A Potential-Based Inverse Spectral Method to Noninvasively Localize Discordant Distributions of Alternans on the Heart From the ECG

Coll‐Font, Jaume; Erem, Burak; Brooks, Dana H.

doi:10.1109/tbme.2017.2732159

Cited by 3 publications

References 28 publications

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Spatial Correlation Between Myocyte's Repolarization Times and Their Alternans Drives T-Wave Alternans on the ECG

Rivolta

Martínez

Sassi

et al. 2022

IEEE J. Biomed. Health Inform.

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Objective: T-wave alternans (TWA) manifests as beat-to-beat fluctuations of T-wave morphology on the electrocardiogram (ECG), with physiological bases not fully understood. Using a biophysical model of the ECG, we demonstrate and give explicit relations that TWA depends on the i) spatial covariance between myocytes' repolarization time and alternans; and ii) global alternans (common to every myocyte). Methods: We quantified the spatial covariance and global alternans by means of two new metrics, R index and δ, respectively. They were validated on both synthetic and real signals. Computerized simulations were generated using a biophysical model linking the action potentials with the surface ECG. Then, the metrics were computed in STAFF-III dataset, containing ECGs from patients who underwent coronary angioplasty with prolonged balloon inflations, and the time courses of the metrics were analyzed together with TWA measured on the surface ECG. Results: The metrics properly estimated the spatial covariance and global alternans in the synthetic data. In the STAFF-III dataset, the R index progressively increased from baseline to the fourth minute of inflation (median ∆R = 0.81 ms; p<0.05), whereas δ was mostly unaltered during the intervention ( δ = 0 ms). Conclusion: We reported, for the first time, that TWA is significantly driven by the myocyte's spatial covariance between their repolarization times and alternans, and not by global alternans, when TWA is generated by regional ischemia. Significance: The metrics may reveal new complementary insights into the mechanisms underlying TWA.

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Spatial Correlation Between Myocyte's Repolarization Times and Their Alternans Drives T-Wave Alternans on the ECG

Rivolta

Martínez

Sassi

et al. 2022

IEEE J. Biomed. Health Inform.

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A Common-Ground Review of the Potential for Machine Learning Approaches in Electrocardiographic Imaging Based on Probabilistic Graphical Models

Coll‐Font

Wang

Brooks

2018

2018 Computing in Cardiology Conference (CinC)

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Machine learning (ML) methods have seen an explosion in their development and application. They are increasingly being used in many different fields with considerable success. However, although the interest is growing, their impact in the field of electrocardiographic imaging (ECGI) remains limited. One of the main reasons that ML has yet to become more prevalent in ECGI is that the published literature is scattered and there is no common ground description and comparison of these methods in an ML framework. Here we address this limitation with a review of ECGI methods from the perspective of ML. We will use probabilistic modeling to provide a common ground framework to compare different methods and well known approaches. Finally, we will discuss which approaches have been used to do inference on these models and which alternatives could be utilized as the methods in ML become more mature.

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Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (II): Electrogram Clustering and T-Wave Alternans

Caulier‐Cisterna

Blanco–Velasco

Goya–Esteban

et al. 2020

Sensors

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During the last years, attention and controversy have been present for the first commercially available equipment being used in Electrocardiographic Imaging (ECGI), a new cardiac diagnostic tool which opens up a new field of diagnostic possibilities. Previous knowledge and criteria of cardiologists using intracardiac Electrograms (EGM) should be revisited from the newly available spatial–temporal potentials, and digital signal processing should be readapted to this new data structure. Aiming to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology, we previously presented two results: First, spatial consistency can be observed even for very basic cardiac signal processing stages (such as baseline wander and low-pass filtering); second, useful bipolar EGMs can be obtained by a digital processing operator searching for the maximum amplitude and including a time delay. In addition, this work aims to demonstrate the functionality of ECGI for cardiac electrophysiology from a twofold view, namely, through the analysis of the EGM waveforms, and by studying the ventricular repolarization properties. The former is scrutinized in terms of the clustering properties of the unipolar an bipolar EGM waveforms, in control and myocardial infarction subjects, and the latter is analyzed using the properties of T-wave alternans (TWA) in control and in Long-QT syndrome (LQTS) example subjects. Clustered regions of the EGMs were spatially consistent and congruent with the presence of infarcted tissue in unipolar EGMs, and bipolar EGMs with adequate signal processing operators hold this consistency and yielded a larger, yet moderate, number of spatial–temporal regions. TWA was not present in control compared with an LQTS subject in terms of the estimated alternans amplitude from the unipolar EGMs, however, higher spatial–temporal variation was present in LQTS torso and epicardium measurements, which was consistent through three different methods of alternans estimation. We conclude that spatial–temporal analysis of EGMs in ECGI will pave the way towards enhanced usefulness in the clinical practice, so that atomic signal processing approach should be conveniently revisited to be able to deal with the great amount of information that ECGI conveys for the clinician.

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A Potential-Based Inverse Spectral Method to Noninvasively Localize Discordant Distributions of Alternans on the Heart From the ECG

Abstract: Our results suggest that ISM is capable of reliably detecting the different regions present in a TWA distribution across a wide variety of TWA locations on the heart in simulation and in the face of transients and nonidealities in the canine recordings.

Cited by 3 publications

References 28 publications

Spatial Correlation Between Myocyte's Repolarization Times and Their Alternans Drives T-Wave Alternans on the ECG

Spatial Correlation Between Myocyte's Repolarization Times and Their Alternans Drives T-Wave Alternans on the ECG

A Common-Ground Review of the Potential for Machine Learning Approaches in Electrocardiographic Imaging Based on Probabilistic Graphical Models

Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (II): Electrogram Clustering and T-Wave Alternans

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