Incessant tachycardia in a patient with advanced heart failure and left ventricular assist device: What is the mechanism?

AbstractWe present a case of incessant wide-complex tachycardia in a patient with left-ventricular assist device, and discuss the differential diagnosis with an in-depth analysis of the intracardiac tracings during the invasive electrophysiologic study, including interpretation of the relative timing of the fascicular signals during tachycardia and in sinus rhythm, and interpretation of pacing and entrainment maneuvers

Accepted and presented at The Design of Medical Devices Conference (DMD2016)

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a prognostic marker for stroke, heart failure, and even death Successful ablation therapy to terminate AF requires a highly reliable technique to determine ablation sites using raw intra-atrial electrograms of AF patients. Hence, there is a clear need for a robust spatiotemporal mapping technology that can accurately identify the rotor pivot points in a patient-specific manner, which is the motivation for this research. Recently, a novel entropy-based approach was used to identify the rotor pivot point using optical mapping data from rabbit heart [4]. This approach was also used to generate 3D Shannon entropy maps for a persistent AF patient using raw intra-atrial electrograms demonstrating the feasibility to identify rotor pivot points outside the pulmonary vein (PV) region. However, challenges still remain to robustly map and more precisely confirm the exact location of rotor pivot points for AF ablation. It is known that the DF of a rotor is the same throughout the entire spatial area occupied by the rotor and therefore cannot accurately identify the rotor pivot point. This method uses a Fourier transform to calculate the DF and is therefore limited to a single frequency. In contrast, we hypothesize that the chaotic nature of the rotor at the pivot point yields various frequency components. In this work, the authors propose and demonstrate a novel multiscale frequency (MSF) approach that takes into account the contribution from various frequencies to yield valuable information regarding the rotor pivot point, thus allowing for its identification. We validate the feasibility of this technique to identify the pivot point of rotors using optical mapping data from isolated rabbit hearts with induced ventricular tachycardia (VT). Methods Novel MSF Approach. Band-pass quadrature filters are robust for estimating local multiscale information, such as the energy, phase, radial frequency, and orientation/angular frequency. The Hilbert transform operation transforms a real-valued signal to analytic signal with no negative frequencies, and its utility with the quadrature filter can yield MSF information by weighting the various frequency components. In this work, eight log-Gabor/normal filters were designed and used with a relative filter bandwidth B of 2ͱ2, one octave apart as described in Ref. where q i is the output of the ith log-Gabor filter, and q 0 is the center frequency of the first log-Gabor filter Optical Mapping Data From Isolated Rabbit Hearts. Optical Optical mapping experiments were performed with IACUC approval on isolated rabbit hearts which were put in the Langendorffperfusion system, and voltage-sensitive dye di-4-ANEPPS (5 lg/mL) was added to the perfusate. After staining, 532 nm green laser was used to illuminate the epicardial surface of the heart. Fluorescence intensity was captured with two 12-bit CCD cameras, which run at 600 frames per second with 64 Â 64 pixel resolution. VT was induced via burst pacing, and phase movies of the rotors were obtained from optical mapping recordings. The phase movies from one rabbit heart with a known pivot point were used in this work, shown in Result

Mapping and ablation procedures for the treatment of ventricular tachycardia

<p><b>Introduction:</b> Ventricular tachycardia (VT) may occur in the presence or absence of structural heart disease. Given that the management of VT hinges on the presence of symptoms and risk of sudden cardiac death (SCD), the main treatment goals are elimination of symptoms (including frequent implantable cardioverter defibrillator [ICD] therapies) and prevention of SCD. Unfortunately, medical management is suboptimal in a significant proportion of patients. As such, ablative therapy plays a prominent role in the treatment of ventricular tachycardia.</p> <p><b>Areas covered:</b> In this review, we will discuss various VT disorders that are encountered in patients with and without structural heart disease. Further, we will highlight salient features regarding mapping and ablation of the various VT syndromes. Finally, we will discuss what lies on the horizon for VT ablation.</p> <p><b>Expert commentary:</b> Meticulous mapping should aim to find the region that is most likely to be successful and least likely to result in a complication. Although recognition of the various mechanisms of VT, familiarity with different methods to mapping and ablation, and awareness of potential limitations of current approaches is critical, a thorough understanding of the fundamental principles and nuances of each facet within EP is required to ensure optimal outcomes for our patients.</p

A Data-Driven Preprocessing Framework for Atrial Fibrillation Intracardiac Electrocardiogram Analysis

Atrial Fibrillation (AF) is the most common cardiac arrhythmia. Signal-processing approaches are widely used for the analysis of intracardiac electrograms (iEGMs), which are collected during catheter ablation from patients with AF. In order to identify possible targets for ablation therapy, dominant frequency (DF) is widely used and incorporated in electroanatomical mapping systems. Recently, a more robust measure, multiscale frequency (MSF), for iEGM data analysis was adopted and validated. However, before completing any iEGM analysis, a suitable bandpass (BP) filter must be applied to remove noise. Currently, no clear guidelines for BP filter characteristics exist. The lower bound of the BP filter is usually set to 3–5 Hz, while the upper bound (BP¯th) of the BP filter varies from 15 Hz to 50 Hz according to many researchers. This large range of BP¯th subsequently affects the efficiency of further analysis. In this paper, we aimed to develop a data-driven preprocessing framework for iEGM analysis, and validate it based on DF and MSF techniques. To achieve this goal, we optimized the BP¯th  using a data-driven approach (DBSCAN clustering) and demonstrated the effects of different BP¯th on subsequent DF and MSF analysis of clinically recorded iEGMs from patients with AF. Our results demonstrated that our preprocessing framework with BP¯th = 15 Hz has the best performance in terms of the highest Dunn index. We further demonstrated that the removal of noisy and contact-loss leads is necessary for performing correct data iEGMs data analysis

Robotic-Assisted Epicardial Pacemaker Lead Placement

Patients experiencing altered interventricular conduction delay and congestive heart failure often witness an improved quality of life and enhanced ventricular function through biventricular pacing therapies (1). However, intravascular pacemaker leads can lead to complications such as superior vena cava (SVC) syndrome, an infrequent yet significant issue following pacemaker lead implantation. In these instances, the alternative option of intravascular lead removal followed by surgical epicardiac pacemaker lead implantation becomes prominent. The traditional method for placing epicardial pacemaker leads involves sternotomy. However, alternative options, including thoracotomy and thoracoscopic procedures with or without robotic assistance, are also available (2). Robotic assistance in implanting epicardial pacemaker leads is a secure and effective technique, providing advanced visualization and precision for accurately targeting the optimal pacing site (2,3).In this video, the authors share their experience with robotic-assisted epicardial pacemaker lead placement in two clinical scenarios, resulting in successful outcomes in both a first-time and redo setting.The first patient, a thirty-seven-year-old female, was pacemaker dependent and developed SVC syndrome with narrowing and stenosis of the subclavian vein and innominate SVC junction. With a history of pneumothorax and pleurodesis on the right hemithorax and a preference to avoid sternotomy, surgeons offered a robotically assisted left-sided pacemaker placement. The surgical plan included previous lead extraction, subclavian and innominate balloon venoplasty, and robotic epicardial pacemaker lead placement. All procedures concluded without complications, with two leads implanted in the left atrial appendage and two in the lateral wall of the left ventricle. The postoperative course was uneventful, leading to discharge on postoperative day two.The second patient, a fifty-year-old male with a prior sternotomy for atrial septal defect repair, had a dual chamber permanent pacemaker with the right lead requiring reimplantation due to device endocarditis and complicated by SVC syndrome. The patient required an atrial pacemaker lead so surgeons dissected the pericardium off the atrium using robotic cautery and blunt dissection, securing two atrial leads to the atrium. The pericardium was then closed. The procedure proceeded without complications, with two epicardial leads successfully implanted in the right atrial wall. The postoperative course was uneventful, resulting in discharge on postoperative day one.Reference(s)1. Derose JJ Jr, Belsley S, Swistel DG, Shaw R, Ashton RC Jr. Robotically assisted left ventricular epicardial lead implantation for biventricular pacing: the posterior approach. Ann Thorac Surg. 2004 Apr;77(4):1472-4.2. Bhatt AG, Steinberg JS. Robotic-Assisted Left Ventricular Lead Placement. Heart Fail Clin. 2017 Jan;13(1):93-103.3. DeRose JJ, Ashton RC, Belsley S, Swistel DG, Vloka M, Ehlert F, et al. Robotically assisted left ventricular epicardial lead implantation for biventricular pacing. J Am Coll Cardiol. 2003 Apr 16;41(8):1414-9.</p