Propagation Maps Research Articles

Explaining slow seizure propagation with white matter tractography.

Epileptic seizures recorded with stereo-EEG can take a fraction of a second or several seconds to propagate from one region to another. What explains such propagation patterns? We combine tractography and stereo-EEG to determine the relationship between seizure propagation and the white matter architecture and to describe seizure propagation mechanisms. Patient-specific spatiotemporal seizure propagation maps were combined with tractography from diffusion imaging of matched subjects from the Human Connectome Project. The onset of seizure activity was marked on a channel-by-channel basis by two board-certified neurologists for all channels involved in the seizure. We measured the tract connectivity (number of tracts) between regions-of-interest pairs among the seizure onset zone, regions of seizure spread and non-involved regions. We also investigated how tract-connected the seizure onset zone is to regions of early seizure spread compared with regions of late spread. Comparisons were made after correcting for differences in distance. Sixty-nine seizures were marked across 26 patients with drug-resistant epilepsy; 11 were seizure free after surgery (Engel IA) and 15 were not (Engel IB-Engel IV). The seizure onset zone was more tract-connected to regions of seizure spread than to non-involved regions (P < 0.0001); however, regions of seizure spread were not differentially tract-connected to other regions of seizure spread compared with non-involved regions. In seizure-free patients only, regions of seizure spread were more tract-connected to the seizure onset zone than to other regions of spread (P < 0.0001). Over the temporal evolution of a seizure, the seizure onset zone was significantly more tract-connected to regions of early spread compared with regions of late spread in seizure-free patients only (P < 0.0001). By integrating information on structure, we demonstrate that seizure propagation is likely to be mediated by white matter tracts. The pattern of connectivity between seizure onset zone, regions of spread and non-involved regions demonstrates that the onset zone might be largely responsible for seizures propagating throughout the brain, rather than seizures propagating to intermediate points, from which further propagation takes place. Our findings also suggest that seizure propagation over seconds might be the result of a continuous bombardment of action potentials from the seizure onset zone to regions of spread. In non-seizure-free patients, the paucity of tracts from the presumed seizure onset zone to regions of spread suggests that the onset zone was missed. Fully understanding the structure-propagation relationship might eventually provide insight into selecting the correct targets for epilepsy surgery.

Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: A deep learning-based line detection approach

Stiffness measurement using shear wave propagation velocity has been the most common non-invasive method for liver fibrosis assessment. The velocity is captured through a trace recorded by transient ultrasonographic elastography, with the slope indicating the velocity of the wave. However, due to various factors such as noise and shear wave attenuation, detecting shear wave trajectory on wave propagation maps is a challenging task. In this work, we made the first attempt to use deep learning methods for shear wave trajectory detection on wave propagation maps. Specifically, we adopted five deep learning models in this task and evaluated them by using a well-acknowledged metric based on EA-Angular-Score (EAA) and task-specific metric based on Young s-Score (Ys) in the line-detection field. Furthermore, we proposed an end-to-end framework based on a Transformer and Hough transform, named Transformer-enhanced Hough Transform (TEHT). It took a wave propagation map as input image and directly output the slope of the shear wave trajectory. The framework extracts multi-scale local features from wave propagation maps, employs a deformable attention mechanism for feature fusion, identifies the target line using the Hough transform’s voting mechanism, and calculates the contribution of each scale through channel attention. Wave propagation maps from 68 patients were utilized in this study, with manual annotation performed by a rater who was trained as a radiologist, serving as the reference value. The evaluation revealed that the SLNet model exhibited F-measure of EA and Ys values as 40.33 % and 40.72 %, respectively, while the TEHT model showed F-measure of EA and Ys values as 80.96 % and 98.00 %, respectively. TEHT yielded significantly better performance than other deep learning models. Moreover, TEHT demonstrated strong concordance with the gold standard, yielding R2 values of 0.967 and 0.968 for velocity and liver stiffness, respectively. The present study therefore suggests the application of the TEHT model for assessing liver fibrosis owing to its superiority among the five deep learning models.

Exploration of peak frequency mapping for ventricular tachycardia ablation. Identification of critical isthmus zones during substrate mapping

Abstract Background/Introduction The ability to classify and differentiate between near field and far-field components of intracardiac signals is a key element in identifying critical arrhythmogenic substrate during ventricular tachycardia (VT) ablation. Near Field algorithms based on omnipolar electrograms enable detection and automation of true localised signals providing unique insights into substrate characteristics. This novel feature identifies localised signal peak frequency (PF) which can be displayed across different voltage ranges. Purpose/Aims The significance of PF mapping in the context of VT ablation is limited and its utility in the identification of the critical diastolic isthmus zone (IZ) is not known. The aim of this study is to explore the utilisation of PF mapping during VT ablation and evaluate whether significant differences in PF occur within areas of interest and critical components of the VT circuit during substrate mapping. Methods All patients underwent VT ablation using the EnSite™ X mapping system with the HDGrid omnipolar mapping catheter. Only cases with both high density sinus rhythm (SR) substrate maps and VT activation maps with clear identification of the IZ were included. VT activation and propagation maps were generated and the diastolic IZ was superimposed onto the SR substrate map. PF analysis was performed retrospectively. Surface area, omnipolar voltage and PF of the maps were measured in the SR substrate maps and co-localised with the critical IZ of the VT circuit as identified in the VT activation maps. Analysis of PF was conducted across different voltage ranges: healthy myocardium (&amp;gt;1.5mV), scar (1.5-0.5mV) and dense scar (0.5-0.1mV). Sensitivity and specificity measurements were made within segments of the IZ and non-isthmus zones and depicted as ROC curves. Results 55 patients underwent VT ablation over a 12-month period, with a total of 18 fulfilling the inclusion criteria. Mean age was 70 (±12.5years) with an average ejection fraction of 36%. The overall PF of the SR substrate maps was 121.85±26.85 Hz, compared to 162.22±46.22Hz within the IZ (p=0.002). Within the low voltage scar region, the overall PF was 120.86±33.24Hz compared to 188.32±81.36Hz within the IZ (p=0.003). No significant difference in PF was observed within healthy myocardium (112.70±52.06 Hz) compared to components of the IZ within the &amp;gt;1.5mV range (157.61±136.11Hz), p=0.207. The AUC for PF within the overall substrate map and co-localisation with the IZ was 0.67, and 0.73 within low voltage zones (&amp;lt;1.5mV). Conclusions PF mapping may identify critical components of the VT circuit during SR substrate mapping and its utilisation may compliment established substrate mapping approaches. PF guided ablation strategies require further evaluation in future prospective studies.

Quantifying local cardiac substrate heterogeneity from high density recordings: an experimental study

Abstract Background and Purpose High-density (HD) grid catheters offer enhanced local electrical conduction characterization, owing to their unique grid arrangement. This arrangement enables the generation of orientation-independent EGMs, termed omnipolar EGMs (oEGMs), overcoming limitations associated with traditional unipolar and bipolar EGMs. This innovation holds potential for differentiating healthy tissue from scarred or arrhythmogenic areas. In this study, we introduce a novel metric, the Vector Field Heterogeneity (VFH), designed to quantify the heterogeneity of propagation wavefronts in local vector maps derived from oEGMs. Methods We developed and validated the VFH metric through a combination of simulations and experiment conducted on Langendorff-perfused rabbit hearts. Simulations involved creating a model that generated 100,000 simulated maps exhibiting various levels of disorganization. For experimental data, 68 propagation maps were utilized, including 29 from basal recordings, 39 from recordings with stimulation (4 or 6Hz), from five Langendorff-perfused rabbit hearts at 37ºC, using a multielectrode mapping catheter with 128 electrodes spaced 1mm apart. The VFH metric, based on vector field theory (see figure 2), was computed and compared to the widely adopted the Spatial Inhomogeneity Index (SI) from Statistical analysis was then performed to assess the distribution of heterogeneity values. Results The analysis of the VFH metric through simulations revealed a linear increase in VFH values with disorganization up to a 45º angle, followed by a plateau. Different catheter grid sizes demonstrated that larger grids reduced the standard deviation, with the VFH metric converging to a lower value of approximately 0.62 for larger grids. Experimental data indicated that for a 4x4 grid, VFH values averaged 0.35 without stimulation and decreased to 0.11 with stimulation. The VFH metric consistently outperformed the SI index in binary classification of basal vs stimulated conditions, as evidenced by higher Area Under Curve (AUC) values in both Receiver Operating Characteristic (ROC) and Precision-Recall (PR) analyses across various catheter sizes. For example, in the 4x4 grid, the AUROC for the VFH metric was 0.9752 compared to 0.8311 for the SI index, showcasing the VFH metric’s superior accuracy in assessing cardiac wavefront heterogeneity (see figure 2). Conclusion Vector Field Heterogeneity (VFH) emerges as an effective tool for characterizing cardiac tissue. It successfully differentiates between stimulated and non-stimulated tissue, accurately representing progressive disorganization in simulated maps. The VFH metric demonstrates superiority over the established Spatial Inhomogeneity (SI) index, making it a reliable parameter for assessing cardiac heterogeneity, especially on small high-density grids. It holds promise for clinical use in studying and understanding the cardiac substrate during arrhythmic conditions.Figure 1.Abstract Figure.Figure 2.Methods and Results.

Comparing Flood Damages to an Industrial Region in Turkey Using Several Methods

Floods are one of the disasters that cause the greatest damage to social life, living health, economy and environment. This paper reveals the calculation of the economic damage of the commercial areas located near the creek due to floods in Sakarya, Dinsiz Stream. In this study, first, flood propagation maps were produced according to 50, 100, 200 and 500 years of flood flow periods that may occur in the study area. The HECRAS program was used to produce the flood maps and a 2D model was created from these maps, water level maps were obtained and then depth damage curves were used to figure out the economic losses leading to flood. In addition to the Huizinga, van Eck and Kok, ICBR, Pistrika and Jonkman flood damage assessment methods, which are frequently used in the literature, the HAZUS-MH method was used to calculate the economic losses that may occur in commercial areas. While HAZUS has functions that make separate calculations for each commercial sector, in other methods, calculations are made over the total area without sector discrimination. In addition, HAZUS has more detailed ranges of flooding water depths and therefore the calculation of damage rates corresponding to water depths can be done with higher precision than other methods. According to the data obtained as a result of the study, the losses exceeded million euros in all methods, while the highest values were in the Pistrika and Jonkman methods.

Left bundle branch pacing with and without anodal capture: impact on ventricular activation pattern and acute haemodynamics.

Left bundle branch pacing (LBBP) can deliver physiological left ventricular activation, but typically at the cost of delayed right ventricular (RV) activation. Right ventricular activation can be advanced through anodal capture, but there is uncertainty regarding the mechanism by which this is achieved, and it is not known whether this produces haemodynamic benefit. We recruited patients with LBBP leads in whom anodal capture eliminated the terminal R-wave in lead V1. Ventricular activation pattern, timing, and high-precision acute haemodynamic response were studied during LBBP with and without anodal capture. We recruited 21 patients with a mean age of 67 years, of whom 14 were males. We measured electrocardiogram timings and haemodynamics in all patients, and in 16, we also performed non-invasive mapping. Ventricular epicardial propagation maps demonstrated that RV septal myocardial capture, rather than right bundle capture, was the mechanism for earlier RV activation. With anodal capture, QRS duration and total ventricular activation times were shorter (116 ± 12 vs. 129 ± 14 ms, P < 0.01 and 83 ± 18 vs. 90 ± 15 ms, P = 0.01). This required higher outputs (3.6 ± 1.9 vs. 0.6 ± 0.2 V, P < 0.01) but without additional haemodynamic benefit (mean difference -0.2 ± 3.8 mmHg compared with pacing without anodal capture, P = 0.2). Left bundle branch pacing with anodal capture advances RV activation by stimulating the RV septal myocardium. However, this requires higher outputs and does not improve acute haemodynamics. Aiming for anodal capture may therefore not be necessary.

Ultrasound imaging of lung disease and its relationship to histopathology: An experimentally validated simulation approach.

Lung ultrasound (LUS) is a widely used technique in clinical lung assessment, yet the relationship between LUS images and the underlying disease remains poorly understood due in part to the complexity of the wave propagation physics in complex tissue/air structures. Establishing a clear link between visual patterns in ultrasound images and underlying lung anatomy could improve the diagnostic accuracy and clinical deployment of LUS. Reverberation that occurs at the lung interface is complex, resulting in images that require interpretation of the artifacts deep in the lungs. These images are not accurate spatial representations of the anatomy due to the almost total reflectivity and high impedance mismatch between aerated lung and chest wall. Here, we develop an approach based on the first principles of wave propagation physics in highly realistic maps of the human chest wall and lung to unveil a relationship between lung disease, tissue structure, and its resulting effects on ultrasound images. It is shown that Fullwave numerical simulations of ultrasound propagation and histology-derived acoustical maps model the multiple scattering physics at the lung interface and reproduce LUS B-mode images that are comparable to clinical images. However, unlike clinical imaging, the underlying tissue structure model is known and controllable. The amount of fluid and connective tissue components in the lung were gradually modified to model disease progression, and the resulting changes in B-mode images and non-imaging reverberation measures were analyzed to explain the relationship between pathological modifications of lung tissue and observed LUS.

Noninvasive ECG imaging of the intrinsic atrial pacemaker and atrial activation in surgically repaired or palliated congenital heart disease.

Sinus node location, function, and atrial activation are often abnormal in patients with congenital heart disease (CHD),due to anatomical, surgical, and acquired factors. We aimed to perform noninvasive electrocardiographic imaging (ECGI)of the intrinsic atrial pacemaker and atrial activation in patients with surgically repaired or palliated CHD, compared with control patients with structurally normal hearts. Atrial ECGI was performed in eightCHD patients with prespecified diagnoses (Fontan circulation, dextro transposition of the great arteries post Mustard/Senning, tetralogy of Fallot), and three controls. Activation and propagation maps were constructed in presenting rhythm. Wavefront propagation was analyzed to identify (1) intrinsic atrial pacemaker breakout site, (2) morphological right atrial (RA) activation pattern, (3) morphological left atrial (LA) breakout sites (i.e., interatrial connections), (4) LA activation pattern, and (5) putative lines of block. Physiologically appropriate atrial activation and propagation maps were able to be constructed. In the majority of patients, atrial breakouts were in keeping with the sinus node, observed in a crescent-shaped distribution from the anterior superior vena cava to the posterior RA. Ectopic atrial pacemaker sites were demonstrated in the atriopulmonary (AP) Fontan patient (very diffuse posterolateral RA) and Mustard patient (very posterior RA competing with a low RA focus). RA propagation was laminar in controls, but suggested either a line of block or conduction slowing consistent with an atriotomy scar in the tetralogy of Fallot (TOF) patients. Putative lines of block were more complex and RA propagation more abnormal in the atrial switch and AP Fontan patients, compared with the TOF patients. RA activation in the extracardiac Fontan patients was relatively laminar. Earliest LA breakout was most commonly observed in the region of Bachmann's Bundle in both controls and CHD patients, except for posterior LA breakouts in two patients. LA activation was typically more homogeneous than RA activation in CHD patients. ECGI can be utilized to create a noninvasive mapping model of atrial activation in postsurgical CHD, demonstrating atrial pacemaker location, putative lines of block and interatrial connections. Once validated invasively, this may have clinical implications in predicting risk of sinus node dysfunction and atrial arrhythmias, or in guiding catheter ablation.

PO-01-138 NON-INVASIVE 3-D MAPPING (ECGI) OF MACRO-REENTRANT ATRIAL ARRHYTHMIAS

Peri-valvular atrial arrhythmias are the most common macro-reentrant mechanism seen in both de-novo and repeat atrial fibrillation (AF) ablations. Standard 12-lead ECG’s poorly predict tachycardia mechanisms especially post AF ablation. Identifying the mechanism of tachycardia non-invasively could help in procedural planning, expedite the invasive procedure, and identify critical areas sustaining persistent AF in patients with concomitant AF. The objective was to determine if ECGi could identify the mechanism of atrial flutters in patients with or without prior AF ablations. 30 patients (11 de-novo, 19 prior ablation) underwent non-invasive propagation and phase mapping (CardioInsight, Medtronic, Inc) and intracardiac bi-atrial high-density activation mapping (HD Grid and Precision, Abbott Medical). An 8-segment model (RA lateral, RA anterior, CTI, Septum, LA anterior, LA lateral, CS, LA posterior) was used for directionality in the propagation maps, and a 9-segment model for phase map analysis was used for presence and localization of ‘rotational hinge points’ which can occur with wavefronts moving in different directions within close proximity. The precise tachycardia mechanism (counterclockwise (CCW) or clockwise (CW) and cavo-tricuspid isthmus (CTI) or mitral isthmus (MI) dependent) was determined by intracardiac activation maps, entrainment, and confirmed with termination by ablation. Directionality in a region was deemed concordant if non-invasive and intracardiac maps matched or was declared discordant/indeterminate. A total of 31 macro-reentrants maps were analyzed: 16 CCW-CTI; 7 CW-CTI; 4 CCW-MI; 4 CW-MI. Regional directional concordance percentages shown in theTable. A total of 30/31 phase maps identified at least one region as a 'rotational hinge point', with 26/31 maps showing paired 'hinge points'. Location of rotations are shown in the Figure. ECGi can be used in macro-reentant atrial arrhythmias to determine directionality of activation with best concordance on the lateral walls of both atria. In our study, 97% of peri-valvular atrial flutters had at least one 'rotational hinge point' with 84% showing them paired representing macro-reentant circuit. Posterior LA wall rotational area was present in all peri-mitral flutters. Additionally, paired 'hinge points' with lateral atrial wall directionality were the best determinants of the macro-reentant mechanism.Tabled 1Directional ConcordanceRA LatRA AntCTISeptumLA AntLA LatCSLA PostCCW-CTI88%69%88%44%44%--50%--CW-CTI71%43%71%43%43%--29%--CCW-MI100%50%--75%75%100%100%50%CW-MI100%60%--40%40%80%80%20% Open table in a new tab

Mesh generation for underwater acoustic modeling with KRAKEN

Underwater sound modeling is applied in several environmental studies, from assessing underwater noise induced by offshore wind farms to the influence of climate change on ocean temperature. One of the most well-known underwater acoustics models is KRAKEN, an open-source code requiring a mesh to simulate 3D environments. This paper presents OMesh2KRAKEN, a software toolkit that uses OceanMesh2D to generate unstructured meshes for KRAKEN based on realistic environmental data. Two practical study cases in the North Atlantic are presented and discussed. In addition, an idealized 3D shallow water wedge was simulated. Practically, OMesh2KRAKEN can assist in implementing underwater acoustic modeling studies from deep waters to nearshore regions where, for instance, sound propagation maps are required. Indeed, higher mesh resolutions may be required for areas with complex bathymetric features. In these cases, the new tool presents several advantages as it automatically implements different mesh resolutions in areas of interest and prepares the respective environmental files for acoustic computations.

Risk Associations between Vehicular Traffic Noise Exposure and Cardiovascular Diseases: A Residential Retrospective Cohort Study.

Environmental noise can induce detrimental health effects such as cardiovascular disease (CVD). The relationship between vehicular traffic noise pollution and CVD was investigated through a retrospective residential cohort study in the city of Pisa. Four exposure classes were defined for noise pollution, using noise propagation maps. The association between noise exposures and cause-specific mortality or hospitalization of the subjects of the cohort was calculated using the hazard ratio (HR) for night and day through a multiple time-dependent and sex-specific Cox regression adjusting for age, the socio-economic deprivation index, and traffic air pollution. Mortality excess for CVD and risk trends for a 1 decibel noise increment were observed among the most exposed women (mortality: HRnightclass4 1.15 (1.03–1.28); Trendnight 1.007 (1.002–1.012); HRdayclass4 1.14 (1.02–1.27); Trendday 1.008 (1.003–1.013)), particularly for ischaemic disease (mortality: Trendnight 1.008 (0.999–1.017); Trendday 1.009 (0.999–1.018)) and cerebrovascular disease (mortality: HRnightclass3 1.23 (1.02–1.48), HRdayclass3 1.24 (1.03–1.49)). Hospitalization analyses confirm mortality results. A decreased risk for hospitalization was also observed among the most exposed men (HRdayclass4 0.94 (0.88–1.01), particularly for ischaemic disease (HRnightclass4 0.90 (0.80–1.02); HRdayclass4 0.86 (0.77–0.97)) and cerebrovascular disease (HRnightclass4 0.89 (0.78–1.01)). Authors recommend the adoption of prevention measures aimed at mitigating noise and the activation of a monitoring of the risk profile in the Pisa population updating both the residential cohort and health data.

Initial experience using a novel algorithm to calculate omnipolar electrograms using a high-density grid-style catheter

Abstract Funding Acknowledgements Type of funding sources: None. Background/Introduction A novel mapping algorithm recently became available in Europe and select countries in the Asia Pacific region. EnSite Omnipolar Technology (OT) utilizes the Advisor HD Grid Mapping Catheter, Sensor Enabled (HD Grid) to calculate electrograms in 360 degrees from two bipolar and three unipolar electrograms acquired from a triangular set of three electrodes. This software also enables calculation of wavefront characteristics including maximum voltage, activation direction and wave speed. Procedural characteristics and clinical utilization of this novel software have not yet been reported. Purpose To examine the clinical utility and procedural characteristics associated with the use of this novel mapping algorithm among participating centers. Methods Acute procedural data were prospectively collected in 386 cases at 52 centers utilizing the newly approved mapping software in the initial phases of commercialization in Europe and the Asia Pacific region. Procedural characteristics recorded included indication for mapping/ablation, navigation mode, mapping reference, and maps and tools used to diagnose/locate ablation targets. Results A total of 14 indications for mapping and ablation were represented including AF, atypical flutter, and VT (Table 1). VoXel (magnetic primary) navigation mode was used in most cases (n=325, 84%). The CS catheter was used as the map reference in 280 cases (73%). A variety of workflows were used with OT to diagnose and locate ablation targets including voltage maps (n=275, 71%), LAT maps (n=226, 59%), OT activation vectors (n=124, 32%), propagation maps (n=94, 24%), and sparkle maps (n=69, 18%); note: total exceeds 100%, multiple workflows per case observed. EnSite LiveView Dynamic Display (LiveView) was used in 129 cases (33%) to diagnose and locate ablation targets, including 28 (22%) where OT activation vectors were used with LiveView. Several benefits of OT were reported including rapid identification of ablation target(s) (n=133, 35%), higher point density (n=82, 21%), better signals (n=69, 18%), and improved procedure efficiency (n=48, 12%). Conclusion(s) Initial experience with this novel mapping software in Europe and the Asia-Pacific region illustrated utility in a variety of arrhythmias to diagnose and locate ablation targets. The use of OT provided several benefits including rapid identification of ablation targets and higher point density, however further examination of its impact on procedural efficiencies and acute outcomes is likely warranted.

PO-639-08 IDENTIFICATION OF CONDUCTION PATTERNS DURING ATRIAL FIBRILLATION USING ARTIFICIAL INTELLIGENCE: HOLISTIC FULL CHAMBER VIEW

Atrial fibrillation (AF) is thought to be maintained by reentrant and focal driver regions that may have some spatial-temporal stability. Recently, several cardiac mapping systems have implemented algorithms for automatic detection of these arrhythmogenic conduction patterns (CPs) during AF. Many of these algorithms divide the atrium into overlapping patches, sequentially analyzing each patch with the driver identification algorithms. Patch-based analyses may misrepresent local CPs as the number and trajectory of wavefronts entering and leaving the analyzed patch are uncertain. However, when a holistic view of chamber-wide activation is used, machine learning algorithms can ubiquitously identify arrhythmogenic CPs. Develop and evaluate a machine learning approach that can automatically identify and locate arrhythmogenic CPs. Propagation maps of clinical AF from nine patients were transformed into a 2D image space using conformal mapping, and these images were used to train and evaluate a UNet architecture model. Rotational and focal CPs were identified by the AcQTrack algorithm (Acutus Medical) and manually confirmed. The clinical dataset was supplemented with eikonal simulations of focally (n=400) and rotationally driven (n=200) AF, where the time and location of the rotational and focal drivers were randomized and known. The UNet architecture was trained using five of the clinical AF cases (n=7,880 frames) and simulated AF (200 focal and 100 rotational simulations, n=14,380 frames). A test set, consisting of five clinical AF cases (n=6,172 frames) and simulated AF (200 focal and 100 rotational simulations, n=14382 frames), were independently used to evaluate the model performance. The UNet model accurately detected the time and location of arrhythmogenic CPs in the atrium - Clinical AF DICE 0.91 and Simulated AF DICE 0.98. The presented machine learning approach can accurately identify and locate arrhythmogenic targets. It has potential to overcome limited view problem in detecting arrhythmogenic targets that is inherent problem of patch-based heuristic algorithms.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Application of dynamic display technology to identify gaps after pulmonary vein isolation in catheter ablation of atrial fibrillation

BackgroundThe identification of post pulmonary vein isolation (PVI) gaps by activation and voltage maps is time-consuming. This study aimed to investigate the characteristics, efficiency and accuracy of LiveView dynamic display module (EnSite™ Dynamic Display; Abbott, Abbott Park, IL, USA) in unmasking post PVI gaps and conduction block line. MethodTwenty four patients with paroxysmal atrial fibrillation (PAF) who failed to achieve first-pass PVI or with recurrent PAF were enrolled. Ninety-six pulmonary veins (PVs) were evaluated, and gaps were identified in 25 (26.0%) PVs. The gap location was confirmed by activation and propagation maps; 110 frames on gaps and 118 frames on block lines were analyzed by using LiveView module. We defined isochronal crowding in the local activation time (LAT) mode as three colors between two adjacent electrodes. Each frame was classified as with or without isochronal crowding in LAT mode and one/continuous color or isochronal discontinuity in reentrant mode. The gray color inside the PVs was considered to represent conduction block. ResultThe isochronal crowding could be found on both gap and block line in LAT mode, whereas isochronal discontinuity only presented on the block line in reentrant mode. The sensitivity and specificity of isochronal discontinuity or gray color in reentrant mode to identify block line were 61.0% and 100%, respectively. The sensitivity and specificity of isochronal crowding or gray color in LAT mode to identify block line were 71.2% and 71.8%, respectively. ConclusionReentrant mode in LiveView module is very specific in identifying block lines. We proposed an efficient, practical algorithm to differentiate the block line from PV gaps.

A Novel Predictor for Exploring PM2.5 Spatiotemporal Propagation by Using Convolutional Recursive Neural Networks

&lt;p&gt;The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micro particles could spread rapidly from their source to residential areas, increasing the risk of respiratory disease if exposed for long periods. However, the existing prediction systems do not take into account the geographical correlation among neighboring nodes spatially and temporally resulting in loss of important information, lack of PM2.5 propagation resolution, and lower forecasting accuracy. In this paper, a novel scheme is proposed to generate propagation heat maps of PM2.5 prediction by using spatiotemporal datasets. In this scheme, the deep learning model is implemented to extract spatiotemporal features on these datasets. This research was conducted by using the dataset of air quality monitoring systems in Taiwan. Moreover, the robust model based on the convolutional recursive neural network is presented to generate the propagation maps of PM2.5 concentration. This study develops an intelligence-based predictor by using Convolutional Recursive Neural Network (CRNN) model for predicting the PM2.5 propagation with uncertain spread and density. It is also one of key technologies of software and hardware co-design for massive Internet of Things (IoT) applications. Finally, the proposed model the proposed model provides accurate predictive results over time by taking into account the spatiotemporal relationship among sensory nodes in order to give a prediction solution for the massive IoT deployment based on green communication.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Bayesian network-based root cause analysis and fault pathway identification in complex industrial processes

Real-time root cause identification (RCI) of faults or abnormal events in industries gives plant personnel the opportunity to address the faults before they progress and lead to failure. RCI in industrial systems must deal with their complex behavior, variable interactions, corrective actions of control systems and variability in faulty behavior. Bayesian networks (BNs) is a data-driven graph-based method that utilizes multivariate sensor data generated during industrial operations for RCI. Bayesian networks, however, require data discretization if data contains both discrete and continuous variables. Traditional discretization techniques such as equal width (EW) or equal frequency (EF) discretization result in loss of dynamic information and often lead to erroneous RCI. To deal with this limitation, we propose the use of a dynamic discretization technique called Bayesian Blocks (BB) which adapts the bin sizes based on the properties of data itself. In this work, we compare the effectiveness of three discretization techniques, namely EW, EF and BB coupled with Bayesian Networks on generation of fault propagation (causal) maps and root cause identification in complex industrial systems. We demonstrate the performance of the three methods on the industrial benchmark Tennessee-Eastman (TE) process. For two complex faults in the TE process, the BB with BN method successfully diagnosed correct root causes of the faults, and reduced redundancy (up to 50%) and improved the propagation paths in causal maps compared to other two techniques.

Influence of transport noise on living environment in New Moscow

The article considers problems of increasing traffic noise in the territory of New Moscow. The increase in traffic flow during the reconstruction of the Kaluga highway led to the expansion of the acoustic discomfort zone. The actual norms of permissible noise levels were violated in many low–rise buildings settlements of New Moscow. The study object was the settlement of Desenovskoe, as the inhabitants of settlement began to note the increase in discomfort associated with the reconstruction of the highway. However, there were no protective measures for this settlement according to the reconstruction plan. Students under the guidance of Moscow state University of Civil Engineering lecturers carried out instrumental measurements and analysis of the traffic noise level. A comprehensive detailed approach to measurement is distinctive feature of this research. 28 characteristic measuring points were chosen in the territory of the settlement and on its border. The location of the points was chosen taking into the lie of the ground and the distribution of the traffic flow. The measurements were carried out in parallel along the Kaluga highway, on access roads and inside Desenovskoe settlement. Instrumental research was conducted both in the daytime and at night. The daily measurements were carried out on Monday and Friday (the days of the greatest congestion of highways in this locality), night measurements were on Wednesday. In addition, the intensity and composition of the traffic flow were calculated. Equivalent and maximum sound levels in dBA, and the average and maximum sound pressure levels in dB were determined by the results of the studies and based on calculations. Significant norms’ deviations for the permissible noise level for populated areas were revealed both for the daytime and for the nighttime period. These results became the basis for creating noise propagation maps and determining zones of acoustic discomfort in Desenovskoe settlement. The zone of acoustic discomfort spread about 400 m deep into the territory of the settlement. Half of the residents were in the zone of acoustic discomfort.

B-PO05-096 USING REENTRANT MODE IN A REAL-TIME DYNAMIC SOFTWARE (LIVEVIEW) IN IDENTIFYING PV GAPS AND CONDUCTION BLOCKS DURING PV ISOLATION

The identification of post pulmonary vein isolation (PVI) gap by traditional activation and voltage maps are time-consuming. To investigate the characteristics, efficiency and accuracy of LiveView, a novel dynamic software, in identifying the post PVI gaps and block lines. Patients with PAF who failed to achieve first-pass PVI and with recurrent PAF were enrolled. The gap location was confirmed by activation and propagation maps. Of 25 PVs with gaps, 110 frames on gaps and 124 frames on conduction block lines were analyzed by using LiveView (EnSiteTM Dynamic Display). We defined isochronal crowding in the LAT mode as 3 colors between 2 adjacent electrodes. Each frame was classified as with or without isochronal crowding in LAT mode and one color or continuous color or isochronal discontinuity in reentrant mode. The gray color seen inside the pulmonary veins was considered to represent conduction block. Presentations of gap and block line in LiveView are shown in table 1. LAT mode demonstrated isochronal crowding on both the gap and block line, but reentrant mode showed isochronal discontinuity only on the block line (figure 1A). The sensitivity and specificity of isochronal discontinuity or gray color in reentrant mode to identify block line were 56.45% and 100%, respectively. The sensitivity and specificity of isochronal crowding or gray color in LAT mode to identify block line were 50.8% and 64.5%, respectively. Reentrant mode in LiveView is more accurate than LAT mode in identifying block lines at PV. We proposed an efficient, practical algorithm to differentiate the block line from PV gaps during AF ablation procedure (Figure 1B).

Topic-Emotion Propagation Mechanism of Public Emergencies in Social Networks.

The information propagation of emergencies in social networks is often accompanied by the dissemination of the topic and emotion. As a virtual sensor of public emergencies, social networks have been widely used in data mining, knowledge discovery, and machine learning. From the perspective of network, this study aims to explore the topic and emotion propagation mechanism, as well as the interaction and communication relations of the public in social networks under four types of emergencies, including public health events, accidents and disasters, social security events, and natural disasters. Event topics were identified by Word2vec and K-means clustering. The biLSTM model was used to identify emotion in posts. The propagation maps of topic and emotion were presented visually on the network, and the synergistic relationship between topic and emotion propagation as well as the communication characteristics of multiple subjects were analyzed. The results show that there were similarities and differences in the propagation mechanism of topic and emotion in different types of emergencies. There was a positive correlation between topic and emotion of different types of users in social networks in emergencies. Users with a high level of topic influence were often accompanied by a high level of emotion appeal.

Diagnostic Performance of 2-D Shear-Wave Elastography with Propagation Maps and Attenuation Imaging in Patients with Non-Alcoholic Fatty Liver Disease

We aimed to investigate the diagnostic performance of new 2-D shear-wave elastography (SWE) with propagation maps and attenuation imaging (ATI) for quantification of fibrosis and steatosis in non-alcoholic fatty liver disease (NAFLD). Consecutive patients with NAFLD and healthy volunteers underwent liver stiffness measurement and steatosis quantification by means of vibration-controlled transient elastography coupled with the controlled attenuation parameter as the reference and by 2-D shear-wave elastography (2-D-SWE) with propagation maps and ATI as the investigational methods. We included 232 participants (164 in the NAFLD group and 68 in the healthy control group): 51.7%/49.3% women/men; mean age, 54.2 ± 15.2 y; mean body mass index, 29.4 ± 6.5 kg/m2. Significant correlations were found between 2-D-SWE and vibration-controlled transient elastography (r = 0.71, p < 0.0001) and between ATI and the controlled attenuation parameter (r = 0.72, p < 0.0001). NAFLD-specific 2-D-SWE liver stiffness measurement cutoffs were as follows—F ≥ 2: 7.9 kPa (area under the curve [AUC] = 0.91); F ≥ 3: 10 kPa (AUC = 0.92); and F = 4: 11.4 kPa (AUC = 0.95). For steatosis, the best cutoffs by ATI were as follows—S1 = 0.73 dB/cm/MHz (AUC = 0.86); S2 = 0.76 dB/cm/MHz (AUC = 0.86); and S3 = 0.80 dB/cm/MHz (AUC = 0.83). According to Baveno VI criteria, the optimal 2-D-SWE liver stiffness measurement for diagnosing liver cirrhosis is 15.5 kPa (AUC = 0.94), and for ruling out compensated advanced chronic liver disease it is 9.2 kPa (AUC = 0.92). To conclude, 2-D-SWE with propagation maps and ATI is reliable for quantification of liver fibrosis and steatosis in patients with NAFLD.