics that may be used to successfully differentiate mechanisms of arrhythmogenesis. A total of 2933 recordings from 151 patients who underwent EGF mapping were analyzed to determine metrics that could distinguish between mechanisms of arrhythmogenesis. These EGF-derived metrics include: (1) electrographic flow consistency (EGFC), (2) flow angle variability (FAV), (3) source activity, (4) atrial cycle length, (5) mean R-R correlation, and (6) disorganization score. The disorganization score varied the most between AF and AFL or AT (P < .0001), while the mean EGFC varied the most between AFL and AT (P < .0001). The mean FAV was found to be strongly correlated with both EGFC (r 2 = 0.767; P < .0001) and the disorganization score (r 2 = 0.552; P < .0001); therefore, the mean FAV was shown to contain the composite information of the other two metrics. A multilayer perceptron trained and tested on an equal number of recordings in each arrhythmia was also able to accurately determine the rhythm from previously unseen samples with 81% accuracy when given only the five remaining metrics. Additionally, it was 100% successful at distinguishing AF from the more organized rhythms. In conclusion, summative EGF metrics that characterize vector flow provide signature patterns of global atrial wavefront propagations in different atrial arrhythmias, which can be used to successfully determine the mechanisms of atrial arrhythmias.
Related Concept Videos
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias
Dysrhythmias V: Evaluating Dysrhythmias
Dysrhythmias II: Classification of Tachyarrhythmias
Mechanism of Cardiac Arrhythmias
Disturbances in Heart Rhythm
Arrhythmias are categorized by their speed, rhythm, and origin. A slow heart...
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism, and...
