ArticleCirculation. Arrhythmia and electrophysiology2020
Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers.
Article in Circulation. Arrhythmia and electrophysiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Temporal Trends and Lesion Sets for Persistent Atrial Fibrillation Ablation: A Meta-Analysis With Trial Sequential Analysis and Meta-Regression.Circulation. Arrhythmia and electrophysiology · 2023Pooled it
- Spatial Autocorrelation Dimension (Arrhythmia & electrophysiology review · 2026Review
- Granger causality connectivity analysis of persistent atrial fibrillation dynamics reveals posterior wall mechanistic insights.Heart rhythm O2 · 2025Article
- Abnormal CaFrontiers in pharmacology · 2025Article
- Information theory-based direct causality measure to assess cardiac fibrillation dynamics.Journal of the Royal Society, Interface · 2023Article
- A Divergence-Based Approach for the Identification of Atrial Fibrillation Focal Drivers From Multipolar Mapping: A Computational Study.Frontiers in physiology · 2021Article
- Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments.Frontiers in physiology · 2021Article
- Response by Handa et al to Letter Regarding Article, "Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers".Circulation. Arrhythmia and electrophysiology · 2020Article
- Toward Mechanism-Directed Electrophenotype-Based Treatments for Atrial Fibrillation.Frontiers in physiology · 2020Review
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13 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundThe mechanisms sustaining myocardial fibrillation remain disputed, partly due to a lack of mapping tools that can accurately identify the mechanism with low spatial resolution clinical recordings. Granger causality (GC) analysis, an econometric tool for quantifying causal relationships between complex time-series, was developed as a novel fibrillation mapping tool and adapted to low spatial resolution sequentially acquired data.
methodsVentricular fibrillation (VF) optical mapping was performed in Langendorff-perfused Sprague-Dawley rat hearts (n=18), where novel algorithms were developed using GC-based analysis to (1) quantify causal dependence of neighboring signals and plot GC vectors, (2) quantify global organization with the causality pairing index, a measure of neighboring causal signal pairs, and (3) localize rotational drivers (RDs) by quantifying the circular interdependence of neighboring signals with the circular interdependence value. GC-based mapping tools were optimized for low spatial resolution from downsampled optical mapping data, validated against high-resolution phase analysis and further tested in previous VF optical mapping recordings of coronary perfused donor heart left ventricular wedge preparations (n=12), and adapted for sequentially acquired intracardiac electrograms during human persistent atrial fibrillation mapping (n=16).
resultsGlobal VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution:
conclusionsGC-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map RDs using low spatial resolution sequentially acquired data.
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