Novel therapies for hypertension and associated cardiovascular risk

University of Minnesota Ph.D. dissertation. August 2018. Major: Biomedical Engineering. Advisor: Alena Talkachova. 1 computer file (PDF); xvii, 134 pages.This thesis is comprised of two parts. The first part investigates a novel therapy, vagus nerve stimulation, for hypertension and hypertension-induced heart disease. Hypertension impacts over 1 billion people worldwide, and clinical management is challenging. Left uncontrolled, high blood pressure can significantly increase the risk of cardiovascular events. The majority of hypertensive patients are treated with anti-hypertensive drugs to control blood pressure, but many limitations exist including resistant hypertension, inability to tolerate therapy, and non-compliance with the medication regime. For these patients, an alternative approach is needed to control blood pressure. Recently, the imbalance in the autonomic nervous system, evident in hypertension, has been the target of novel device-based therapies such as vagus nerve stimulation. The main goal of this research is to evaluate the efficacy of vagus nerve stimulation to treat hypertension and hypertension-induced heart disease. This thesis investigates the impact of vagus nerve stimulation on disease progression, survival, and cardiovascular remodeling in Dahl salt-sensitive hypertensive rats. Overall, the results of this work provide evidence for the beneficial therapeutic effects of vagus nerve stimulation in hypertension and motivate future studies to optimize therapy parameters and further understand therapeutic mechanisms. The second part of this thesis focuses on atrial fibrillation and the evaluation of new mapping techniques for improving rotor localization for ablation procedures. Currently, success rates for ablation procedures for non-paroxysmal atrial fibrillation are low and require repeat procedures or a lifetime of pharmacological agents to reduce the risk of stroke. Improved signal processing techniques for mapping electrical activity in the atrium can help further our understanding of the generation and maintenance of atrial fibrillation and ultimately improve ablation procedure success rates and terminate the arrhythmia. The main goal of this work was to validate new signal processing techniques – multiscale frequency, kurtosis, Shannon entropy, and multiscale entropy – to identify regions of abnormal electrical activity. The results of this work demonstrate improved accuracy of these novel techniques in mapping rotors in cardiac arrhythmias and motivates further studies evaluating more complex arrhythmias and human intracardiac electrograms

Novel approaches for quantitative electrogram analysis for rotor identification: Implications for ablation in patients with atrial fibrillation

University of Minnesota Ph.D. dissertation. May 2017. Major: Biomedical Engineering. Advisor: Elena Tolkacheva. 1 computer file (PDF); xxviii, 349 pages + 4 audio/video filesAtrial fibrillation (AF) is the most common sustained cardiac arrhythmia that causes stroke affecting more than 2.3 million people in the US. Catheter ablation with pulmonary vein isolation (PVI) to terminate AF is successful for paroxysmal AF but suffers limitations with persistent AF patients as current mapping methods cannot identify AF active substrates outside of PVI region. Recent evidences in the mechanistic understating of AF pathophysiology suggest that ectopic activity, localized re-entrant circuit with fibrillatory propagation and multiple circuit re-entries may all be involved in human AF. Accordingly, the hypothesis that rotor is an underlying AF mechanism is compatible with both the presence of focal discharges and multiple wavelets. Rotors are stable electrical sources which have characteristic spiral waves like appearance with a pivot point surrounded by peripheral region. Targeted ablation at the rotor pivot points in several animal studies have demonstrated efficacy in terminating AF. The objective of this dissertation was to develop robust spatiotemporal mapping techniques that can fully capture the intrinsic dynamics of the non-stationary time series intracardiac electrogram signal to accurately identify the rotor pivot zones that may cause and maintain AF. In this thesis, four time domain approaches namely multiscale entropy (MSE) recurrence period density entropy (RPDE), kurtosis and intrinsic mode function (IMF) complexity index and one frequency domain approach namely multiscale frequency (MSF) was proposed and developed for accurate identification of rotor pivot points. The novel approaches were validated using optical mapping data with induced ventricular arrhythmia in ex-vivo isolated rabbit heart with single, double and meandering rotors (including numerically simulated data). The results demonstrated the efficacy of the novel approaches in accurate identification of rotor pivot point. The chaotic nature of rotor pivot point resulted in higher complexity measured by MSE, RPDE, kurtosis, IMF and MSF compared to the stable rotor periphery that enabled its accurate identification. Additionally, the feasibility of using conventional catheter mapping system to generate patient specific 3D maps for intraprocedural guidance for catheter ablation using these novel approaches was demonstrated with 1055 intracardiac electrograms obtained from both atria’s in a persistent AF patient. Notably, the 3D maps did not provide any clinically significant information on rotor pivot point identification or the presence of rotors themselves. Validation of these novel approaches is required in large datasets with paroxysmal and persistent AF patients to evaluate their clinical utility in rotor identification as potential targets for AF ablation