Three-Dimensional Noninvasive Imaging of Ventricular Arrhythmias in Patients With Premature Ventricular Contractions

Yu, Long; Qi, Jin; Zhou, Zhaoye; Wu, Liqun; He, Bin

doi:10.1109/tbme.2017.2758369

Cited by 13 publications

(11 citation statements)

References 45 publications

(37 reference statements)

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“…The unipolar electrograms were obtained site by site sequentially by CARTO system. The endocardial surfaces of ventricles were registered with the segmented heart from CT images using a four-degree-freedom (locations and scale) rigid body registration method [ 55 ]. The CARTO endocardial geometries were automatically aligned based on similarities in shape without rotation.…”

Section: Methodsmentioning

confidence: 99%

Activation recovery interval imaging of premature ventricular contraction

Yang

et al. 2018

PLoS ONE

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Dispersion of ventricular repolarization due to abnormal activation contributes to the susceptibility to cardiac arrhythmias. However, the global pattern of repolarization is difficult to assess clinically. Activation recovery interval (ARI) has been used to understand the properties of ventricular repolarization. In this study, we developed an ARI imaging technique to noninvasively reconstruct three-dimensional (3D) ARI maps in 10 premature ventricular contraction (PVC) patients and evaluated the results with the endocardial ARI maps recorded by a clinical navigation system (CARTO). From the analysis results of a total of 100 PVC beats in 10 patients, the average correlation coefficient is 0.86±0.05 and the average relative error is 0.06±0.03. The average localization error is 4.5±2.3 mm between the longest ARI sites in 3D ARI maps and those in CARTO endocardial ARI maps. The present results suggest that ARI imaging could serve as an alternative of evaluating global pattern of ventricular repolarization noninvasively and could assist in the future investigation of the relationship between global repolarization dispersion and the susceptibility to cardiac arrhythmias.

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Section: Methodsmentioning

confidence: 99%

Activation recovery interval imaging of premature ventricular contraction

Yang

et al. 2018

PLoS ONE

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“…Several studies have validated the use of ECGi mapping for catheter ablation in patients with PVC/VT. 21 , 50 , 59 , 63 The localization of the VT and PVC pacing sites by non-invasive electrophysiological mapping using 120 21 , 59 , 63 or up to 208 body surface electrodes 50 prior to the invasive procedure was shown to be correlated with the results from the invasive mapping system CARTO.…”

Section: Ventricular Arrhythmiasmentioning

confidence: 96%

“…Among the studies described below, three included participants with Wolf–Parkinson–White (WPW) syndrome, 2 , 4 , 62 nine included patients with premature ventricular complexes (PVC), 4 , 6 , 21 , 37 , 45 , 48 , 50 , 56 , 61 and one compared the ability of QRS duration and left bundle branch block (LBBB) to ECGi for predicting CRT outcomes. 39 The studies that examined patients with WPW syndrome approached the disease mechanism in different ways.…”

Section: Ventricular Arrhythmiasmentioning

confidence: 99%

Electrocardiographic imaging for cardiac arrhythmias and resynchronization therapy

2020

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Use of the 12-lead electrocardiogram (ECG) is fundamental for the assessment of heart disease, including arrhythmias, but cannot always reveal the underlying mechanism or the location of the arrhythmia origin. Electrocardiographic imaging (ECGi) is a non-invasive multi-lead ECG-type imaging tool that enhances conventional 12-lead ECG. Although it is an established technology, its continuous development has been shown to assist in arrhythmic activation mapping and provide insights into the mechanism of cardiac resynchronization therapy (CRT). This review addresses the validity, reliability, and overall feasibility of ECGi for use in a diverse range of arrhythmias. A systematic search limited to full-text human studies published in peer-reviewed journals was performed through Medline via PubMed, using various combinations of three key concepts: ECGi, arrhythmia, and CRT. A total of 456 studies were screened through titles and abstracts. Ultimately, 42 studies were included for literature review. Evidence to date suggests that ECGi can be used to provide diagnostic insights regarding the mechanistic basis of arrhythmias and the location of arrhythmia origin. Furthermore, ECGi can yield valuable information to guide therapeutic decision-making, including during CRT. Several studies have used ECGi as a diagnostic tool for atrial and ventricular arrhythmias. More recently, studies have tested the value of this technique in predicting outcomes of CRT. As a non-invasive method for assessing cardiovascular disease, particularly arrhythmias, ECGi represents a significant advancement over standard procedures in contemporary cardiology. Its full potential has yet to be fully explored.

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“…For example, the 3DCEI approach minimizes the use of physiological constraints and was thus applied to various clinical conditions [8]- [11]. Some electrocardiographic imaging (ECGI) methods are integrating physiological and model-based priors in a Bayesian framework [12], [13].…”

Section: A Ep Model-based Inverse Problem Of Electrocardiographymentioning

confidence: 99%

Transfer Learning From Simulations on a Reference Anatomy for ECGI in Personalized Cardiac Resynchronization Therapy

Giffard‐Roisin

Delingette²,

Jackson

et al. 2019

IEEE Trans. Biomed. Eng.

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Abstract-Goal: Non-invasive cardiac electrophysiology (EP) model personalisation has raised interest for instance in the scope of predicting EP cardiac resynchronization therapy (CRT) response. However, the restricted clinical applicability of current methods is due in particular to the limitation to simple situations and the important computational cost. Methods: We propose in this manuscript an approach to tackle these two issues. First, we analyse more complex propagation patterns (multiple onsets and scar tissue) using relevance vector regression and shape dimensionality reduction on a large simulated database. Second, this learning is performed offline on a reference anatomy and transferred onto patient-specific anatomies in order to achieve fast personalised predictions online. Results: We evaluated our method on a dataset composed of 20 dyssynchrony patients with a total of 120 different cardiac cycles. The comparison with a commercially available electrocardiographic imaging (ECGI) method shows a good identification of the cardiac activation pattern. From the cardiac parameters estimated in sinus rhythm, we predicted 5 different paced patterns for each patient. The comparison with the body surface potential mappings (BSPM) measured during pacing and the ECGI method indicates a good predictive power. Conclusion: We showed that learning offline from a large simulated database on a reference anatomy was able to capture the main cardiac EP characteristics from non-invasive measurements for fast patient-specific predictions. Significance: The fast CRT pacing predictions are a step forward to a noninvasive CRT patient selection and therapy optimisation, to help clinicians in these difficult tasks.

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Three-Dimensional Noninvasive Imaging of Ventricular Arrhythmias in Patients With Premature Ventricular Contractions

Cited by 13 publications

References 45 publications

Activation recovery interval imaging of premature ventricular contraction

Activation recovery interval imaging of premature ventricular contraction

Electrocardiographic imaging for cardiac arrhythmias and resynchronization therapy

Transfer Learning From Simulations on a Reference Anatomy for ECGI in Personalized Cardiac Resynchronization Therapy

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