Cargando…

Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials

During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprec...

Descripción completa

Detalles Bibliográficos
Autores principales: Caulier-Cisterna, Raúl, Sanromán-Junquera, Margarita, Muñoz-Romero, Sergio, Blanco-Velasco, Manuel, Goya-Esteban, Rebeca, García-Alberola, Arcadi, Rojo-Álvarez, José Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309141/
https://www.ncbi.nlm.nih.gov/pubmed/32492938
http://dx.doi.org/10.3390/s20113131
_version_ 1783549156519837696
author Caulier-Cisterna, Raúl
Sanromán-Junquera, Margarita
Muñoz-Romero, Sergio
Blanco-Velasco, Manuel
Goya-Esteban, Rebeca
García-Alberola, Arcadi
Rojo-Álvarez, José Luis
author_facet Caulier-Cisterna, Raúl
Sanromán-Junquera, Margarita
Muñoz-Romero, Sergio
Blanco-Velasco, Manuel
Goya-Esteban, Rebeca
García-Alberola, Arcadi
Rojo-Álvarez, José Luis
author_sort Caulier-Cisterna, Raúl
collection PubMed
description During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprecedented amount of measured cardiac signals needs to be conditioned and adapted to current knowledge and methods in cardiac electrophysiology in order to maximize its support to the clinical practice. In this setting, many cardiac indices are defined in terms of the so-called bipolar electrograms, which correspond with differential potentials between two spatially close potential measurements. Our aim was to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology. For this purpose, we first analyzed the basic stages of conventional cardiac signal processing and scrutinized the implications of the spatial-temporal nature of signals in ECGI scenarios. Specifically, the stages of baseline wander removal, low-pass filtering, and beat segmentation and synchronization were considered. We also aimed to establish a mathematical operator to provide suitable bipolar electrograms from the ECGI-estimated epicardium potentials. Results were obtained on data from an infarction patient and from a healthy subject. First, the low-frequency and high-frequency noises are shown to be non-independently distributed in the ECGI-estimated recordings due to their spatial dimension. Second, bipolar electrograms are better estimated when using the criterion of the maximum-amplitude difference between spatial neighbors, but also a temporal delay in discrete time of about 40 samples has to be included to obtain the usual morphology in clinical bipolar electrograms from catheters. We conclude that spatial-temporal digital signal processing and bipolar electrograms can pave the way towards the usefulness of ECGI recordings in the cardiological clinical practice. The companion paper is devoted to analyzing clinical indices obtained from ECGI epicardial electrograms measuring waveform variability and repolarization tissue properties.
format Online
Article
Text
id pubmed-7309141
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-73091412020-06-25 Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials Caulier-Cisterna, Raúl Sanromán-Junquera, Margarita Muñoz-Romero, Sergio Blanco-Velasco, Manuel Goya-Esteban, Rebeca García-Alberola, Arcadi Rojo-Álvarez, José Luis Sensors (Basel) Article During the last years, Electrocardiographic Imaging (ECGI) has emerged as a powerful and promising clinical tool to support cardiologists. Starting from a plurality of potential measurements on the torso, ECGI yields a noninvasive estimation of their causing potentials on the epicardium. This unprecedented amount of measured cardiac signals needs to be conditioned and adapted to current knowledge and methods in cardiac electrophysiology in order to maximize its support to the clinical practice. In this setting, many cardiac indices are defined in terms of the so-called bipolar electrograms, which correspond with differential potentials between two spatially close potential measurements. Our aim was to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology. For this purpose, we first analyzed the basic stages of conventional cardiac signal processing and scrutinized the implications of the spatial-temporal nature of signals in ECGI scenarios. Specifically, the stages of baseline wander removal, low-pass filtering, and beat segmentation and synchronization were considered. We also aimed to establish a mathematical operator to provide suitable bipolar electrograms from the ECGI-estimated epicardium potentials. Results were obtained on data from an infarction patient and from a healthy subject. First, the low-frequency and high-frequency noises are shown to be non-independently distributed in the ECGI-estimated recordings due to their spatial dimension. Second, bipolar electrograms are better estimated when using the criterion of the maximum-amplitude difference between spatial neighbors, but also a temporal delay in discrete time of about 40 samples has to be included to obtain the usual morphology in clinical bipolar electrograms from catheters. We conclude that spatial-temporal digital signal processing and bipolar electrograms can pave the way towards the usefulness of ECGI recordings in the cardiological clinical practice. The companion paper is devoted to analyzing clinical indices obtained from ECGI epicardial electrograms measuring waveform variability and repolarization tissue properties. MDPI 2020-06-01 /pmc/articles/PMC7309141/ /pubmed/32492938 http://dx.doi.org/10.3390/s20113131 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Caulier-Cisterna, Raúl
Sanromán-Junquera, Margarita
Muñoz-Romero, Sergio
Blanco-Velasco, Manuel
Goya-Esteban, Rebeca
García-Alberola, Arcadi
Rojo-Álvarez, José Luis
Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title_full Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title_fullStr Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title_full_unstemmed Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title_short Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (I): Preprocessing and Bipolar Potentials
title_sort spatial-temporal signals and clinical indices in electrocardiographic imaging (i): preprocessing and bipolar potentials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309141/
https://www.ncbi.nlm.nih.gov/pubmed/32492938
http://dx.doi.org/10.3390/s20113131
work_keys_str_mv AT cauliercisternaraul spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT sanromanjunqueramargarita spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT munozromerosergio spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT blancovelascomanuel spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT goyaestebanrebeca spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT garciaalberolaarcadi spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials
AT rojoalvarezjoseluis spatialtemporalsignalsandclinicalindicesinelectrocardiographicimagingipreprocessingandbipolarpotentials