ECG Feature Importance Rankings: Cardiologists vs. Algorithms.

Feature importance methods promise to provide a ranking of features according to importance for a given classification task. A wide range of methods exist but their rankings often disagree and they are inherently difficult to evaluate due to a lack of ground truth beyond synthetic datasets. In this work, we put feature importance methods to the test on real-world data in the domain of cardiology, where we try to distinguish three specific pathologies from healthy subjects based on ECG features comparing to features used in cardiologists' decision rules as ground truth. We found that the SHAP and LIME methods and Chi-squared test all worked well together with the native Random forest and Logistic regression feature rankings. Some methods gave inconsistent results, which included the Maximum Relevance Minimum Redundancy and Neighbourhood Component Analysis methods. The permutation-based methods generally performed quite poorly. A surprising result was found in the case of left bundle branch block, where T-wave morphology features were consistently identified as being important for diagnosis, but are not used by clinicians.

Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European heart rhythm association and European society of cardiology working group on ecardiology in collaboration with the heart rhythm society, Asia pacific heart rhythm society, Latin American Heart rhythm society and computing in cardiology

Abstract We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (I) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (I) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e. g. catheter­electrode combinations) for signal processing (e. g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology.

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Local Electrical Impedance Mapping of the Atria: Conclusions on Substrate Properties and Confounding Factors.

The treatment of atrial fibrillation and other cardiac arrhythmias as a major cause of cardiovascular hospitalization has remained a challenge predominantly for patients with severely remodeled substrate. Individualized ablation strategies are extremely important both for pulmonary vein isolation and subsequent ablations. Current approaches to identifying arrhythmogenic regions rely on electrogram-based features such as activation time and voltage. Novel technologies now enable clinical assessment of the local impedance as tissue property. Previous studies demonstrated its use for ablation monitoring and indicated its potential to differentiate healthy substrate, scar, and pathological tissue. This study investigates the potential of local electrical impedance-based substrate mapping of the atria for human in-vivo data. The presented pipeline for impedance mapping particularly contains options for dealing with undesirable effects originating from cardiac motion, catheter motion, or proximity to other intracardiac devices. Bloodpool impedance was automatically determined as a patient-specific reference. Full-chamber, left atrial impedance maps were drawn up from interpolating the measured impedances to the atrial endocardium. Finally, the origin and magnitude of oscillations of the raw impedance recording were probed into. The most dominant reason for exclusion of impedance samples was the loss of endocardial contact. With median elevations above the bloodpool impedance between 29 and 46 Ω, the impedance within the pulmonary veins significantly exceeded the remaining atrial walls presenting median elevations above the bloodpool impedance between 16 and 20 Ω. Previous ablation lesions were distinguished from their surroundings by a significant drop in local impedance while the corresponding regions did not differ for the control group. The raw impedance was found to oscillate with median amplitudes between 6 and 17 Ω depending on the patient. Oscillations were traced back to an interplay of atrial, ventricular, and respiratory motion. In summary, local impedance measurements demonstrated their capability to distinguish pathological atrial tissue from physiological substrate. Methods to limit the influence of confounding factors that still hinder impedance mapping were presented. Measurements at different frequencies or the combination of multiple electrodes could lead to further improvement. The presented examples indicate that electrogram- and impedance-based substrate mapping have the potential to complement each other toward better patient outcomes in future.

Electrocardiographic features for the measurement of drivers' mental workload.

This study examines the effect of mental workload on the electrocardiogram (ECG) of participants driving the Lane Change Task (LCT). Different levels of mental workload were induced by a secondary task (n-back task) with three levels of difficulty. Subjective data showed a significant increase of the experienced workload over all three levels. An exploratory approach was chosen to extract a large number of rhythmical and morphological features from the ECG signal thereby identifying those which differentiated best between the levels of mental workload. No single rhythmical or morphological feature was able to differentiate between all three levels. A group of parameters were extracted which were at least able to discriminate between two levels. For future research, a combination of features is recommended to achieve best diagnosticity for different levels of mental workload.

Experimental Data and Geometric Analysis Repository-EDGAR.

INTRODUCTION: The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets. METHODS: The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository. RESULTS: An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany). CONCLUSIONS: It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.

Patient-specific modeling of atrial fibrosis increases the accuracy of sinus rhythm simulations and may explain maintenance of atrial fibrillation.

Left atrial fibrosis is thought to contribute to the manifestation of atrial fibrillation (AF). Late Gadolinium enhancement (LGE) MRI has the potential to image regions of low perfusion, which can be related to fibrosis. We show that a simulation with a patient-specific model including left atrial regional fibrosis derived from LGE-MRI reproduces local activation in the left atrium more precisely than the regular simulation without fibrosis. AF simulations showed a spontaneous termination of the arrhythmia in the absence of fibrosis and a stable rotor center in the presence of fibrosis. The methodology may provide a tool for a deeper understanding of the mechanisms maintaining AF and eventually also for the planning of substrate-guided ablation procedures in the future.

Comparing measured and simulated wave directions in the left atrium - a workflow for model personalization and validation.

Atrial arrhythmias are frequently treated using catheter ablation during electrophysiological (EP) studies. However, success rates are only moderate and could be improved with the help of personalized simulation models of the atria. In this work, we present a workflow to generate and validate personalized EP simulation models based on routine clinical computed tomography (CT) scans and intracardiac electrograms. From four patient data sets, we created anatomical models from angiographic CT data with an automatic segmentation algorithm. From clinical intracardiac catheter recordings, individual conduction velocities were calculated. In these subject-specific EP models, we simulated different pacing maneuvers and measurements with circular mapping catheters that were applied in the respective patients. This way, normal sinus rhythm and pacing from a coronary sinus catheter were simulated. Wave directions and conduction velocities were quantitatively analyzed in both clinical measurements and simulated data and were compared. On average, the overall difference of wave directions was 15° (8%), and the difference of conduction velocities was 16 cm/s (17%). The method is based on routine clinical measurements and is thus easy to integrate into clinical practice. In the long run, such personalized simulations could therefore assist treatment planning and increase success rates for atrial arrhythmias.

Quantitative conductivity and permittivity imaging of the human brain using electric properties tomography.

The electric properties of human tissue can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. In the framework of radiofrequency safety, the electric conductivity of tissue is needed to correctly estimate the local specific absorption rate distribution during MR measurements. In this study, a recently developed approach, called electric properties tomography (EPT) is adapted for and applied to in vivo imaging. It derives the patient's electric conductivity and permittivity from the spatial sensitivity distributions of the applied radiofrequency coils. In contrast to other methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or radiofrequency probes, which enhances the practicability of the approach. This work shows that conductivity distributions can be reconstructed from phase images and permittivity distributions can be reconstructed from magnitude images of the radiofrequency transmit field. Corresponding numerical simulations using finite-difference time-domain methods support the feasibility of this phase-based conductivity imaging and magnitude-based permittivity imaging. Using this approximation, three-dimensional in vivo conductivity and permittivity maps of the human brain are obtained in 5 and 13 min, respectively, which can be considered a step toward clinical feasibility for EPT.

T1 corrected B1 mapping using multi-TR gradient echo sequences.

This work presents a new approach toward a fast, simultaneous amplitude of radiofrequency field (B(1)) and T(1) mapping technique. The new method is based on the "actual flip angle imaging" (AFI) sequence. However, the single pulse repetition time (TR) pair used in the standard AFI sequence is replaced by multiple pulse repetition time sets. The resulting method was called "multiple TR B(1)/T(1) mapping" (MTM). In this study, MTM was investigated and compared to standard AFI in simulations and experiments. Feasibility and reliability of MTM were proven in phantom and in vivo experiments. Error propagation theory was applied to identify optimal sequence parameters and to facilitate a systematic noise comparison to standard AFI. In terms of accuracy and signal-to-noise ratio, the presented method outperforms standard AFI B(1) mapping over a wide range of T(1). Finally, the capability of MTM to determine T(1) was analyzed qualitatively and quantitatively, yielding good agreement with reference measurements.

Noninvasive, automatic optimization strategy in cardiac resynchronization therapy.

OBJECTIVE: Optimization of cardiac resynchronization therapy (CRT) is still unsolved. It has been shown that optimal electrode position,atrioventricular (AV) and interventricular (VV) delays improve the success of CRT and reduce the number of non-responders. However, no automatic, noninvasive optimization strategy exists to date. METHODS: Cardiac resynchronization therapy was simulated on the Visible Man and a patient data-set including fiber orientation and ventricular heterogeneity. A cellular automaton was used for fast computation of ventricular excitation. An AV block and a left bundle branch block were simulated with 100%, 80% and 60% interventricular conduction velocity. A right apical and 12 left ventricular lead positions were set. Sequential optimization and optimization with the downhill simplex algorithm (DSA) were carried out. The minimal error between isochrones of the physiologic excitation and the therapy was computed automatically and leads to an optimal lead position and timing. RESULTS: Up to 1512 simulations were carried out per pathology per patient. One simulation took 4 minutes on an Apple Macintosh 2 GHz PowerPC G5. For each electrode pair an optimal pacemaker delay was found. The DSA reduced the number of simulations by an order of magnitude and the AV-delay and VV - delay were determined with a much higher resolution. The findings are well comparable with clinical studies. CONCLUSION: The presented computer model of CRT automatically evaluates an optimal lead position and AV-delay and VV-delay, which can be used to noninvasively plan an optimal therapy for an individual patient. The application of the DSA reduces the simulation time so that the strategy is suitable for pre-operative planning in clinical routine. Future work will focus on clinical evaluation of the computer models and integration of patient data for individualized therapy planning and optimization.

Multiple wavelets, rotors, and snakes in atrial fibrillation--a computer simulation study.

BACKGROUND: Multiple wavelets and rotors are accused of maintaining atrial fibrillation (AF). However, snake-like excitation patterns have recently been observed in AF. So far, computer models have investigated AF in a simplified anatomical model. In this work, pulmonary vein firing is simulated to investigate the initiation and maintenance of AF in a realistic anatomical model. METHODS AND RESULTS: Thirty-five ectopic foci situated around all pulmonary veins were simulated by a unidirectional conduction block. The excitation propagation was simulated by an adaptive cellular automaton on a realistic 3-dimensional atrial anatomy. Atrial fibrillation was initiated in 65.7% of the simulations. Stable excitation patterns were broken up in anatomically heterogeneous regions, creating a streak-like excitation pattern similar to snakes. Multiple wavelets and rotors could be observed in anatomically smooth areas at the atria's roofs. CONCLUSIONS: The influence of macroscopic anatomical structures on the course of AF seems to play an important role in the excitation propagation in AF. The computer simulations indicate that multiple mechanisms contribute to the maintenance of AF.

An optimal radial profile order based on the Golden Ratio for time-resolved MRI.

In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.

Simultaneous imaging and R2* mapping using a radial multi-gradient-echo (rMGE) sequence.

PURPOSE: To demonstrate a rapid MR technique that combines imaging and R2* mapping based on a single radial multi-gradient-echo (rMGE) data set. The technique provides a fast method for online monitoring of the administration of (super-)paramagnetic contrast agents as well as image-guided drug delivery. MATERIALS AND METHODS: Data are acquired using an rMGE sequence, resulting in interleaved undersampled radial k-spaces representing different echo times (TEs). These data sets are reconstructed separately, yielding a series of images with different TEs used for pixelwise R2* mapping. A fast numerical algorithm implemented on a real-time reconstruction platform provides online estimation of the relaxation rate R2*. Simultaneously the images are summed for the computation of a high-resolution image. RESULTS: Convenient high-resolution R2* maps of phantoms and the liver of a healthy volunteer were obtained. In addition to stable intrinsic baseline maps, the proposed technique provides particularly accurate results for the high relaxation rates observed during the presence of (super-)paramagnetic contrast agents. Assuming that the change in R2* is proportional to the concentration of the agent, the technique offers a rough estimate for dynamic dosage. CONCLUSION: The simultaneous online display of morphological and parametric information permits convenient, quantitative surveillance of contrast-agent administration.

SNR enhancement in radial SSFP imaging using partial k-space averaging.

The steady-state free precessing (SSFP) sequences, widely used in MRI today, acquire data only during a short fraction of the repetition time (TR). Thus, they exhibit a poor scan efficiency. In this paper, a novel approach to extending the acquisition window for a given TR without considerably modifying the basic sequence is explored for radial SSFP sequences. The additional data are primarily employed to increase the signal-to-noise ratio, rather than to improve the temporal resolution of the imaging. The approach is analyzed regarding its effect on the image SNR (signal to noise ratio) and the reconstruction algorithm. Results are presented for phantom experiments and cardiac functions studies. The gain in SNR is most notable in rapid imaging, since SNR enhancement for a constant repetition time may be used to compensate for the increase in noise resulting from angular undersampling.