Project description:The anatomy of the His-Purkinje system has been studied, yet there remains a knowledge gap regarding the impact of His bundle pacing and its electrocardiographic implications. This case report highlights the presence of His-Purkinje system pathology without apparent clues on the surface electrocardiogram (EKG). By observing identical QRS morphology with varying HV intervals resulting from different pacing outputs, we demonstrate the presence of an electrical propagation block within the His bundle.
Project description:We highlight a diagnostic challenge in a patient with dyspnea on exertion due to radiation therapy-induced severe first-degree atrioventricular block and how permanent His bundle pacing was helpful in overcoming these symptoms. (Level of Difficulty: Intermediate.).
Project description:BackgroundLocalisation of the conduction system under fluoroscopy is not easy and the ideal location of the pacing leads in physiological pacing is still being debated.ObjectiveThe primary aim was to assess the lead locations using cardiac CT scan. Secondary aims were clinical outcomes including success and safety of the procedure and lead performance.MethodsOf the 100 consecutive patients who received physiological pacing, 34 patients underwent follow-up cardiac CT scan. The four different types of pacing were identified as His bundle (HBP), para-Hisian, left bundle branch (LBBP), and deep septal pacing.ResultsMost patients had successful HBP via the right atrium (RA) (87.5%) as compared to the right ventricle (RV) (12.5%). Lower thresholds were observed when leads were placed within 2 mm of the junction of the membranous and muscular ventricular septum. Unlike HBP, LBBP was possible at a wide region of the septum and selective capture of individual fascicles was feasible. LBBP showed deeper penetration of leads into the septum, as compared to deep septal pacing (70% vs. 45%). Approximately, 80% of patients did not have an intra-ventricular portion of the membranous septum.ConclusionsThe anterior part of the atrio-ventricular (AV) septum at the junction between the membranous and muscular septum via RA appeared to be the best target to successfully pace His bundle. LBBP was possible at a wide region of the septum and selective capture of individual fascicle was feasible. Adequate depth of penetration of lead was very important to capture the left bundle.
Project description:BackgroundHis-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts.ObjectiveThe purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation.MethodsWe identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset.ResultsThe CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network's performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P <.0001), with an overall accuracy of 75%. The CNN's accuracy in the 17-patient testing set was 67% for S-HBP, 71% for NS-HBP, and 84% for MOC.ConclusionWe demonstrated proof of concept that a neural network can be trained to automate discrimination between HBP ECG responses. When a larger dataset is trained to higher accuracy, automated AI ECG analysis could facilitate HBP implantation and follow-up and prevent complications resulting from incorrect HBP ECG analysis.
Project description:BackgroundHis bundle pacing (HBP) is an alternative to biventricular pacing (BVP) for delivering cardiac resynchronization therapy (CRT) in patients with heart failure and left bundle branch block (LBBB). It is not known whether ventricular activation times and patterns achieved by HBP are equivalent to intact conduction systems and not all patients with LBBB are resynchronized by HBP.ObjectiveTo compare activation times and patterns of His-CRT with BVP-CRT, LBBB and intact conduction systems.MethodsIn patients with LBBB, noninvasive epicardial mapping (ECG imaging) was performed during BVP and temporary HBP. Intrinsic activation was mapped in all subjects. Left ventricular activation times (LVAT) were measured and epicardial propagation mapping (EPM) was performed, to visualize epicardial wavefronts. Normal activation pattern and a normal LVAT range were determined from normal subjects.ResultsForty-five patients were included, 24 with LBBB and LV impairment, and 21 with normal 12-lead ECG and LV function. In 87.5% of patients with LBBB, His-CRT successfully shortened LVAT by ≥10 ms. In 33.3%, His-CRT resulted in complete ventricular resynchronization, with activation times and patterns indistinguishable from normal subjects. EPM identified propagation discontinuity artifacts in 83% of patients with LBBB. This was the best predictor of whether successful resynchronization was achieved by HBP (logarithmic odds ratio, 2.19; 95% confidence interval, 0.07-4.31; p = .04).ConclusionNoninvasive electrocardiographic mapping appears to identify patients whose LBBB can be resynchronized by HBP. In contrast to BVP, His-CRT may deliver the maximum potential ventricular resynchronization, returning activation times, and patterns to those seen in normal hearts.