Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and in response to increasing clinical demand, a variety of signals and indices have been utilized for its analysis, which include complex fractionated atrial electrograms (CFAEs). New methodologies have been developed to characterize t...

Full description

Bibliographic Details
Main Authors: Emanuela Finotti, Aurelio Quesada, Edward J. Ciaccio, Hasan Garan, Fernando Hornero, Raúl Alcaraz, José J. Rieta
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/24/9/1261
_version_ 1797488675692478464
author Emanuela Finotti
Aurelio Quesada
Edward J. Ciaccio
Hasan Garan
Fernando Hornero
Raúl Alcaraz
José J. Rieta
author_facet Emanuela Finotti
Aurelio Quesada
Edward J. Ciaccio
Hasan Garan
Fernando Hornero
Raúl Alcaraz
José J. Rieta
author_sort Emanuela Finotti
collection DOAJ
description Atrial fibrillation (AF) is the most common cardiac arrhythmia, and in response to increasing clinical demand, a variety of signals and indices have been utilized for its analysis, which include complex fractionated atrial electrograms (CFAEs). New methodologies have been developed to characterize the atrial substrate, along with straightforward classification models to discriminate between paroxysmal and persistent AF (ParAF vs. PerAF). Yet, most previous works have missed the mark for the assessment of CFAE signal quality, as well as for studying their stability over time and between different recording locations. As a consequence, an atrial substrate assessment may be unreliable or inaccurate. The objectives of this work are, on the one hand, to make use of a reduced set of nonlinear indices that have been applied to CFAEs recorded from ParAF and PerAF patients to assess intra-recording and intra-patient stability and, on the other hand, to generate a simple classification model to discriminate between them. The dominant frequency (DF), AF cycle length, sample entropy (SE), and determinism (DET) of the Recurrence Quantification Analysis are the analyzed indices, along with the coefficient of variation (CV) which is utilized to indicate the corresponding alterations. The analysis of the intra-recording stability revealed that discarding noisy or artifacted CFAE segments provoked a significant variation in the CV(%) in any segment length for the DET and SE, with deeper decreases for longer segments. The intra-patient stability provided large variations in the CV(%) for the DET and even larger for the SE at any segment length. To discern ParAF versus PerAF, correlation matrix filters and Random Forests were employed, respectively, to remove redundant information and to rank the variables by relevance, while coarse tree models were built, optimally combining high-ranked indices, and tested with leave-one-out cross-validation. The best classification performance combined the SE and DF, with an accuracy (Acc) of 88.3%, to discriminate ParAF versus PerAF, while the highest single Acc was provided by the DET, reaching 82.2%. This work has demonstrated that due to the high variability of CFAEs data averaging from one recording place or among different recording places, as is traditionally made, it may lead to an unfair oversimplification of the CFAE-based atrial substrate characterization. Furthermore, a careful selection of reduced sets of features input to simple classification models is helpful to accurately discern the CFAEs of ParAF versus PerAF.
first_indexed 2024-03-10T00:05:43Z
format Article
id doaj.art-d559cbb9a60d4e22b4762f875b590131
institution Directory Open Access Journal
issn 1099-4300
language English
last_indexed 2024-03-10T00:05:43Z
publishDate 2022-09-01
publisher MDPI AG
record_format Article
series Entropy
spelling doaj.art-d559cbb9a60d4e22b4762f875b5901312023-11-23T16:08:42ZengMDPI AGEntropy1099-43002022-09-01249126110.3390/e24091261Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial FibrillationEmanuela Finotti0Aurelio Quesada1Edward J. Ciaccio2Hasan Garan3Fernando Hornero4Raúl Alcaraz5José J. Rieta6BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, SpainArrhythmia Unit, Cardiology Department, General University Hospital Consortium of Valencia, 46014 Valencia, SpainDepartment of Medicine, Division of Cardiology, Columbia University Medical Center, New York, NY 10032, USADepartment of Medicine, Division of Cardiology, Columbia University Medical Center, New York, NY 10032, USACardiovascular Surgery Department, Hospital Clínico Universitario de Valencia, 46010 Valencia, SpainResearch Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, SpainBioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, SpainAtrial fibrillation (AF) is the most common cardiac arrhythmia, and in response to increasing clinical demand, a variety of signals and indices have been utilized for its analysis, which include complex fractionated atrial electrograms (CFAEs). New methodologies have been developed to characterize the atrial substrate, along with straightforward classification models to discriminate between paroxysmal and persistent AF (ParAF vs. PerAF). Yet, most previous works have missed the mark for the assessment of CFAE signal quality, as well as for studying their stability over time and between different recording locations. As a consequence, an atrial substrate assessment may be unreliable or inaccurate. The objectives of this work are, on the one hand, to make use of a reduced set of nonlinear indices that have been applied to CFAEs recorded from ParAF and PerAF patients to assess intra-recording and intra-patient stability and, on the other hand, to generate a simple classification model to discriminate between them. The dominant frequency (DF), AF cycle length, sample entropy (SE), and determinism (DET) of the Recurrence Quantification Analysis are the analyzed indices, along with the coefficient of variation (CV) which is utilized to indicate the corresponding alterations. The analysis of the intra-recording stability revealed that discarding noisy or artifacted CFAE segments provoked a significant variation in the CV(%) in any segment length for the DET and SE, with deeper decreases for longer segments. The intra-patient stability provided large variations in the CV(%) for the DET and even larger for the SE at any segment length. To discern ParAF versus PerAF, correlation matrix filters and Random Forests were employed, respectively, to remove redundant information and to rank the variables by relevance, while coarse tree models were built, optimally combining high-ranked indices, and tested with leave-one-out cross-validation. The best classification performance combined the SE and DF, with an accuracy (Acc) of 88.3%, to discriminate ParAF versus PerAF, while the highest single Acc was provided by the DET, reaching 82.2%. This work has demonstrated that due to the high variability of CFAEs data averaging from one recording place or among different recording places, as is traditionally made, it may lead to an unfair oversimplification of the CFAE-based atrial substrate characterization. Furthermore, a careful selection of reduced sets of features input to simple classification models is helpful to accurately discern the CFAEs of ParAF versus PerAF.https://www.mdpi.com/1099-4300/24/9/1261atrial fibrillationatrial arrhythmianonlinear indicesclassification modelscomplex fractionated atrial electrogramcatheter ablation
spellingShingle Emanuela Finotti
Aurelio Quesada
Edward J. Ciaccio
Hasan Garan
Fernando Hornero
Raúl Alcaraz
José J. Rieta
Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
Entropy
atrial fibrillation
atrial arrhythmia
nonlinear indices
classification models
complex fractionated atrial electrogram
catheter ablation
title Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
title_full Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
title_fullStr Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
title_full_unstemmed Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
title_short Practical Considerations for the Application of Nonlinear Indices Characterizing the Atrial Substrate in Atrial Fibrillation
title_sort practical considerations for the application of nonlinear indices characterizing the atrial substrate in atrial fibrillation
topic atrial fibrillation
atrial arrhythmia
nonlinear indices
classification models
complex fractionated atrial electrogram
catheter ablation
url https://www.mdpi.com/1099-4300/24/9/1261
work_keys_str_mv AT emanuelafinotti practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT aurelioquesada practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT edwardjciaccio practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT hasangaran practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT fernandohornero practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT raulalcaraz practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation
AT josejrieta practicalconsiderationsfortheapplicationofnonlinearindicescharacterizingtheatrialsubstrateinatrialfibrillation