TY - JOUR
T1 - Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotational Drivers
AU - Handa, Balvinder S.
AU - Li, Xinyang
AU - Aras, Kedar K.
AU - Qureshi, Norman A.
AU - Mann, Ian
AU - Chowdhury, Rasheda A.
AU - Whinnett, Zachary I.
AU - Linton, Nick W.F.
AU - Lim, Phang Boon
AU - Kanagaratnam, Prapa
AU - Efimov, Igor R.
AU - Peters, Nicholas S.
AU - Ng, Fu Siong
N1 - Publisher Copyright:
© 2020 Lippincott Williams and Wilkins. All rights reserved.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - 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.
AB - 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.
KW - algorithm
KW - atrial fibrillation
KW - catheter ablation
KW - incidence
KW - ventricular fibrillation
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U2 - 10.1161/CIRCEP.119.008237
DO - 10.1161/CIRCEP.119.008237
M3 - Article
C2 - 32064900
AN - SCOPUS:85082095599
SN - 1941-3149
VL - 13
SP - E008237
JO - Circulation: Arrhythmia and Electrophysiology
JF - Circulation: Arrhythmia and Electrophysiology
IS - 3
ER -