Dataset Information

Automatic identification of a stable QRST complex for non-invasive evaluation of human cardiac electrophysiology.

ABSTRACT: BACKGROUND:A vectorcardiography approach to electrocardiology contributes to the non-invasive assessment of electrical heterogeneity in the ventricles of the heart and to risk stratification for cardiac events including sudden cardiac death. The aim of this study was to develop an automatic method that identifies a representative QRST complex (QRSonset to Tend) from a Frank vectorcardiogram (VCG). This method should provide reliable measurements of morphological VCG parameters and signal when such measurements required manual scrutiny. METHODS:Frank VCG was recorded in a population-based sample of 1094 participants (550 women) 50-65 years old as part of the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot. Standardized supine rest allowing heart rate stabilization and adaptation of ventricular repolarization preceded a recording period lasting ?5 minutes. In the Frank VCG a recording segment during steady-state conditions and with good signal quality was selected based on QRST variability. In this segment a representative signal-averaged QRST complex from cardiac cycles during 10s was selected. Twenty-eight morphological parameters were calculated including both conventional conduction intervals and VCG-derived parameters. The reliability and reproducibility of these parameters were evaluated when using completely automatic and automatic but manually edited annotation points. RESULTS:In 1080 participants (98.7%) our automatic method reliably selected a representative QRST complex where its instability measure effectively identified signal variability due to both external disturbances ("noise") and physiologic and pathophysiologic variability, such as e.g. sinus arrhythmia and atrial fibrillation. There were significant sex-related differences in 24 of 28 VCG parameters. Some VCG parameters were insensitive to the instability value, while others were moderately sensitive. CONCLUSION:We developed an automatic process for identification of a signal-averaged QRST complex suitable for morphologic measurements which worked reliably in 99% of participants. This process is applicable for all non-invasive analyses of cardiac electrophysiology including risk stratification for cardiac death based on such measurements.

SUBMITTER: Lundahl G

PROVIDER: S-EPMC7498068 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Automatic identification of a stable QRST complex for non-invasive evaluation of human cardiac electrophysiology.

Lundahl Gunilla G Gransberg Lennart L Bergqvist Gabriel G Bergström Göran G Bergfeldt Lennart L

PloS one 20200917 9

<h4>Background</h4>A vectorcardiography approach to electrocardiology contributes to the non-invasive assessment of electrical heterogeneity in the ventricles of the heart and to risk stratification for cardiac events including sudden cardiac death. The aim of this study was to develop an automatic method that identifies a representative QRST complex (QRSonset to Tend) from a Frank vectorcardiogram (VCG). This method should provide reliable measurements of morphological VCG parameters and signal ...[more]

PMID: 32941513

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Project description:Clinical and experimental studies involving human hearts can have certain limitations. Methods such as computer simulations can be an important alternative or supplemental tool. Physiological simulation at the tissue or organ level typically involves the handling of partial differential equations (PDEs). Boundary conditions and distributed parameters, such as those used in pharmacokinetics simulation, add to the complexity of the PDE solution. These factors can tailor PDE solutions and their corresponding program code to specific problems. Boundary condition and parameter changes in the customized code are usually prone to errors and time-consuming. We propose a general approach for handling PDEs and boundary conditions in computational models using a replacement scheme for discretization. This study is an extension of a program generator that we introduced in a previous publication. The program generator can generate code for multi-cell simulations of cardiac electrophysiology. Improvements to the system allow it to handle simultaneous equations in the biological function model as well as implicit PDE numerical schemes. The replacement scheme involves substituting all partial differential terms with numerical solution equations. Once the model and boundary equations are discretized with the numerical solution scheme, instances of the equations are generated to undergo dependency analysis. The result of the dependency analysis is then used to generate the program code. The resulting program code are in Java or C programming language. To validate the automatic handling of boundary conditions in the program code generator, we generated simulation code using the FHN, Luo-Rudy 1, and Hund-Rudy cell models and run cell-to-cell coupling and action potential propagation simulations. One of the simulations is based on a published experiment and simulation results are compared with the experimental data. We conclude that the proposed program code generator can be used to generate code for physiological simulations and provides a tool for studying cardiac electrophysiology.

Project description:To develop electrocardiogram (ECG) tools to quantify the number of sources for atrial fibrillation (AF), i.e. spatially stable rotors and focal impulses, and whether they lie in right or left atrium. Intracardiac mapping has recently shown that paroxysmal and persistent AF is sustained by rotors or focal sources that are stable in location and thus targets for limited ablation [focal impulse and rotor modulation (FIRM)] to eliminate AF. Importantly, the numbers and locations of concurrent sources determine both the complexity of AF and the approach for ablation.In 36 AF patients (n = 29 persistent, 63 ± 9 years) in the CONventional ablation with or without Focal Impulse and Rotor Modulation (CONFIRM) trial, we developed phase lock (PL) to quantify spatial repeatability of ECG 'F-waves' between leads over time. Phase lock spectrally quantifies the angle ? between F-wave voltages in planes formed by ECG leads I, aVF, and V1 at successive points in time. We compared PL with ECG spectral dominant frequency (DF) and organizational index (OI) to characterize stable rotors and focal sources validated by intracardiac FIRM mapping. Focal impulse and rotor modulation ablation alone at ?3 sources acutely terminated and rendered AF non-inducible or substantially slowed AF in 31 of 36 patients. Receiver operating characteristics of PL for this endpoint had area under the curve (AUC) = 0.72, and the optimum cut-point (PL = 0.09) had 74% sensitivity, 92% positive predictive value (PPV). Receiver operating characteristics areas for OI and DF were 0.50 and 0.58, respectively. Left (n = 28) or right (n = 3) atrial sources were localized by PL with AUC = 0.85, sensitivity 100%, PPV 30%, and negative predictive value 100%. Spectral DF provided AUC = 0.79. Notably, PL did not comigrate with diagnosis of paroxysmal or persistent AF (P = NS), unlike ECG DF.The novel metric of ECG PL identifies patients with fewer (?3) or greater numbers of stable rotors/focal sources for AF, validated by intracardiac FIRM mapping, and localized them to right or left atria. These data open the possibility of using 12-lead ECG analyses to classify AF mechanistically and plan procedures for right- or left-sided FIRM ablation.

Dataset Information

Automatic identification of a stable QRST complex for non-invasive evaluation of human cardiac electrophysiology.

Publications

Automatic identification of a stable QRST complex for non-invasive evaluation of human cardiac electrophysiology.

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