Dominant Frequency Maps Research Articles

New evaluation method for defects propagation in toroidal roller bearings using dominant frequency of acoustic emission

ABSTRACT The increased use of roller bearings in recent years has made it vital to develop techniques for Condition Monitoring (CM) of these valuable assets. Toroidal Roller Bearings (TRB) are one of the recent inventions that has revolutionised some industries because of its unique design. In this study, newly produced TRBs were tested using Acoustic Emission (AE), vibration and temperature, on a specially designed test rig. The AE signal was recorded, processed, and analysed using FFT-based methods to transform from the time domain to the frequency domain, and to specify the Dominant Frequency (DF) of each hit in the signal. The result of the analysis was a layout on the time domain of the DFs of all AE hits along with RMSAE and other parameters, this layout was called DF map. The test was divided into three phases, and the DF bands were divided horizontally into three band groups. The aim is to establish a correlation between the phases and DF bands. Knowing the type of defects that are typical for each phase in the test provided insights to what are the DFs of that type. Promising results can be achieved using this measuring method on other types of bearings.

Spatial mapping of the seismic vulnerability index in Kathmandu Valley: insight from dominant frequency and amplification factor

Abstract Kathmandu Valley situated in Nepal has experienced several earthquakes in the past. The expanding population of Kathmandu Valley is driving a significant acceleration in building construction reaching record levels and posing risks to both human lives and the economy, despite this surge in development. This study aimed to spatially map the dominant frequency, amplification factor, and vulnerability index map of Kathmandu Valley, Nepal using ArcGIS. This paper presents the nonlinear response analysis of 225 boreholes using the Gorkha earthquake as input motion and DEEPSOIL software for determining the amplification ratio and dominant frequency. The results revealed a range of values for dominant frequency from 0.08 to 7.65 Hz and soil amplification ratio from 0.13 to 8.14. Furthermore, the seismic vulnerability index was derived from the dominant frequency and soil amplification ratio ranging from 0.22 to 21.84. The resulting maps acquired through this study enable the decision-makers and stakeholders, to prioritize resources and implement targeted measures for enhancing seismic resilience in the region.

Using acoustic emission for condition monitoring of the main shaft bearings in 4-point suspension wind turbine drivetrains

ABSTRACT The continuous growth of wind power technology makes condition monitoring of wind turbine components crucially important for their operational efficiency. The main shaft bearings in wind turbines have been identified as one of the most critical components in the system, especially with the ongoing increase in rotor size and weight. This increase made the 4-point suspension drivetrain more preferable. In this study, we present a novel approach for condition monitoring of the main shaft bearings in a 2 Megawatt wind turbine with 4-point suspension drivetrain using primarily acoustic emission (AE). The focus was on the analysis of time and frequency domains of the AE signal, where the dominant frequency of each AE hit was identified and plotted back in the time domain to create the so-called dominant frequency map in specific time intervals for each bearing. A comparison between the two dominant frequency maps of the two bearings gives valuable insights into the condition of the two bearings. The distinctive nature of the dominant frequency bands in the dominant frequency maps presented promising potential for this method. The presented method is straightforward and can be automated and then integrated into a planned predictive maintenance programme for this wind turbine.

High-resolution spatiotemporal changes in dominant frequency and structural organization during persistent atrial fibrillation.

Analyze changes in frequency activity and structural organization that occur over time with persistent atrial fibrillation (AF). Little is known about the frequency characteristics of the epicardium during transition from paroxysmal to persistent AF. Accurate identification of areas of high dominant frequency (DF) is often hampered by limited spatial resolution. Improvements in electrode arrays provide high spatiotemporal resolution, allowing for characterization of the changes that occur during this transition. AF was induced in adult Yorkshire swine by atrial tachypacing. DF mapping was performed using personalized mapping arrays. Histological analysis and late gadolinium enhanced magnetic resonance imaging were performed to determine structural differences in fibrosis. The left atrial epicardium was associated with a significant increase in DF in persistent AF (6.5 ± 0.2 vs. 7.4 ± 0.5 Hz, P = 0.03). The organization index (OI) significantly decreased during persistent AF in both the left atria (0.3 ± 0.03 vs. 0.2 ± 0.03, P = 0.01) and right atria (0.33 ± 0.04 vs. 0.23 ± 0.02, P = 0.02). MRI analysis demonstrated increased ECV values in persistent AF (0.19 vs 0.34, paroxysmal vs persistent, P = 0.05). Tissue sections from the atria showed increase in fibrosis in pigs with persistent AF compared to paroxysmal AF. Staining demonstrated decreased myocardial fiber alignment and loss of anisotropy in persistent AF tissue. Changes in tissue organization and fibrosis are observed in the porcine model of persistent AF. Alterations in frequency activity and organization index can be captured with high resolution using flexible electrode arrays.

Solving the inverse problem in electrocardiography imaging for atrial fibrillation using various time-frequency decomposition techniques based on empirical mode decomposition: A comparative study.

Electrocardiographic imaging (ECGI) can aid in identifying the driving sources that cause and sustain atrial fibrillation (AF). Traditional regularization strategies for addressing the ECGI inverse problem are not currently concerned about the multi-scale analysis of the inverse problem, and these techniques are not clinically reliable. We have previously investigated the solution based on uniform phase mode decomposition (UPEMD-based) to the ECGI inverse problem. Numerous other methods for the time-frequency analysis derived from empirical mode decomposition (EMD-based) have not been applied to the inverse problem in ECGI. By applying many EMD-based solutions to the ECGI inverse problem and evaluating the performance of these solutions, we hope to find a more efficient EMD-based solution to the ECGI inverse problem. In this study, five AF simulation datasets and two real datasets from AF patients derived from a clinical ablation procedure are employed to evaluate the operating efficiency of several EMD-based solutions. The Pearson's correlation coefficient (CC), the relative difference measurement star (RDMS) of the computed epicardial dominant frequency (DF) map and driver probability (DP) map, and the distance (Dis) between the estimated and referenced most probable driving sources are used to evaluate the application of various EMD-based solutions in ECGI. The results show that for DF maps on all simulation datasets, the CC of UPEMD-based and improved UPEMD (IUPEMD)-based techniques are both greater than 0.95 and the CC of the empirical wavelet transform (EWT)-based solution is greater than 0.889, and the RDMS of UPEMD-based and IUPEMD-based approaches is less than 0.3 overall and the RDMS of EWT-based method is less than 0.48, performing better than other EMD-based solutions; for DP maps, the CC of UPEMD-based and IUPEMD-based techniques are close to 0.5, the CC of EWT-based is 0.449, and the CC of the remaining EMD-based techniques on the SAF and CAF is all below 0.1; the RDMS of UPEMD-based and IUPEMD-based are 0.06∼0.9 less than that of other EMD-based methods for all the simulation datasets overall. On two authentic AF datasets, the Dis between the first 10 real and estimated maximum DF positions of UPEMD-based and EWT-based methods are 212∼1440 less than that of others, demonstrating these two EMD-based solutions are superior and are suggested for clinical application in solving the ECGI inverse problem. On all datasets, EWT-based algorithms deconstruct the signal in the shortest time (no more than 0.12s), followed by UPEMD-based solutions (less than 0.81s), showing that these two schemes are more efficient than others.

Predictors of recurrence of atrial tachyarrhythmias after pulmonary vein isolation by functional and structural mapping of nonparoxysmal atrial fibrillation.

BackgroundThis study aimed to evaluate the predictors of recurrence of atrial tachyarrhythmias by structural and functional mapping: voltage, dominant frequency (DF), and rotor mapping after a pulmonary vein isolation (PVI) in nonparoxysmal atrial fibrillation (AF) patients.MethodsA total of 66 nonparoxysmal AF patients were prospectively investigated. After the PVI, an online real‐time phase mapping system was used to detect the location of rotors with critical nonpassively activated ratios (%NPs) of ≧50% in each left atrial (LA) segment, and high‐DFs of ≧7 Hz were simultaneously mapped. After restoring sinus rhythm, low‐voltage areas (LVAs < 0.5 mV) were mapped using the Advisor HD grid catheter (HDG).ResultsSixty‐four of 66 (97%) AF patients had minimum to mild LVAs regardless of an enlarged LAD and LA volume (45 ± 6.0 mm and 141 ± 29 ml). There were no significant differences in the max and mean DF values and %NPs between the patients with and without recurrent atrial tachyarrhythmias. However, there was a significant difference in the LVA/LA surface area between the patients with and without recurrent atrial tachyarrhythmias (p = .004). Atrial tachyarrhythmia freedom was significantly greater in those with LVAs of ≤3.3% than in those >3.3% after one procedure over 11.6 ± 0.8 months of follow‐up (77.1% vs. 33.3%, p < .001). In a multivariate analysis, the LVA/LA surface area after the PVI (HR 1.079; CI, 1.025–1.135, p = .003) was an independent predictor of AF recurrence.ConclusionsThe predictor of atrial tachyarrhythmia recurrence after the PVI was LVAs rather than DFs and rotors in nonparoxysmal AF patients.

Abstract 14293: Automated Arrhythmia Detection in HiPSC-Derived Cardiac Cell Sheet Models for Drug Testing and Disease Modeling

Introduction: The use of human-induced pluripotent stem cells (hiPSC) derived cardiomyocytes may bring a unique value for drug testing and disease modeling applications. In this project, we developed an automatic and robust arrhythmia detection tool that enables recognition of early-after-depolarizations (EADs) and reentrant activity (spiral waves) in hiPSC-derived cardiac tissue models. Methods and Results: hiPSCs were differentiated into cardiomyocytes, seeded as large-scale hiPSC-derived cardiac cell-sheets (hiPSC-CCSs), loaded with a voltage-sensitive dye, and optically mapped. Arrhythmias were induced either spontaneously, using pacing interventions, or following drug applications. We examined two algorithms to detect spiral wave arrhythmias: optical flow (OF) and dominant frequency (DF). OF enables flow detection through spatial analysis of local velocity vectors (Fig.1 a-d). DF maps depict the frequency with the highest energy in each pixel (Fig.1 e-f). Spiral waves were readily detected by both approaches by the presence of significant diversity in both the frequencies maps (DF) and in the velocity angles (OF). Moreover, in DF maps, the core of the spiral wave (singularity point) could be identified as pixels displaying high dominant frequency as compared to values in other parts of the specimen. (Figure 1). Finally, EADs could be detected using a curve-fitting approach (Fig.1g). Figure 1: (a-d) Consecutive optical map frames (a, c) and velocity vector maps (b, d) of normal (a, b) and a spiral wave (c-d) propagations. (e-f ) DF maps of normal (e) and spiral wave (f) propagations. (g) EAD detection in red. Conclusion: Automatic algorithms were developed to enable robust detection of arrhythmic activity (EADs and spiral waves) in a hiPSC-based cardiac tissue model. This novel approach may bring a unique value to arrhythmia mechanistic studies, high throughput drug screening, and disease modeling.

B-PO04-078 DRIVING MECHANISMS IN PERSISTENT ATRIAL FIBRILLATION DEMONSTRATE MULTI-MONTH STABILITY IN A CANINE MODEL

Previous studies suggest persistent atrial fibrillation (AF) is maintained by focused mechanisms, or drivers, outside the pulmonary veins. Single mapping sessions during AF to locate drivers for ablation have had limited success in improving over pulmonary vein isolation. Little is known about the development of drivers over time, but this development may explain current difficulties in driver-based ablation. To characterize the development of drivers in a canine model of persistent AF. We captured high-density left atrial voltage maps from a rapid-paced canine paced model of persistent AF (n=9, 1 yr. mongrel, 29±3 kg). To assess the progression of AF with time, we conducted these mapping sessions at 1, 3, and 6 months post-implant during AF using an Orion catheter and the Rhythmia mapping system (Boston Scientific). The mapping catheter was held at sites distributed in the atrium for 4 minutes each, such that the entire substrate was well covered. We examined each site for the existence of stable focal and reentrant mechanisms as guided by dominant frequency maps. For each mapping session, we measured 15.5±3.7 sites (n=357) and found an average of 1.9±0.8 drivers (n=39). ANOVA analysis showed the mean number of drivers to be stable over time (p=0.004). While duration of AF is associated with remodeling of the atrial substrate, these results support the surprising finding that the number of active drivers remains stable from the first month through at least 6 months of paced AF. This is promising for ablation as it shows a limited number of driving sites for treatment even as AF develops.

Automatic Extraction of Recurrent Patterns of High Dominant Frequency Mapping During Human Persistent Atrial Fibrillation.

Purpose: Identifying targets for catheter ablation remains challenging in persistent atrial fibrillation (persAF). The dominant frequency (DF) of atrial electrograms during atrial fibrillation (AF) is believed to primarily reflect local activation. Highest DF (HDF) might be responsible for the initiation and perpetuation of persAF. However, the spatiotemporal behavior of DF remains not fully understood. Some DFs during persAF were shown to lack spatiotemporal stability, while others exhibit recurrent behavior. We sought to develop a tool to automatically detect recurrent DF patterns in persAF patients.Methods: Non-contact mapping of the left atrium (LA) was performed in 10 patients undergoing persAF HDF ablation. 2,048 virtual electrograms (vEGMs, EnSite Array, Abbott Laboratories, USA) were collected for up to 5 min before and after ablation. Frequency spectrum was estimated using fast Fourier transform and DF was identified as the peak between 4 and 10 Hz and organization index (OI) was calculated. The HDF maps were identified per 4-s window and an automated pattern recognition algorithm was used to find recurring HDF spatial patterns. Dominant patterns (DPs) were defined as the HDF pattern with the highest recurrence.Results: DPs were found in all patients. Patients in atrial flutter after ablation had a single DP over the recorded time period. The time interval (median [IQR]) of DP recurrence for the patients in AF after ablation (7 patients) decreased from 21.1 s [11.8 49.7 s] to 15.7 s [6.5 18.2 s]. The DF inside the DPs presented lower temporal standard deviation (0.18 ± 0.06 Hz vs. 0.29 ± 0.12 Hz, p < 0.05) and higher OI (0.35 ± 0.03 vs. 0.31 ± 0.04, p < 0.05). The atrial regions with the highest proportion of HDF region were the septum and the left upper pulmonary vein.Conclusion: Multiple recurrent spatiotemporal HDF patterns exist during persAF. The proposed method can identify and quantify the spatiotemporal repetition of the HDFs, where the high recurrences of DP may suggest a more organized rhythm. DPs presented a more consistent DF and higher organization compared with non-DPs, suggesting that DF with higher OI might be more likely to recur. Recurring patterns offer a more comprehensive dynamic insight of persAF behavior, and ablation targeting such regions may be beneficial.

Measuring the sediment thickness in urban areas using H/V spectral ratio method in Batman region, Southeast Turkey

In this study, microtremor records measured with a 3-component seismometer in Batman city center, which was established on the plain, were evaluated for the geological structure of the region and soil forming units. The measurements obtained from the field survey were evaluated with the Geopsy program by using the horizontal/vertical spectral ratio (Nakamura 1989) and the geological condition of the area and soil dominant frequency were determined. Soil characteristics of Batman City, which is geologically located on a plain, was evaluated by finding the loose units in the site with the map consisting of shear wave velocities (VS) found by applying the T = Σ4Hi/Vsi formula of Kanai (1983), which was developed for the soft soil layer on the bedrock, to the dominant frequency values (F0) obtained from the microtremor measured and soil classes corresponding to these values; and depth (H) and shear wave velocities (VS) were found by applying Formula (6) and the soil classes corresponding to these values. The dominant frequency at the measurement points and the lithology of the soil forming units were evaluated together to create dominant frequency maps of the region, and the relationship between the geology of the region and obtained microtremor measurements was discussed.

Abstract 14839: High-resolution Spatiotemporal Changes in Dominant Frequency and Structural Organization During Persistent Atrial Fibrillation

Introduction: Spatiotemporal differences in atrial activity are thought to contribute to the maintenance of atrial fibrillation (AF). While recent evidence has identified changes in dominant frequency (DF) during the transition from paroxysmal to persistent AF, little is known about the frequency characteristics of the epicardium during this transition. The purpose of this study was to perform high-resolution mapping of the atrial epicardium and to characterize changes in frequency activity and structural organization during the transition from paroxysmal to persistent AF. Hypothesis: In a porcine model of persistent AF, we tested the hypothesis that the epicardium undergoes spatiotemporal changes in atrial activity and structural organization during persistent AF. Methods: Paroxysmal and persistent AF was induced in adult Yorkshire swine by atrial tachypacing. Atrial morphology was segmented from magnetic resonance imaging and high-resolution patient-specific flexible mapping arrays were 3D printed to match the epicardial contours of the atria. Epicardial activation and DF mapping was performed in four paroxysmal and four persistent AF animals using personalized mapping arrays. Histological analysis was performed to determine structural differences between paroxysmal and persistent AF. Results: The left atrial epicardium was associated with a significant increase in DF between paroxysmal and persistent AF (6.5 ± 0.2 vs. 7.4 ± 0.5 Hz, P = 0.03). High-resolution spatiotemporal mapping identified organized clusters of DF during paroxysmal AF which were lost during persistent AF. The development of persistent AF led to structural remodeling with increased atrial epicardial fibrosis. The organization index (OI) significantly decreased during persistent AF in both the left atria (0.3 ± 0.03 vs. 0.2 ± 0.03, P = 0.01) and right atria (0.33 ± 0.04 vs. 0.23 ± 0.02, P = 0.02). Conclusions: In the porcine model of persistent AF, the epicardium undergoes structural remodeling with increased epicardial fibrosis, reflected by changes in atrial organization index and dominant frequency.

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.

Highest dominant frequency and rotor positions are robust markers of driver location during noninvasive mapping of atrial fibrillation: A computational study

Dominant frequency (DF) and rotor mapping have been proposed as noninvasive techniques to guide localization of drivers maintaining atrial fibrillation (AF). The purpose of this study was to evaluate the robustness of both techniques in identifying atrial drivers noninvasively under the effect of electrical noise or model uncertainties. Inverse-computed DFs and phase maps were obtained from 30 different mathematical AF simulations. Epicardial highest dominant frequency (HDF) regions and rotor location were compared with the same inverse-computed measurements after addition of noise to the ECG, size variations of the atria, and linear or angular deviations in the atrial location inside the thorax. Inverse-computed electrograms (EGMs) individually correlated poorly with the original EGMs in the absence of induced uncertainties (0.45 ± 0.12) and were worse with 10-dB noise (0.22 ± 0.11), 3-cm displacement (0.01 ± 0.02), or 36° rotation (0.02 ± 0.03). However, inverse-computed HDF regions showed robustness against induced uncertainties: from 82% ± 18% match for the best conditions, down to 73% ± 23% for 10-dB noise, 77% ± 21% for 5-cm displacement, and 60% ± 22% for 36° rotation. The distance from the inverse-computed rotor to the original rotor was also affected by uncertainties: 0.8 ± 1.61 cm for the best conditions, 2.4 ± 3.6 cm for 10-dB noise, 4.3 ± 3.2 cm for 4-cm displacement, and 4.0 ± 2.1 cm for 36° rotation. Restriction of rotor detections to the HDF area increased rotor detection accuracy from 4.5 ± 4.5 cm to 3.2 ± 3.1 cm (P <.05) with 0-dB noise. The combination of frequency and phase-derived measurements increases the accuracy of noninvasive localization of atrial rotors driving AF in the presence of noise and uncertainties in atrial location or size.

An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping

Background and ObjectiveOptimal targets for persistent atrial fibrillation (persAF) ablation are still debated. Atrial regions hosting high dominant frequency (HDF) are believed to participate in the initiation and maintenance of persAF and hence are potential targets for ablation, while rotor ablation has shown promising initial results. Currently, no commercially available system offers the capability to automatically identify both these phenomena. This paper describes an integrated 3D software platform combining the mapping of both frequency spectrum and phase from atrial electrograms (AEGs) to help guide persAF ablation in clinical cardiac electrophysiological studies. Methods30s of 2048 non-contact AEGs (EnSite Array, St. Jude Medical) were collected and analyzed per patient. After QRST removal, the AEGs were divided into 4s windows with a 50% overlap. Fast Fourier transform was used for DF identification. HDF areas were identified as the maximum DF to 0.25Hz below that, and their centers of gravity (CGs) were used to track their spatiotemporal movement. Spectral organization measurements were estimated. Hilbert transform was used to calculate instantaneous phase. ResultsThe system was successfully used to guide catheter ablation for 10 persAF patients. The mean processing time was 10.4 ± 1.5min, which is adequate comparing to the normal electrophysiological (EP) procedure time (120∼180min). ConclusionsA customized software platform capable of measuring different forms of spatiotemporal AEG analysis was implemented and used in clinical environment to guide persAF ablation. The modular nature of the platform will help electrophysiological studies in understanding of the underlying AF mechanisms.

Novel approaches for quantitative electrogram analysis for intraprocedural guidance for catheter ablation: A case of a patient with persistent atrial fibrillation.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that causes stroke affecting more than 2.3 million people in the US and is increasing in prevalence due to ageing population causing a new global epidemic. 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. The authors developed novel electrogram analysis methods and validated using optical mapping data from isolated rabbit hearts to accurately identify rotor pivot points. The purpose of this study was to assess the feasibility of generating patient-specific 3D maps for intraprocedural guidance for catheter ablation using intracardiac electrograms from a persistent AF patient using novel electrogram analysis methods. A persistent AF patient with clinical appointment for AF ablation was recruited for this study with IRB approval. 1055 electrograms throughout the left and right atrium were obtained for offline analysis with the novel approaches such as multiscale entropy, multiscale frequency, recurrence period density entropy, kurtosis and empirical mode decomposition to generate patient specific 3D maps. 3D Shannon Entropy, Renyi Entropy and Dominant frequency maps were also generated for comparison purposes along with local activation time and complex fractionated electrogram analysis maps. Patient specific 3D maps were obtained for each of the different approach. The 3D maps indicate potential active sites outside the PVI region. However, presence of rotors cannot be confirmed and validation of these approaches is required on a larger dataset. Conventional catheter mapping system can be used for generating patient specific 3D maps with short time series analysis using the novel approaches.

An Analytical Model for the Effects of the Spatial Resolution of Electrode Systems on the Spectrum of Cardiac Signals

It has been suggested that the spatiotemporal characteristics of complex cardiac arrhythmias can be extracted from the spectrum of cardiac signals. However, the analysis of simple bioelectric models indicates that the spectrum of cardiac signals can be affected by the spatial resolution of the electrode system. In this paper, we derive exact measurement transfer functions relating the spectrum of cardiac signals to the spatiotemporal dynamics of cardiac sources. The analysis of the measurement transfer bandwidths for dynamics with different degrees of spatiotemporal correlation shows that as the spatial resolution decreases, the bandwidth of the measurement transfer function decreases until it reaches a constant value. Moreover, this transition from decreasing to constant values is determined by the degree of spatiotemporal correlation of the underlying cardiac source. Motivated by our analytical results, we investigate in a realistic computer simulation environment the impact of additive noise on the accuracy of body-surface dominant frequency (DF) maps. Our simulation results show that meaningful DF values are obtained on those locations where the analytical measurement transfer bandwidth is wide. These findings suggest that the accuracy of body-surface DF maps can be limited by the low spatial resolution of body-surface electrode systems.

Invasive management of atrial fibrillation

AbstractAtrial fibrillation (AF), the most common sustained cardiac arrhythmia, affects 1% of the general population with increased incidence in the elderly population and is an important contributor to population morbidity and mortality. This article reviews the current invasive management of AF. Pulmonary vein isolation (PVI) is the cornerstone of current ablation techniques for the treatment of paroxysmal atrial fibrillation (AF). Despite proven PVI, a subset of patients still experience recurrent arrhythmia, mostly due to a higher prevalence of non‐PV triggers. PVI is associated with worse arrhythmia‐free survival in patients with persistent AF than those with paroxysmal AF. Accumulating data have shown that elimination of atrial fibrillation 9 (AF) sources (rotors or rotational activity, drivers, electrograms with continuous activity) should be the goal in persistent AF ablation. Pulmonary vein isolation, linear lesions, and complex fractionated atrial electrograms (CFAEs) ablation have shown limited efficacy in patients with persistent AF. A combined approach using voltage, CFAEs, and dominant frequency (DF) mapping may be helpful for the identification of AF sources and subsequent focal substrate modification. The fibrillatory activity is maintained by intramural reentry centered on fibrotic patches. Voltage mapping may assist in the identification of fibrotic areas. Stable rotors display the higher DF and possibly drive AF. Furthermore, the single rotor is usually consistent with organized AF electrograms without fractionation. It is therefore quite possible that rotors are located at relatively “healthy islands” within the patchy fibrosis. This is supported by the fact that high DF sites have been negatively correlated with the amount of fibrosis. CFAEs are located in areas adjacent to high DF. In conclusion, patchy fibrotic areas displaying the maximum DF along with high organization index and the lower fractionation index are potential targets of ablation. Prospective studies are required to validate the efficacy of substrate modification in left atrial ablation outcomes.Answer questions and earn CME: https://wileyhealthlearning.com/Activity2/4469458/Activity.aspx

Noninvasive Imaging of High-Frequency Drivers and Reconstruction of Global Dominant Frequency Maps in Patients With Paroxysmal and Persistent Atrial Fibrillation.

Highest dominant-frequency (DF) drivers maintaining atrial fibrillation (AF) activities are effective ablation targets for restoring sinus rhythms in patients. This study aims to investigate whether AF drivers with highest activation rate can be noninvasively localized by means of a frequency-based cardiac electrical imaging (CEI) technique, which may aid in the planning of ablation strategy and the investigation of the underlying mechanisms of AF. A total of seven out of 13 patients were recorded with spontaneous paroxysmal or persistent AF and analyzed. The biatrial DF maps were reconstructed by coupling 5-s BSPM with CT-determined patient geometry. The CEI results were compared with ablation sites and DFs found from BSPMs. CEI imaged left-to-right maximal frequency gradient (7.42 ± 0.66Hz versus 5.85 ± 1.2Hz, LA versus RA, p<0.05) in paroxysmal AF patients. Patients with persistent AF were imaged with a loss of the intrachamber frequency gradient and a dispersion of the fast sources in both chambers. CEI was able to capture the AF behaviors, which were characterized by short-term stability, dynamic transition, and spatial repetition of the highest DF sites. The imaged highest DF sites were consistent with ablation sites in patients studied. The frequency-based CEI allows localization of AF drivers with highest DF and characterization of the spatiotemporal frequency behaviors, suggesting the possibility for individualizing treatment strategy and advancing understanding of the underlying AF mechanisms. The establishment of noninvasive imaging techniques localizing AF drivers would facilitate management of this significant cardiac arrhythmia.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

BackgroundAreas with high frequency activity within the atrium are thought to be ‘drivers’ of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation.MethodsAutoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach.Results3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz).ConclusionWe have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

Abstract 15890: Spatiotemporal Analysis of Phase and Frequency Dynamics in Human Persistent Atrial Fibrillation

There is increasing focus on understanding the substrates that maintain persistent atrial fibrillation (persAF) based on dominant frequency (DF) sources and phase singularity points (PS). In this study we aimed to combine these two parameters and study the relationship between them to depict the complex spatiotemporal patterns of fibrillation. For 9 patients with longstanding persAF (duration: 34 ± 25 months) undergoing left atrial (LA) ablation, noncontact array catheter (EnSite Array, St. Jude Medical) was used to collect virtual unipolar electrograms (EGMs) simultaneously from 2048 nodes on the LA. After QRST subtraction, 3D DF maps were obtained through the fast Fourier Transform applied simultaneously to each individual EGM. DF was defined within the range of 4-10Hz (4s time window; 87.5% overlap; 30s/patient). Highest DF (HDF) regions for each individual window were defined as any LA geometry nodes where the calculated DF was within 0.25 Hz of the maximum DF value registered in the window. In order to correlate these HDF locations with PS, phase maps were constructed using the Hilbert transform approach and the locations of PS and its respective chirality (+ clockwise; - anticlockwise) were identified applying an automatic PS detection algorithm. A statistical majority of PSs (92.5%, p&lt;0.001) were distributed outside the HDF regions. There was a relationship between PSs and the HDF regions such that PSs of opposite chirality influence the propagation of HDF. This was observed for all patients and in 72.1 (± 10.5) % of the total windows. The influence of direction of HDF movement by PSs of opposite chirality was observed 12 (±9) times for each window. A case illustration is presented on Figure 1. Our analysis suggests an organised behaviour of PS of opposite chirality and HDF regions travelling between them. Once an electrophysiological relationship is established, the spatiotemporal behaviour of PS and HDF could provide alternative ablation strategies for AF.