The processed Euphorbia lathyris L. alleviates the inflammatory injury via regulating LXRα/ABCA1 expression and TLR4 positioning to lipid rafts.

Euphorbia lathyris L. (EL) is a traditional poisonous herbal medicine used to treat dropsy, ascites, amenorrhea, anuria and constipation. Processing to reduce toxicity of EL is essential for its safe and effective application. However, there is little known regarding the molecular mechanism of reducing toxicity after EL processing. This research aimed to screen the differential markers for EL and PEL, explore the differential mechanisms of inflammatory injury induced by EL and processed EL (PEL) to expound the mechanism of alleviating toxicity after EL processing. The results showed that 15 potential biomarkers, mainly belonging to diterpenoids, were screened to distinguish EL from PEL. EL promoted the expressions of TLR4, NLRP3, NF-κB p65, IL-1ß and TNF-α, increased lipid rafts abundance and promoted TLR4 positioning to lipid rafts. Meanwhile, EL decreased LXRα and ABCA1 expression, and reduced cholesterol efflux. In contrast to EL, the effects of PEL on these indicators were markedly weakened. In addition, Euphorbia factors L1, L2, and L3 affected LXRα, ABCA1, TLR4, NLRP3, NF-κB p65, TNF-α and IL-1ß expression, influenced cholesterol efflux and lipid rafts abundance, and interfered with the colocalization of TLR4 and lipid rafts. The inflammatory injury caused by processed EL was significantly weaker than that caused by crude EL, and reduction of Euphorbia factors L1, L2, and L3 as well as attenuation of inflammatory injury participated in processing-based detoxification of EL. Our results provide valuable insights into the attenuated mechanism of EL processing and will guide future research on the processing mechanism of toxic traditional Chinese medicine.

Impact of proximity of left atrium to descending aorta on left inferior pulmonary vein triggers or drivers of atrial fibrillation: A risk score model.

BACKGROUND: Prior studies have investigated cardiac anatomy and clinical parameters as predictors for pulmonary vein and non-pulmonary vein triggers. OBJECTIVE: We aimed to assess the link between the descending aorta to left inferior pulmonary vein (Dao-LIPV) distance and the occurrence of triggers and drivers in atrial fibrillation (AF) ablation procedures. METHODS: Drug-refractory AF patients who underwent first-time index catheter ablation from January 2010 to December 2019 were retrospectively assembled. The Dao-LIPV distance was measured from preablation pulmonary vein computed tomography. Patients were assigned to groups on the basis of the presence of LIPV triggers or drivers. Multivariate logistic regression was used to identify risk factors. RESULTS: A total of 886 consecutive patients with drug-refractory AF were studied, and 63 (7.1%) patients were identified to have LIPV triggers or drivers. The Dao-LIPV distance had a better predictive performance (area under the curve, 0.70) compared with persistent AF (area under the curve, 0.57). Multivariate logistic regression analysis showed that Dao-LIPV distance ≤2.5 mm (odds ratio, 3.96; 95% CI, 2.15-7.29; P < .001) and persistent AF (odds ratio, 1.73; 95% CI, 1.02-2.94]; P = .044) were independent predictors for the presence of LIPV triggers or drivers. A risk score model was established to predict the probability of LIPV triggers or drivers with persistent AF (10.2%), Dao-LIPV distance ≤2.5 mm (11.4%), and both (15.0%). CONCLUSION: The proximity of the Dao-LIPV was correlated to the presence of LIPV triggers or drivers. We developed a risk score model indicating that persistent AF and Dao-LIPV distances ≤2.5 mm significantly increase the risk of LIPV triggers or drivers, aiding electrophysiologists in preparing for and performing catheter ablation more effectively.

Signal-averaged electrocardiography as a noninvasive tool for evaluating the ventricular substrate in patients with nonischemic cardiomyopathy: reassessment of an old tool.

Introduction: Signal-averaged electrocardiography (SAECG) provides diagnostic and prognostic information regarding cardiac diseases. However, its value in other nonischemic cardiomyopathies (NICMs) remains unclear. This study aimed to investigate the role of SAECG in patients with NICM. Methods and results: This retrospective study included consecutive patients with NICM who underwent SAECG, biventricular substrate mapping, and ablation for ventricular arrhythmia (VA). Patients with baseline ventricular conduction disturbances were excluded. Patients who fulfilled at least one SAECG criterion were categorized into Group 1, and the other patients were categorized into Group 2. Baseline and ventricular substrate characteristics were compared between the two groups. The study included 58 patients (39 men, mean age 50.4 ± 15.5 years), with 34 and 24 patients in Groups 1 and 2, respectively. Epicardial mapping was performed in eight (23.5%) and six patients (25.0%) in Groups 1 and 2 (p = 0.897), respectively. Patients in Group 1 had a more extensive right ventricular (RV) low-voltage zone (LVZ) and scar area than those in Group 2. Group 1 had a larger epicardial LVZ than Group 2. Epicardial late potentials were more frequent in Group 1 than in Group 2. There were more arrhythmogenic foci within the RV outflow tract in Group 1 than in Group 2. There was no significant difference in long-term VA recurrence. Conclusion: In our NICM population, a positive SAECG was associated with a larger RV endocardial scar, epicardial scar/late potentials, and a higher incidence of arrhythmogenic foci in the RV outflow tract.

Use of artificial intelligence and I-Score for prediction of recurrence before catheter ablation of atrial fibrillation.

BACKGROUND: Based solely on pre-ablation characteristics, previous risk scores have demonstrated variable predictive performance. This study aimed to predict the recurrence of AF after catheter ablation by using artificial intelligence (AI)-enabled pre-ablation computed tomography (PVCT) images and pre-ablation clinical data. METHODS: A total of 638 drug-refractory paroxysmal atrial fibrillation (AF) patients undergone ablation were recruited. For model training, we used left atria (LA) acquired from pre-ablation PVCT slices (126,288 images). A total of 29 clinical variables were collected before ablation, including baseline characteristics, medical histories, laboratory results, transthoracic echocardiographic parameters, and 3D reconstructed LA volumes. The I-Score was applied to select variables for model training. For the prediction of one-year AF recurrence, PVCT deep-learning and clinical variable machine-learning models were developed. We then applied machine learning to ensemble the PVCT and clinical variable models. RESULTS: The PVCT model achieved an AUC of 0.63 in the test set. Various combinations of clinical variables selected by I-Score can yield an AUC of 0.72, which is significantly better than all variables or features selected by nonparametric statistics (AUCs of 0.66 to 0.69). The ensemble model (PVCT images and clinical variables) significantly improved predictive performance up to an AUC of 0.76 (sensitivity of 86.7% and specificity of 51.0%). CONCLUSIONS: Before ablation, AI-enabled PVCT combined with I-Score features was applicable in predicting recurrence in paroxysmal AF patients. Based on all possible predictors, the I-Score is capable of identifying the most influential combination.

Deep learning-based workflow for automatic extraction of atria and epicardial adipose tissue on cardiac computed tomography in atrial fibrillation.

BACKGROUND: Preoperative estimation of the volume of the left atrium (LA) and epicardial adipose tissue (EAT) on computed tomography (CT) images is associated with an increased risk of atrial fibrillation (AF) recurrence. We aimed to design a deep learning-based workflow to provide reliable automatic segmentation of the atria, pericardium, and EAT for future applications in the management of AF. METHODS: This study enrolled 157 patients with AF who underwent first-time catheter ablation between January 2015 and December 2017 at Taipei Veterans General Hospital. Three-dimensional (3D) U-Net models of the LA, right atrium (RA), and pericardium were used to develop a pipeline for total, LA-EAT, and RA-EAT automatic segmentation. We defined fat within the pericardium as tissue with attenuation between -190 and -30 HU and quantified the total EAT. Regions between the dilated endocardial boundaries and endocardial walls of the LA or RA within the pericardium were used to detect voxels attributed to fat, thus estimating LA-EAT and RA-EAT. RESULTS: The LA, RA, and pericardium segmentation models achieved Dice coefficients of 0.960 ± 0.010, 0.945 ± 0.013, and 0.967 ± 0.006, respectively. The 3D segmentation models correlated well with the ground truth for the LA, RA, and pericardium ( r = 0.99 and p < 0.001 for all). The Dice coefficients of our proposed method for EAT, LA-EAT, and RA-EAT were 0.870 ± 0.027, 0.846 ± 0.057, and 0.841 ± 0.071, respectively. CONCLUSION: Our proposed workflow for automatic LA, RA, and EAT segmentation using 3D U-Nets on CT images is reliable in patients with AF.

Feasibility of Auto-Quantified Epicardial Adipose Tissue in Predicting Atrial Fibrillation Recurrence After Catheter Ablation.

BACKGROUND: The aim of this study was to build an auto-segmented artificial intelligence model of the atria and epicardial adipose tissue (EAT) on computed tomography (CT) images, and examine the prognostic significance of auto-quantified left atrium (LA) and EAT volumes for AF. METHODS AND RESULTS: This retrospective study included 334 patients with AF who were referred for catheter ablation (CA) between 2015 and 2017. Atria and EAT volumes were auto-quantified using a pre-trained 3-dimensional (3D) U-Net model from pre-ablation CT images. After adjusting for factors associated with AF, Cox regression analysis was used to examine predictors of AF recurrence. The mean (±SD) age of patients was 56±11 years; 251 (75%) were men, and 79 (24%) had non-paroxysmal AF. Over 2 years of follow-up, 139 (42%) patients experienced recurrence. Diabetes, non-paroxysmal AF, non-pulmonary vein triggers, mitral line ablation, and larger LA, right atrium, and EAT volume indices were linked to increased hazards of AF recurrence. After multivariate adjustment, non-paroxysmal AF (hazard ratio [HR] 0.6; 95% confidence interval [CI] 0.4-0.8; P=0.003) and larger LA-EAT volume index (HR 1.1; 95% CI 1.0-1.2; P=0.009) remained independent predictors of AF recurrence. CONCLUSIONS: LA-EAT volume measured using the auto-quantified 3D U-Net model is feasible for predicting AF recurrence after CA, regardless of AF type.

Catheter ablation in patients with atrial fibrillation and dilated cardiomyopathy.

Introduction: Catheter ablation is an effective and safe strategy for treating atrial fibrillation patients. Nevertheless, studies on the long-term outcomes of catheter ablation in patients with dilated cardiomyopathy are limited. This study aimed to assess the electrophysiological characteristics of atrial fibrillation patients with dilated cardiomyopathy and compare the long-term clinical outcomes between patients undergoing catheter ablation and medical therapy. Method: Patient baseline characteristics and electrophysiological parameters were examined to identify the predictors of atrial fibrillation recurrence following catheter ablation. The clinical outcomes of catheter ablation and medical therapy were compared using the propensity score matched method. Results: A total of 343 patients were enrolled, with 46 in the catheter ablation group and 297 in the medical therapy group. Among the catheter ablation group, 58.7% (n = 27) had persistent atrial fibrillation. The recurrence rate of atrial arrhythmia was 30.4% (n = 14) after an average follow-up duration of 7.7 years following catheter ablation. The only predictive factor for atrial fibrillation recurrence after catheter ablation was the left atrial diameter. When compared to medical therapy, catheter ablation demonstrated significantly better outcomes in terms of overall survival, freedom from heart failure hospitalization, improvement in left ventricular ejection fraction, and a greater reduction in left ventricular diameter and left atrial diameter after propensity score matching. Conclusions: Therefore, catheter ablation proves to be effective in providing long-term control of atrial fibrillation in patients with dilated cardiomyopathy. In addition to standard heart failure care, catheter ablation significantly enhanced both morbidity and mortality outcomes and reversed structural remodeling when compared to heart failure medication alone.

Catheter Ablation in Arrhythmic Cardiac Diseases: Endocardial and Epicardial Ablation.

Arrhythmogenic cardiomyopathy (ACM) is a group of arrhythmogenic disorders of the myocardium that are not caused by ischemic, hypertensive, or valvular heart disease. The clinical manifestations of ACMs may overlap those of dilated cardiomyopathy, complicating the differential diagnosis. In several ACMs, ventricular tachycardia (VT) has been observed at an early stage, regardless of the severity of the disease. Therefore, preventing recurrences of VT can be a clinical challenge. There is a wide range of efficacy and side effects associated with the use of antiarrhythmic drugs (AADs) in the treatment of VT. In addition to AADs, patients with ACM and ventricular tachyarrhythmias may benefit from catheter ablation, especially if they are drug-refractory. The differences in pathogenesis between the various types of ACMs can lead to heterogeneous distributions of arrhythmogenic substrates, non-uniform ablation strategies, and distinct ablation outcomes. Ablation has been documented to be effective in eliminating ventricular tachyarrhythmias in arrhythmogenic right ventricular dysplasia (ARVC), sarcoidosis, Chagas cardiomyopathy, and Brugada syndrome (BrS). As an entity that is rare in nature, ablation for ventricular tachycardia in certain forms of ACM may only be reported through case reports, such as amyloidosis and left ventricular noncompaction. Several types of ACMs, including ARVC, sarcoidosis, Chagas cardiomyopathy, BrS, and left ventricular noncompaction, may exhibit diseased substrates within or adjacent to the epicardium that may be accountable for ventricular arrhythmogenesis. As a result, combining endocardial and epicardial ablation is of clinical importance for successful ablation. The purpose of this article is to provide a comprehensive overview of the substrate characteristics, ablation strategies, and ablation outcomes of various types of ACMs using endocardial and epicardial approaches.