Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds.

Models of electrical excitation and recovery in the heart have become increasingly detailed, but have yet to be used routinely in the clinical setting to guide personalized intervention in patients. One of the main challenges is calibrating models from the limited measurements that can be made in a patient during a standard clinical procedure. In this work, we propose a novel framework for the probabilistic calibration of electrophysiology parameters on the left atrium of the heart using local measurements of cardiac excitability. Parameter fields are represented as Gaussian processes on manifolds and are linked to measurements via surrogate functions that map from local parameter values to measurements. The posterior distribution of parameter fields is then obtained. We show that our method can recover parameter fields used to generate localised synthetic measurements of effective refractory period. Our methodology is applicable to other measurement types collected with clinical protocols, and more generally for calibration where model parameters vary over a manifold.

Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds.

OBJECTIVE: Local activation time (LAT) mapping of the atria is important for targeted treatment of atrial arrhythmias, but current methods do not interpolate on the atrial manifold and neglect uncertainties associated with LAT observations. In this paper, we describe novel methods to, first, quantify uncertainties in LAT arising from bipolar electrogram analysis and assignment of electrode recordings to the anatomical mesh, second, interpolate uncertain LAT measurements directly on left atrial manifolds to obtain complete probabilistic activation maps, and finally, interpolate LAT jointly across both the manifold and different S1-S2 pacing protocols. METHODS: A modified center of mass approach was used to process bipolar electrograms, yielding a LAT estimate and error distribution from the electrogram morphology. An error distribution for assigning measurements to the anatomical mesh was estimated. Probabilistic LAT maps were produced by interpolating on a left atrial manifold using Gaussian Markov random fields, taking into account observation errors and characterizing LAT predictions by their mean and standard deviation. This approach was extended to interpolate across S1-S2 pacing protocols. RESULTS: We evaluated our approach using recordings from three patients undergoing atrial ablation. Cross-validation showed consistent and accurate prediction of LAT observations both at different locations on the left atrium and for different S1-S2 intervals. SIGNIFICANCE: Interpolation of scalar and vector fields across anatomical structures from point measurements is a challenging problem in biomedical engineering, compounded by uncertainties in measurements and meshes. New methods and approaches are required, and in this paper, we have demonstrated an effective method for probabilistic interpolation of uncertain LAT.

Evaluation of a real-time magnetic resonance imaging-guided electrophysiology system for structural and electrophysiological ventricular tachycardia substrate assessment.

AIMS: Potential advantages of real-time magnetic resonance imaging (MRI)-guided electrophysiology (MR-EP) include contemporaneous three-dimensional substrate assessment at the time of intervention, improved procedural guidance, and ablation lesion assessment. We evaluated a novel real-time MR-EP system to perform endocardial voltage mapping and assessment of delayed conduction in a porcine ischaemia-reperfusion model. METHODS AND RESULTS: Sites of low voltage and slow conduction identified using the system were registered and compared to regions of late gadolinium enhancement (LGE) on MRI. The Sorensen-Dice similarity coefficient (DSC) between LGE scar maps and voltage maps was computed on a nodal basis. A total of 445 electrograms were recorded in sinus rhythm (range: 30-186) using the MR-EP system including 138 electrograms from LGE regions. Pacing captured at 103 sites; 47 (45.6%) sites had a stimulus-to-QRS (S-QRS) delay of ≥40 ms. Using conventional (0.5-1.5 mV) bipolar voltage thresholds, the sensitivity and specificity of voltage mapping using the MR-EP system to identify MR-derived LGE was 57% and 96%, respectively. Voltage mapping had a better predictive ability in detecting LGE compared to S-QRS measurements using this system (area under curve: 0.907 vs. 0.840). Using an electrical threshold of 1.5 mV to define abnormal myocardium, the total DSC, scar DSC, and normal myocardium DSC between voltage maps and LGE scar maps was 79.0 ± 6.0%, 35.0 ± 10.1%, and 90.4 ± 8.6%, respectively. CONCLUSION: Low-voltage zones and regions of delayed conduction determined using a real-time MR-EP system are moderately associated with LGE areas identified on MRI.

Analytical approaches for myocardial fibrillation signals.

Atrial and ventricular fibrillation are complex arrhythmias, and their underlying mechanisms remain widely debated and incompletely understood. This is partly because the electrical signals recorded during myocardial fibrillation are themselves complex and difficult to interpret with simple analytical tools. There are currently a number of analytical approaches to handle fibrillation data. Some of these techniques focus on mapping putative drivers of myocardial fibrillation, such as dominant frequency, organizational index, Shannon entropy and phase mapping. Other techniques focus on mapping the underlying myocardial substrate sustaining fibrillation, such as voltage mapping and complex fractionated electrogram mapping. In this review, we discuss these techniques, their application and their limitations, with reference to our experimental and clinical data. We also describe novel tools including a new algorithm to map microreentrant circuits sustaining fibrillation.

Unraveling the Underlying Arrhythmia Mechanism in Persistent Atrial Fibrillation: Results From the STARLIGHT Study.

BACKGROUND: The mechanisms that initiate and sustain persistent atrial fibrillation are not well characterized. Ablation results remain significantly worse than in paroxysmal atrial fibrillation in which the mechanism is better understood and subsequent targeted therapy has been developed. The aim of this study was to characterize and quantify patterns of activation during atrial fibrillation using contact mapping. METHODS: Patients with persistent atrial fibrillation (n=14; mean age, 61±8 years; ejection fraction, 59±10%) underwent simultaneous biatrial contact mapping with 64 electrode catheters. The atrial electrograms were transformed into phase, and subsequent spatiotemporal mapping was performed to identify phase singularities (PSs). RESULTS: PSs were located in both atria, but we observed more PSs in the left atrium compared with the right atrium (779±302, 552±235; P=0.015). Although some PSs of duration sufficient to complete >1 rotation were detected, the maximum PS duration was only 1150 ms, and the vast majority (97%) of PSs persisted for too short a period to complete a full rotation. Although in selected patients there was evidence of PS local clustering, overall, PSs were distributed globally throughout both chambers with no clear anatomic predisposition. In a subset of patients (n=7), analysis was repeated using an alternative established atrial PS mapping technique, which confirmed our initial findings. CONCLUSIONS: No sustained rotors or localized drivers were detected, and instead, the mechanism of arrhythmia maintenance was consistent with the multiple wavelet hypothesis, with passive activation of short-lived rotational activity. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01765075.

Personalized Models of Human Atrial Electrophysiology Derived From Endocardial Electrograms.

OBJECTIVE: Computational models represent a novel framework for understanding the mechanisms behind atrial fibrillation (AF) and offer a pathway for personalizing and optimizing treatment. The characterization of local electrophysiological properties across the atria during procedures remains a challenge. The aim of this work is to characterize the regional properties of the human atrium from multielectrode catheter measurements. METHODS: We propose a novel method that characterizes regional electrophysiology properties by fitting parameters of an ionic model to conduction velocity and effective refractory period restitution curves obtained by a s1-s2 pacing protocol applied through a multielectrode catheter. Using an in-silico dataset we demonstrate that the fitting method can constrain parameters with a mean error of 21.9 ± 16.1% and can replicate conduction velocity and effective refractory curves not used in the original fitting with a relative error of 4.4 ± 6.9%. RESULTS: We demonstrate this parameter estimation approach on five clinical datasets recorded from AF patients. Recordings and parametrization took approx. 5 and 6 min, respectively. Models fitted restitution curves with an error of ~ 5% and identify a unique parameter set. Tissue properties were predicted using a two-dimensional atrial tissue sheet model. Spiral wave stability in each case was predicted using tissue simulations, identifying distinct stable (2/5), meandering and breaking up (2/5), and unstable self-terminating (1/5) spiral tip patterns for different cases. CONCLUSION AND SIGNIFICANCE: We have developed and demonstrated a robust and rapid approach for personalizing local ionic models from a clinically tractable.

Analysis of lead placement optimization metrics in cardiac resynchronization therapy with computational modelling.

AIMS: The efficacy of cardiac resynchronization therapy (CRT) is known to vary considerably with pacing location, however the most effective set of metrics by which to select the optimal pacing site is not yet well understood. Computational modelling offers a powerful methodology to comprehensively test the effect of pacing location in silico and investigate how to best optimize therapy using clinically available metrics for the individual patient. METHODS AND RESULTS: Personalized computational models of cardiac electromechanics were used to perform an in silico left ventricle (LV) pacing site optimization study as part of biventricular CRT in three patient cases. Maps of response to therapy according to changes in total activation time (ΔTAT) and acute haemodynamic response (AHR) were generated and compared with preclinical metrics of electrical function, strain, stress, and mechanical work to assess their suitability for selecting the optimal pacing site. In all three patients, response to therapy was highly sensitive to pacing location, with laterobasal locations being optimal. ΔTAT and AHR were found to be correlated (ρ < -0.80), as were AHR and the preclinical activation time at the pacing site (ρ ≥ 0.73), however pacing in the last activated site did not result in the optimal response to therapy in all cases. CONCLUSION: This computational modelling study supports pacing in laterobasal locations, optimizing pacing site by minimizing paced QRS duration and pacing in regions activated late at sinus rhythm. Results demonstrate information content is redundant using multiple preclinical metrics. Of significance, the correlation of AHR with ΔTAT indicates that minimization of QRSd is a promising metric for optimization of lead placement.

Beneficial Effect on Cardiac Resynchronization From Left Ventricular Endocardial Pacing Is Mediated by Early Access to High Conduction Velocity Tissue: Electrophysiological Simulation Study.

BACKGROUND: Cardiac resynchronization therapy (CRT) delivered via left ventricular (LV) endocardial pacing (ENDO-CRT) is associated with improved acute hemodynamic response compared with LV epicardial pacing (EPI-CRT). The role of cardiac anatomy and physiology in this improved response remains controversial. We used computational electrophysiological models to quantify the role of cardiac geometry, tissue anisotropy, and the presence of fast endocardial conduction on myocardial activation during ENDO-CRT and EPI-CRT. METHODS AND RESULTS: Cardiac activation was simulated using the monodomain tissue excitation model in 2-dimensional (2D) canine and human and 3D canine biventricular models. The latest activation times (LATs) for LV endocardial and biventricular epicardial tissue were calculated (LVLAT and TLAT), as well the percentage decrease in LATs for endocardial (en) versus epicardial (ep) LV pacing (defined as %dLV=100×(LVLATep-LVLATen)/LVLATep and %dT=100×(TLATep-TLATen)/TLATep, respectively). Normal canine cardiac anatomy is responsible for %dLV and %dT values of 7.4% and 5.5%, respectively. Concentric and eccentric remodeled anatomies resulted in %dT values of 15.6% and 1.3%, respectively. The 3D biventricular-paced canine model resulted in %dLV and %dT values of -7.1% and 1.5%, in contrast to the experimental observations of 16% and 11%, respectively. Adding fast endocardial conduction to this model altered %dLV and %dT to 13.1% and 10.1%, respectively. CONCLUSIONS: Our results provide a physiological explanation for improved response to ENDO-CRT. We predict that patients with viable fast-conducting endocardial tissue or distal Purkinje network or both, as well as concentric remodeling, are more likely to benefit from reduced ATs and increased synchrony arising from endocardial pacing.