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Granger causality-based analysis for classification of fibrillation mechanisms and localisation of rotational drivers

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Title: Granger causality-based analysis for classification of fibrillation mechanisms and localisation of rotational drivers
Authors: Handa, B
Li, X
Aras, KK
Qureshi, NA
Mann, I
Chowdhury, R
Whinnett, ZI
Linton, NWF
Lim, PB
Kanagaratnam, P
Efimov, IR
Peters, N
Ng, FS
Item Type: Journal Article
Abstract: Background: The 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. Methods: Ventricular 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). Results: Global VF organization quantified by causality pairing index showed a negative correlation at progressively lower resolutions (50% resolution: P=0.006, R2=0.38, 12.5% resolution, P=0.004, R2=0.41) with a phase analysis derived measure of disorganization, locations occupied by phase singularities. In organized VF with high causality pairing index values, GC vector mapping characterized dominant propagating patterns and localized stable RDs, with the circular interdependence value showing a significant difference in driver versus nondriver regions (0.91±0.05 versus 0.35±0.06, P=0.0002). These findings were further confirmed in human VF. In persistent atrial fibrillation, a positive correlation was found between the causality pairing index and presence of stable RDs (P=0.0005,R2=0.56). Fifty percent of patients had RDs, with a low incidence of 0.9±0.3 RDs per patient. Conclusions: GC-based fibrillation analysis can measure global fibrillation organization, characterize dominant propagating patterns, and map RDs using low spatial resolution sequentially acquired data.
Issue Date: 16-Feb-2020
Date of Acceptance: 4-Feb-2020
URI: http://hdl.handle.net/10044/1/77567
DOI: 10.1161/CIRCEP.119.008237
ISSN: 1941-3084
Publisher: American Heart Association
Start Page: 258
End Page: 273
Journal / Book Title: Circulation: Arrhythmia and Electrophysiology
Volume: 12
Issue: 3
Copyright Statement: © 2020 The Authors. Circulation: Arrhythmia and Electrophysiology is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.
Sponsor/Funder: British Heart Foundation
British Heart Foundation
Rosetrees Trust
Imperial College Healthcare NHS Trust- BRC Funding
British Heart Foundation
British Heart Foundation
Rosetrees Trust
Imperial College Healthcare NHS Trust- BRC Funding
Imperial College Healthcare NHS Trust- BRC Funding
British Heart Foundation
Funder's Grant Number: RG/16/3/32175
RG/16/3/32175
A1173/ M577
RDB02
PG/16/17/32069
PG/16/17/32069
A1407/ M645
RDB02
RDF01
RE/18/4/34215
Keywords: Granger causality
causality pairing index
rotational drivers
1102 Cardiorespiratory Medicine and Haematology
1103 Clinical Sciences
1116 Medical Physiology
Cardiovascular System & Hematology
Online Publication Date: 2020-02-16
Appears in Collections:National Heart and Lung Institute