Estimation of conduction velocity vector fields from epicardial mapping data.

This dissertation presents a new method for the estimation of oceanic surface velocity vector fields using multiresolution. Multiresolution is the ability to analyze a signal at various levels of resolution. In this dissertation, wavelet analysis is used to obtain multiresolution. This method requires the use of two sea surface temperature (SST) images of the same region taken within a known time interval. Wavelet analysis is performed in both images to reveal their components at decreasing resolution levels. The comparison of these components at each level yields vector fields representing local displacements of features within the images. These vector fields are smoothed to eliminate noise and to produce coherent vector fields at each resolution level. Vector fields produced with images at levels with higher resolutions are used as refinements to vector fields found at lower resolution levels. Analysis of the operational parameters for the new method are presented in this dissertation. Artificial SST images and NOAA satellite SST images are used to test its accuracy. Comparison with drifter information is also performed. Extensions to the basic algorithm that improve the accuracy of estimations are also discussed. Finally, foreshadowing of the use of the new technique in GOES satellite images and hurricane imagery concludes this dissertation.

Background Alterations in atrial conduction velocity have been implicated in the pathogenesis of atrial arrhythmias, with conduction velocity thought to be slower and more heterogeneous in areas promoting atrial fibrillation. However, clinical studies of conduction velocity are challenging since there are no available platforms that provide researchers and clinicians with the ability to quantify conduction velocity and analyse conduction heterogeneity from electroanatomic mapping data. Purpose In this paper we sought to address these limitations by enhancing the OpenEP Python library by (1) automating calculations using previously-published conduction velocity estimation algorithms; (2) providing an interactive graphical representing of conduction velocity and conduction heterogeneity and (3) implementing a histogram analysis tool to quantify conduction velocity and enable the identification of slow conduction regions. Method Two well-known and previously published methods for calculating cardiac conduction velocity, Triangulation and polynomial surface fitting, were implemented. Conduction velocity estimation was improved further by excluding regions with wave collisions and focal discharges. These regions were identified using the divergence of conduction velocity vector fields, with positive divergence representing focal sources and negative divergence representing areas of collision. Finally, calculated conduction velocities using electrogram data were interpolated over the surface mesh via Radial Basis Function (RBF) interpolation method. All algorithms were implemented in the OpenEP Python library (openep-py), with visualisation tools provided in the complementary graphical interface, EP Workbench. Results An extensible "Analysis" feature was created in openep-py, to provide conduction velocity and divergence calculations which are fully customisable through the graphical interface based on user preferences. The EP Workbench desktop application displays resulting cardiac surface maps to depict calculated conduction velocity and divergence fields, together with conventional activation and voltage maps (Figure 1). The histogram analysis tool can be used to identify regions of slow conduction velocity from electroanatomic mapping data. Using a threshold of <0.3m/s, two slow conducting channels are visualised on the posterior wall of a test case (Figure 2). The tool is not specific to conduction velocity and may also be used to quantify other data types in EP Workbench. Finally, computed conduction velocity and divergence values and surface maps are stored in the standard OpenEP data structure, allowing further analysis following data export. Conclusion We have extended OpenEP to provide a comprehensive set of tools for conduction velocity calculation and analysis which will facilitate investigation of the structural and functional basis of conduction velocity alterations in disease states.

Robust and fast stochastic 4D Flow Vector-field signature technique for quantifying composite flow dynamics from 4D Flow MRI: Application to left atrial flow in atrial fibrillation

Use of approximate entropy measurements to classify ventricular tachycardia and fibrillation

Mechanisms Underlying Epicardial Radiofrequency Ablation to Suppress Arrhythmogenesis in Experimental Models of Brugada Syndrome.

Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders with increasing prevalence. Mechanisms sustaining these arrhythmias are different, and subsequently, the required treatments options differ. Although many algorithms have been developed for differentiating fibrillation from normal sinus rhythm, very few methods exist to differentiate between different forms of AF and VF from surface electrocardiogram (ECG). To address the issue, we propose a novel ECG classification method to differentiate fibrillation that is completely chaotic from forms where it is organized with key driving sites. Differentiating fibrillation organisation from ECGs may aid patient selection, and identify those who may benefit from targeted ablation treatment. Evaluation using real-world data sets based on rat VF model shows that the proposed method could recognise the correct Fibrillation subtype from the single-channel electrocardiogram with an accuracy of 88.89\(\%\).

Velocity of propagation of electrical excitation in the heart is important for the understanding of complex arrhythmias such as ventricular fibrillation (VF). In this paper, we present a method to estimate the conduction velocity of electrical activation wavefronts that are defined to be a particular isovalue of any scalar field, such as electrical activation times, electrical phase, or indeed any other quantity that can be used to determine excitation wavefronts. This general method is based on tracking trajectories of material points that are assumed to be embedded within the wavefronts, whilst the direction of propagation is assumed to be perpendicular to the wavefront. We have derived an explicit expression for the conduction velocity in terms of the spatiotemporal gradients of the scalar field used to define wavefronts. Moreover, although it is often difficult to use activation times to compute conduction velocities during complex VF, we show that other scalar fields such as detrended voltage or electrical phase, which can faithfully represent the electrical activity during fibrillatory conduction, can be used to determine conduction velocities. We demonstrate the application of our method to determine conduction velocities from contact mapping recordings over the entire epicardial surface of the fibrillating pig heart.

Measurement of ventricular electrogram amplitude during intraoperative induction of ventricular tachyarrhythmias

The introduction of autonomous delivery systems is expected to improve productivity in numerous application fields. Since such systems comprise both unmanned and manned units, it is important to control the whole system using appropriate behavioral models of manned vehicles or humans. This work builds on the results of a previous study, where a velocity vector field was used to model human movement, and extends the use of velocity vector fields to the simulation of vehicle behavior by modeling variance in given trajectories. This extension enables the velocity vector field to regenerate an average trajectory with a band and consequently allows one to calculate the vehicle's predicted region in arbitrary future time steps and anomaly detection. These applications are expected to facilitate collision avoidance and should help one to control other applications of unmanned vehicles.

The normal functioning of dual chamber pacemaker-cardioverter defibrillator (AV pacer/ICD) may be affected by oversensing of the farfield R wave (FFRW) by the atrial channel. This study aimed to investigate whether placement of the AV pacer/ICD's atrial lead at a lateral (LAT) wall location compared to a medial (MED) location i.e. the appendage of the right atrium, would reduce the amplitude of FFRWs but not the nearfield atrial electrograms (AEGMs) during sinus rhythm (SR) and ventricular fibrillation (VF). In 17 patients, real time electrograms were recorded during SR and induced VF through the atrial lead initially at the MED and subsequently at the LAT location. In 10 patients the electrograms in SR were also recorded on a computerized data acquisition and recording system at different band-pass filter settings. Although FFRWs were recorded both at MED and LAT locations, they were much smaller, 3.5+/-4.1mm during SR and 1.7+/-2.2mm during VF at the LAT location. At 30-500Hz band-pass filter, lower amplitudes of FFRWs 0.14+/-0.09 mV were recorded at the LAT location. The V/A ratios of the amplitudes of FFRWs and AEGMs were smaller at the LAT location during SR and VF. The nearfield AEGMs were of similar amplitudes at the MED and LAT locations. These data indicate that lower amplitudes of FFRWs are recorded by placement of the atrial lead at the lateral wall of the right atrium. Oversensing of FFRWs may be prevented to improve functioning of the AV pacer-ICD.

Pacemaker-Induced Ventricular Fibrillation

Pathophysiology of atrial fibrillation (AF) remains unclear. Interactions between scar and conduction velocity (CV) and their impact on wavefront propagation in sinus rhythm (SR) and rotational activity burden in AF were evaluated. Local activation times (LATs) and voltage data were obtained from patients undergoing ablation for persistent AF. Omnipolar voltage (OV) and bipolar voltage (BV) data were obtained during AF and SR at pacing intervals of 600 and 250 ms. Local activation times were used to determine CV dynamics and their relationship to the underlying voltage and pivot points in SR. Computational modelling studies were performed to evaluate the impact of CVs and fibrosis on rotational activity burden in AF. Data from 60 patients with a total of 2 768 400 LAT and voltage points were analysed (46 140 ± 5689 points/patient). Voltage determined CV dynamics. Enhanced CV heterogeneity sites were predominantly mapped to low-voltage zones (LVZs) (0.2-0.49 mV) (128/168, 76.2%) rather than LVZs (<0.2 mV) and frequently co-located to pivot points (151/168, 89.9%). Atrial fibrillation OV maps correlated better with SR BV 250 ms than 600 ms maps, thereby representing fixed and functional remodelling. Sinus rhythm maps at 250 ms compared with 600 ms harboured a greater number of pivot points. Increased CV slowing and functional remodelling on computational models resulted in a greater rotational activity burden. Conduction velocity dynamics are impacted by the degree of scar. Conduction velocity heterogeneity and functional remodelling impacts wavefront propagation in SR and rotational activity burden in AF. This study provides insight into the pathophysiology of AF and identifies potential novel ablation targets.

The antiarrhythmic effect of an oral 3-week-pretreatment with oligomer procyanidins derived from Vitis vinifera was investigated on the isolated perfused heart after global no-flow ischemia (procyanidin-treated group: n = 9, control group: n = 13). Hearts were perfused with a modified Krebs-Henseleit solution in which the K+ content was reduced to 3.0 mmol/l in order to lower the fibrillation threshold. Monophasic action potentials in addition to ECG were recorded. The durations of ischemia and reperfusion were 20 and 30 min, respectively. Arrhythmias including ventricular fibrillation (VF), ventricular tachycardia (VT), flutter (Fl) and bradycardia were evaluated. During the reperfusion, irreversible VF occurred in most of control hearts. The incidence of VF (percentage of the hearts in which VF occurred) was lowered by oligomer procyanidins from 84.6 to 55.6 %, and the duration of the episodes of VF (expressed as percentage relative to the total duration) was significantly shortened from 76.1 +/- 27.9 % to 36.6 +/- 40.6 % (p = 0.036). Simultaneously, the percentage of duration of normal sinus rhythm (NSR) increased from 19.5 +/- 30.3 % to 46.2 +/- 35.9 % (n.s.). VF occuring in the procyanidin-treated hearts could be reversed in two hearts within few minutes to a stage of "reversible arrhythmias" consisting of short episodes (1 to 60 s) of either Fl or VT or bradycardia or NSR alternating with each other. LDH (lactate dehydrogenase) release in the first drops appearing from the reperfused heart was significantly reduced in the procyanidin-treated rats (66.7 +/- 36.2 mU/min, n = 8) in comparison to controls (159.7 +/- 79.0 mU/min, n = 10; p = 0.010). These results demonstrate an antiarrhythmic and cytoprotective effect of oral pretreatment with oligomer procyanidins under the given experimental conditions.

We address the problem of tracking points in dense vector fields. Such vector fields may come from computational fluid dynamics simulations, environmental monitoring sensors, or dense point tracking of video data. To track points in vector fields, we capture the distribution of higher-order properties (e.g., properties derived from the gradient of the velocity vector field) in a novel local descriptor called a vector spin-image. Our distribution-based approach has a number of advantages over methods that use topology analysis to track points in vector fields. The local distributions are robust to noise, adaptable to changes in the feature, and can be used to extrapolate the location of features after they have disappeared. We describe the vector spin-image data structure, the higher-order properties we record to track vector field points, and show results of tracking points in the simulated flow through a diesel engine cylinder.

AimsLoss of cell-to-cell communication results in local conduction disorders and directional heterogeneity (LDH) in conduction velocity (CV) vectors, which may be unmasked by premature atrial contractions (PACs). We quantified LDH and examined differences between sinus rhythm (SR) and spontaneous PACs in patients with and without atrial fibrillation (AF).Methods and resultsIntra-operative epicardial mapping of the right and left atrium (RA, LA), Bachmann’s bundle (BB) and pulmonary vein area (PVA) was performed in 228 patients (54 with AF). Conduction velocity vectors were computed at each electrode using discrete velocity vectors. Directions and magnitudes of individual vectors were compared with surrounding vectors to identify LDH. Five hundred and three PACs [2 (1–3) per patient; prematurity index of 45 ± 12%] were included. During SR, most LDH were found at BB and LA [11.9 (8.3–14.9) % and 11.3 (8.0–15.2) %] and CV was lowest at BB [83.5 (72.4–94.3) cm/s, all P < 0.05]. Compared with SR, the largest increase in LDH during PAC was found at BB and PVA [+13.0 (7.7, 18.3) % and +12.5 (10.8, 14.2) %, P < 0.001]; CV decreased particularly at BB, PVA and LA [−10.0 (−13.2, −6.9) cm/s, −9.3 (−12.5, −6.2) cm/s and −9.1 (−11.7, −6.6) cm/s, P < 0.001]. Comparing patients with and without AF, more LDH were found during SR in AF patients at PVA and BB, although the increase in LDH during PACs was similar for all sites.ConclusionLocal directional heterogeneity is a novel methodology to quantify local heterogeneity in CV as a possible indicator of electropathology. Intra-operative high-resolution mapping indeed revealed that LDH increased during PACs particularly at BB and PVA. Also, patients with AF already have more LDH during SR, which becomes more pronounced during PACs.