Electrocardiographic characteristics of idiopathic ventricular arrhythmias based on anatomy

Auto-contouring of cardiac substructures for Stereotactic arrhythmia radioablation (STAR): A STOPSTORM.eu consortium study

BACKGROUND/PURPOSE

High doses to healthy cardiac substructures (CS) in stereotactic arrhythmia radioablation (STAR) raise concerns regarding potential treatment-induced cardio-toxicity. However, CS contours are not routinely created, hindering the understanding of the CS dose-effect relationships. To address this issue, the alignment of CS contouring was initiated within the STOPSTORM consortium. In this study, we developed and evaluated auto-contouring models trained to delineate CS and major vessels in ventricular tachycardia (VT) patients.

METHODS

Eight centres provided standard treatment planning computed tomography (CT) and/or contrast-enhanced CT datasets of 55 VT patients, each including 16 CS. Auto-contouring models were trained to contour either large structures or small structures. Dice Similarity Coefficient (DSC), 95 % Hausdorff distance (HD95) and volume ratio (VR) were used to evaluate model performance versus inter-observer variation (IOV) on seven VT patient test cases. Significant differences were tested using the Mann-Whitney U test.

RESULTS

The performance on the four chambers and the major vessels (median DSC: 0.88; HD95: 5.8-19.4 mm; VR: 1.09) was similar to the IOV (median DSC: 0.89; HD95: 4.8-14.0 mm; VR: 1.20). For the valves, model performance (median DSC: 0.37; HD95: 11.6 mm; VR: 1.63) was similar to the IOV (median DSC: 0.41; HD95: 12.4 mm; VR: 3.42), but slightly worse for the coronary arteries (median DSC: 0.33 vs 0.42; HD95: 24.4 mm vs 16.9 mm; VR: 1.93 vs 3.30). The IOV for these small structures remains large despite using contouring guidelines.

CONCLUSION

CS auto-contouring models trained on VT patient data perform similarly to IOV. This allows for time-efficient evaluation of CS as possible organs-at-risk.

Enhancing origin prediction: deep learning model for diagnosing premature ventricular contractions with dual-rhythm analysis focused on cardiac rotation

AIMS

Several algorithms can differentiate inferior axis premature ventricular contractions (PVCs) originating from the right side and left side on 12-lead electrocardiograms (ECGs). However, it is unclear whether distinguishing the origin should rely solely on PVC or incorporate sinus rhythm (SR). We compared the dual-rhythm model (incorporating both SR and PVC) to the PVC model (using PVC alone) and quantified the contribution of each ECG lead in predicting the PVC origin for each cardiac rotation.

METHODS AND RESULTS

This multicentre study enrolled 593 patients from 11 centres-493 from Japan and Germany, and 100 from Belgium, which were used as the external validation data set. Using a hybrid approach combining a Resnet50-based convolutional neural network and a transformer model, we developed two variants-the PVC and dual-rhythm models-to predict PVC origin. In the external validation data set, the dual-rhythm model outperformed the PVC model in accuracy (0.84 vs. 0.74, respectively; P < 0.01), precision (0.73 vs. 0.55, respectively; P < 0.01), specificity (0.87 vs. 0.68, respectively; P < 0.01), area under the receiver operating characteristic curve (0.91 vs. 0.86, respectively; P = 0.03), and F1-score (0.77 vs. 0.68, respectively; P = 0.03). The contributions to PVC origin prediction were 77.3% for PVC and 22.7% for the SR. However, in patients with counterclockwise rotation, SR had a greater contribution in predicting the origin of right-sided PVC.

CONCLUSION

Our deep learning-based model, incorporating both PVC and SR morphologies, resulted in a higher prediction accuracy for PVC origin, considering SR is particularly important for predicting right-sided origin in patients with counterclockwise rotation.

Lead I R-wave indexes: A novel electrocardiographic criterion for distinguishing the origin of idiopathic premature ventricular contractions from the three subregions of the aortic sinus cusps

PURPOSE

The current study was conducted to investigate the electrocardiographic (ECG) characteristics of idiopathic premature ventricular contractions (PVCs) originating from the aortic sinus cusp (ASC) and establish a novel ECG criterion to discriminate PVCs originating from the right coronary cusp (RCC), left coronary cusp (LCC), and the left and right coronary cusp junction (LRJ).

METHODS

A retrospective analysis was performed on a total of 133 patients with idiopathic PVCs who underwent successful mapping and ablation. The sites of origin (SOO) were confirmed using fluoroscopy and a three-dimensional mapping system during radiofrequency catheter ablation (RFCA). Among the patients, 69 had PVCs originating from the LCC, 39 from the RCC, and 25 from the LRJ. Characteristics of surface 12‑lead electrocardiograms (ECGs) recorded during PVCs were analyzed. Q-, R-, S, and R'-wave amplitudes were measured in lead I, and the lead I R-wave indexes (IRa, IRb, IRc, IRd, and IRe) were derived by employing multiplication, subtraction, sum, and division operations on these ECG measurements. Notably, IRb and IRe demonstrated usefulness as ECG indexes for discriminating PVCs originating from RCC, LCC, and LRJ in the ASC.

RESULTS

The R- and S-wave amplitudes in lead I exhibited statistically significant differences among the three groups (P < 0.001 and P < 0.001, respectively). In discriminating PVCs originating from the RCC from the other two groups, IRb showed the largest area under the curve (AUC) of 0.813, as assessed by receiver operating characteristic (ROC) analysis, with a cutoff value of ≤0.5 indicating PVCs of RCC origin. The sensitivity and specificity were 80.3% and 78.7%, respectively. For discriminating PVCs arising from the LCC from those in the LRJ group, IRe exhibited the largest AUC of 0.801, with an optimal cutoff value of 0. An IRe value >0 indicated PVCs originating from the LRJ, while an IRe value ≤0 indicated PVCs originating from the LCC. The sensitivity and specificity of the IRe index were 84.0% and 70.7%, respectively.

CONCLUSION

Lead I R-wave indexes provided simple and useful ECG criteria for discriminating PVCs originating from the LCC, RCC, and LRJ in the left ventricular outflow tract (LVOT).

The R-S difference index: A new electrocardiographic method for differentiating idiopathic premature ventricular contractions originating from the left and right ventricular outflow tracts presenting a left bundle branch block pattern

Introduction: Differentiating idiopathic premature ventricular contractions (PVCs) originating from the right and left ventricular outflow tracts with a left bundle branch block (LBBB) morphology is relevant to catheter ablation planning and important for lowering the risk of complications. This study established a novel electrocardiographic (ECG) criterion to discriminate PVCs originating from the septum of the right ventricular outflow tract (s-RVOT) and those originating from the aortic sinus cusp of the left ventricular outflow tract (LVOT-ASC).

Methods: A total of 259 patients with idiopathic PVCs originating from ventricular outflow tract with a LBBB pattern who underwent successful catheter ablation were retrospectively included. Among them, the PVCs originated from the s-RVOT in 183 patients and from the LVOT-ASC in 76 patients. The surface ECGs of the PVCs and sinus beats were analyzed using an electronic caliper. The R-S difference index in the precordial leads was calculated as V2R + V3R + V4R − V1S.

Results: PVCs originating from both the s-RVOT and LVOT-ASC displayed an inferior axis (dominant R waves in leads II, III, and aVF). Compared with the s-RVOT group, the R-wave amplitudes on leads II, III, and aVF were significantly larger in the LVOT-ASC group (p < 0.001, p < 0.003, and p < 0.001, respectively). Compared to the LVOT-ASC group, the s-RVOT group showed smaller R-wave amplitudes on leads V1–V6 (p = 0.021, p < 0.001, p < 0.001, p < 0.001, p < 0.001, and p < 0.001, respectively) and larger S-wave amplitudes on leads V1–V3 (p < 0.001, p < 0.001, and p < 0.001, respectively). Lead V3 was the most common transitional lead in both groups. Analysis of the receiver operating characteristic curve showed that the R-wave amplitude on lead V3 had the largest area under the curve (AUC) of 0.856 followed by the R-wave amplitudes on leads V4 (0.834) and V2 (0.806). The AUC of the R-S difference index was 0.867. An R-S difference index greater than 20.9 predicted an LVOT-ASC origin with 73.7% sensitivity and 86.3% specificity. This index is superior to previous criteria in differentiating PVCs with LBBB morphology and inferior axis originating from s-RVOT vs. LVOT-ASC.

Conclusions: The R-S difference index in precordial leads is a useful new ECG criterion for distinguishing LVOT-PVCs from RVOT-PVCs with LBBB morphology.

Electrocardiographic characteristics of idiopathic ventricular arrhythmias based on anatomy

Idiopathic ventricular arrhythmia (IVA) is a term used to describe a spectrum of ventricular arrhythmia without structural heart disease (SHD). IVAs contain premature ventricular contractions (PVCs), nonsustained monomorphic ventricular tachycardia (VT), and sustained VT. Electrocardiography is a fundamental and important tool to diagnose and localize IVAs. More detailed, IVAs originating from different origins exhibit characterized ECGs due to their specific anatomic backgrounds. As catheter ablation becomes widely used to eliminate these arrhythmias, its high success rate is based on accurate localization of their origins. Therefore, these ECG characteristics show great importance for precise localization of their origins and subsequently successful ablation. This review aims to sum up ECG characteristics of IVAs based on anatomy and give brief introduction of mechanisms and treatment of IVAs.