ISE/ISHNE expert consensus statement on the ECG diagnosis of left ventricular hypertrophy: The change of the paradigm.

The ECG diagnosis of LVH is predominantly based on the QRS voltage criteria. The classical paradigm postulates that the increased left ventricular mass generates a stronger electrical field, increasing the leftward and posterior QRS forces, reflected in the augmented QRS amplitude. However, the low sensitivity of voltage criteria has been repeatedly documented. We discuss possible reasons for this shortcoming and proposal of a new paradigm. The theoretical background for voltage measured at the body surface is defined by the solid angle theorem, which relates the measured voltage to spatial and non-spatial determinants. The spatial determinants are represented by the extent of the activation front and the distance of the recording electrodes. The non-spatial determinants comprise electrical characteristics of the myocardium, which are comparatively neglected in the interpretation of the QRS patterns. Various clinical conditions are associated with LVH. These conditions produce considerable diversity of electrical properties alterations thereby modifying the resultant QRS patterns. The spectrum of QRS patterns observed in LVH patients is quite broad, including also left axis deviation, left anterior fascicular block, incomplete and complete left bundle branch blocks, Q waves, and fragmented QRS. Importantly, the QRS complex can be within normal limits. The new paradigm stresses the electrophysiological background in interpreting QRS changes, i.e., the effect of the non-spatial determinants. This postulates that the role of ECG is not to estimate LV size in LVH, but to understand and decode the underlying electrical processes, which are crucial in relation to cardiovascular risk assessment.

A two-step inverse solution for a single dipole cardiac source.

Introduction: The inverse problem of electrocardiography noninvasively localizes the origin of undesired cardiac activity, such as a premature ventricular contraction (PVC), from potential recordings from multiple torso electrodes. However, the optimal number and placement of electrodes for an accurate solution of the inverse problem remain undetermined. This study presents a two-step inverse solution for a single dipole cardiac source, which investigates the significance of the torso electrodes on a patient-specific level. Furthermore, the impact of the significant electrodes on the accuracy of the inverse solution is studied. Methods: Body surface potential recordings from 128 electrodes of 13 patients with PVCs and their corresponding homogeneous and inhomogeneous torso models were used. The inverse problem using a single dipole was solved in two steps: First, using information from all electrodes, and second, using a subset of electrodes sorted in descending order according to their significance estimated by a greedy algorithm. The significance of electrodes was computed for three criteria derived from the singular values of the transfer matrix that correspond to the inversely estimated origin of the PVC computed in the first step. The localization error (LE) was computed as the Euclidean distance between the ground truth and the inversely estimated origin of the PVC. The LE obtained using the 32 and 64 most significant electrodes was compared to the LE obtained when all 128 electrodes were used for the inverse solution. Results: The average LE calculated for both torso models and using all 128 electrodes was 28.8 ± 11.9 mm. For the three tested criteria, the average LEs were 32.6 ± 19.9 mm, 29.6 ± 14.7 mm, and 28.8 ± 14.5 mm when 32 electrodes were used. When 64 electrodes were used, the average LEs were 30.1 ± 16.8 mm, 29.4 ± 12.0 mm, and 29.5 ± 12.6 mm. Conclusion: The study found inter-patient variability in the significance of torso electrodes and demonstrated that an accurate localization by the inverse solution with a single dipole could be achieved using a carefully selected reduced number of electrodes.

ISE/ISHNE Expert Consensus Statement on ECG Diagnosis of Left Ventricular Hypertrophy: The Change of the Paradigm. The joint paper of the International Society of Electrocardiology and the International Society for Holter Monitoring and Noninvasive Electrocardiology.

The ECG diagnosis of LVH is predominantly based on the QRS voltage criteria, i.e. the increased QRS complex amplitude in defined leads. The classical ECG diagnostic paradigm postulates that the increased left ventricular mass generates a stronger electrical field, increasing the leftward and posterior QRS forces. These increased forces are reflected in the augmented QRS amplitude in the corresponding leads. However, the clinical observations document increased QRS amplitude only in the minority of patients with LVH. The low sensitivity of voltage criteria has been repeatedly documented. We discuss possible reasons for this shortcoming and proposal of a new paradigm.

Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data.

Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).

Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization.

Electrocardiographic Imaging (ECGI) is a promising tool to non-invasively map the electrical activity of the heart using body surface potentials (BSPs) and the patient specific anatomical data. One of the first steps of ECGI is the segmentation of the heart and torso geometries. In the clinical practice, the segmentation procedure is not fully-automated yet and is in consequence operator-dependent. We expect that the inter-operator variation in cardiac segmentation would influence the ECGI solution. This effect remains however non quantified. In the present work, we study the effect of segmentation variability on the ECGI estimation of the cardiac activity with 262 shape models generated from fifteen different segmentations. Therefore, we designed two test cases: with and without shape model uncertainty. Moreover, we used four cases for ectopic ventricular excitation and compared the ECGI results in terms of reconstructed activation times and excitation origins. The preliminary results indicate that a small variation of the activation maps can be observed with a model uncertainty but no significant effect on the source localization is observed.

The Effect of Segmentation Variability in Forward ECG Simulation.

Segmentation of patient-specific anatomical models is one of the first steps in Electrocardiographic imaging (ECGI). However, the effect of segmentation variability on ECGI remains unexplored. In this study, we assess the effect of heart segmentation variability on ECG simulation. We generated a statistical shape model from segmentations of the same patient and generated 262 cardiac geometries to run in an ECG forward computation of body surface potentials (BSPs) using an equivalent dipole layer cardiac source model and 5 ventricular stimulation protocols. Variability between simulated BSPs for all models and protocols was assessed using Pearson's correlation coefficient (CC). Compared to the BSPs of the mean cardiac shape model, the lowest variability (average CC = 0.98 ± 0.03) was found for apical pacing whereas the highest variability (average CC = 0.90 ± 0.23) was found for right ventricular free wall pacing. Furthermore, low amplitude BSPs show a larger variation in QRS morphology compared to high amplitude signals. The results indicate that the uncertainty in cardiac shape has a significant impact on ECGI.

The Impact of Torso Signal Processing on Noninvasive Electrocardiographic Imaging Reconstructions.

GOAL: To evaluate state-of-the-art signal processing methods for epicardial potential-based noninvasive electrocardiographic imaging reconstructions of single-site pacing data. METHODS: Experimental data were obtained from two torso-tank setups in which Langendorff-perfused hearts (n = 4) were suspended and potentials recorded simultaneously from torso and epicardial surfaces. 49 different signal processing methods were applied to torso potentials, grouped as i) high-frequency noise removal (HFR) methods ii) baseline drift removal (BDR) methods and iii) combined HFR+BDR. The inverse problem was solved and reconstructed electrograms and activation maps compared to those directly recorded. RESULTS: HFR showed no difference compared to not filtering in terms of absolute differences in reconstructed electrogram amplitudes nor median correlation in QRS waveforms (p > 0.05). However, correlation and mean absolute error of activation times and pacing site localization were improved with all methods except a notch filter. HFR applied post-reconstruction produced no differences compared to pre-reconstruction. BDR and BDR+HFR significantly improved absolute and relative difference, and correlation in electrograms (p < 0.05). While BDR+HFR combined improved activation time and pacing site detection, BDR alone produced significantly lower correlation and higher localization errors (p < 0.05). CONCLUSION: BDR improves reconstructed electrogram morphologies and amplitudes due to a reduction in lambda value selected for the inverse problem. The simplest method (resetting the isoelectric point) is sufficient to see these improvements. HFR does not impact electrogram accuracy, but does impact post-processing to extract features such as activation times. Removal of line noise is insufficient to see these changes. HFR should be applied post-reconstruction to ensure over-filtering does not occur.

Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications.

Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and non-invasively reconstructed in a digitized model of the patient's three-dimensional heart, which has led to clinical interest in ECGI's ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI's ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose 'best' practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists, and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique toward a useful role in clinical practice.

Geometrical constraint of sources in noninvasive localization of premature ventricular contractions.

The inverse problem of electrocardiography for localization of a premature ventricular contraction (PVC) origin was solved and compared for three types of the equivalent cardiac electrical generator: transmembrane voltages, epicardial potentials, and dipoles. Instead of regularization methods usually used for the ill-posed inverse problems an assumption of a single point source representative of the heart generator was applied to the solution as a geometrical constraint. Body surface potential maps were simulated from eight modeled origins of the PVC in the heart model. Then the maps were corrupted by additional Gaussian noise with the signal-to-noise ratio (SNR) from 20 to 10dB and used as the input of the inverse solution. The inverse solution was computed from the first 30ms of the ventricular depolarization. It was assumed that during this period only a small part of the heart volume is activated thus it can be represented by a single point electrical source. Generally, the localization error was more dependent on the PVC origin position than on the type of the used heart generator. The most stable localization error between the inversely found results and the true PVC origin was not larger than 20mm for PVC origins located in the left ventricular wall and on the right ventricular anterior side. For such cases, the localization was robust to the noise up to SNR of 10dB for all studied types of the cardiac generator. For SNR 10dB the results became unstable mainly for the PVC origins in the septum and posterior right ventricle for the dipolar heart generator and for epicardial potentials defined on the pericardium when the range of the localization error increased up to 50mm. When the results for different electrical heart generators were considered altogether, the mean radius of the cloud of results did not exceed 20mm and the localization error of the cloud center was smaller than that obtained for a particular type of the cardiac generator. Combination of results from different models of a single point cardiac electrical generator can provide better information for the preliminary noninvasive localization of PVC than the use of one type of the generator.

QRS complex waveform indicators of ventricular activation slowing: Simulation studies.

Diffuse or regional activation slowing in ventricular myocardium can result from different cardiac pathologies, such as left ventricular hypertrophy, ischemia or fibrosis. Altered ventricular activation sequence leads to deformations of the activation front and consequently to the changes in the QRS complex. Using a computer model we simulated the effect of slowed ventricular activation on the QRS waveform with a special interest in ECG changes which reproduce the ECG criteria of left ventricular hypertrophy (ECG-LVH). This paper describes results of a set of computer modeling experiments and discusses visual QRS patterns. Slowed ventricular activation in the whole left ventricle resulted in the prolongation of QRS duration, leftward shift of electrical axis, and increase in the QRS amplitude mainly in the precordial leads, having thus their main impact on simulated Sokolow-Lyon index and Cornell voltage. Slowed ventricular activation in the anteroseptal region resulted in a leftward shift of the electrical axis and increased values of ECG-LVH criteria seen in limb leads or in a combination with precordial leads (Gubner criterion, Cornell voltage). Transmural slowing and midwall slowing in two layers in the anteroseptal area led also to the QRS duration prolongation. Changes in QRS complex were more pronounced in the cases of transmural slowing as compared to the left ventricular midwall slowing. Using computer modeling, we showed that slowed ventricular activation is a potent determinant of QRS complex morphology and can mimic ECG patterns that are usually interpreted as the effect of left ventricular hypertrophy, i.e., increased left ventricular mass. These results contribute to understanding the variety of ECG finding documented in patients with LVH, considering not only anatomical enlargement but also the altered electrical properties of hypertrophied myocardium.

Modeling and visualization of the activation wavefront propagation to improve understanding the QRS complex changes indicating left ventricular hypertrophy.

Activation wavefront propagation was computed and visualized in a geometrical heart model for pathological cases of reduced velocity of propagation, left ventricular hypertrophy and their combination. Selected parameters of a multiple dipole equivalent heart generator were computed and compared for three heart geometries and several degrees and extents of reduction of propagation velocity. First, the influence of geometrical changes modeling the left ventricular hypertrophy at reference propagation velocity was compared with reduction of the propagation velocity in the reference heart geometry. Reduced propagation velocity yielded similar or greater changes of the magnitude of the (electrical) heart vector representing the activation wavefront than the geometrical changes. Observations of the wavefront propagation with reduced velocity revealed longer presence of a large extent of the wavefront during depolarization which resulted in increased magnitude of the heart vector. The duration of depolarization was significantly prolonged only when the propagation velocity was decreased to 25% of its normal value. Changes of the direction of the maximal heart vector were dependent on the position of the region where the propagation velocity was reduced. Then the combination of the left ventricular hypertrophy and reduced propagation velocity was studied. Such combination enhanced the enlargement of the electrical heart vector and significantly prolonged the duration of depolarization. The influence of reduced activation velocity on the observed parameters was greater than the effect of the enlargement of the left ventricular mass. The presented study showed that intramyocardial conduction disturbances might cause increase of the actual surface area of propagation wavefront leading to changes of the amplitudes of ECG signals comparable with the changes resulting from the left ventricular hypertrophy. Intramyocardial conduction disturbances, as well as the modeled 50% increase of the thickness of the left ventricular wall, did not cause prolongation of the QRS complex out of normal range. Considerable prolongation of the QRS complex duration was observed only for transmural slowing of the propagation velocity to 25% of its reference value in large ventricular areas or for combination of such slowing with the left ventricular hypertrophy.

The effect of conduction velocity slowing in left ventricular midwall on the QRS complex morphology: A simulation study.

UNLABELLED: Midwall fibrosis is a frequent finding in different types of left ventricular hypertrophy. Fibrosis presents a local conduction block that can create a substrate for ventricular arrhythmias and lead to the continuous generation of reentry. Having also impact on the sequence of ventricular activation it can modify the shape of QRS complex. In this study we simulated the effects of slowed conduction velocity in the midwall in the left ventricle and in its anteroseptal region on the QRS morphology using a computer model. MATERIAL AND METHODS: The model defines the geometry of cardiac ventricles analytically as parts of ellipsoids; the left ventricular wall is represented by five layers. The impulse propagation velocity was decreased by 50% in one and two midwall layers, respectively, in the whole left ventricle and in LV anterior region. The effects of slowed conduction velocity on the QRS complex of the 12-lead electrocardiogram are presented as 12-lead electrocardiograms and corresponding values of ECG criteria for left ventricular hypertrophy (ECG-LVH criteria): Gubner criterion, Sokolow-Lyon index (SLI) and Cornell voltage. RESULTS: All simulated situations led to increased R wave amplitude in the lead I and of S wave in the lead III, showing a leftward shift of the electrical axis and increased values of ECG-LVH criteria based on limb leads alone or in combination with precordial leads (Gubner criterion, Cornell voltage). The slowed conduction velocity in the whole LV influenced the QRS complex voltage in precordial leads, having an impact on the SLI and Cornell voltage. The changes were pronounced if two layers were involved. CONCLUSION: Using computer modeling we showed that the midwall slowing in conduction velocity modified the QRS complex morphology. The QRS complex changes were consistent with ECG-LVH criteria, i.e. QRS patterns usually interpreted as the effect of left ventricular hypertrophy (the increased left ventricular mass).

Noninvasive identification of two lesions with local repolarization changes using two dipoles in inverse solution simulation study.

BACKGROUND: The method for inverse localization and identification of two distinct simultaneous lesions with changed repolarization in the ventricular myocardium (two-vessel disease) is proposed and its robustness to errors in input data is tested in this simulation study. METHOD: The inverse solution was obtained from the difference between STT integral body surface potential map computed with repolarization changes and the STT integral map from normal activation. In a numerical model of ventricles 48 cases of two simultaneous lesions and 48 cases of a single lesion were modeled. The effect of the lesions was taken to be represented by two dipoles. The input data were disturbed by three types of added noise. Twenty three characteristics of every obtained inverse solution were defined and four of them were used as the features in discriminant analysis task distinguishing the correct inverse solutions identifying two lesions. RESULTS: The mean localization error for identified two lesions was 1.1±0.7cm. The sensitivity and specificity of quadratic discriminant analysis with cross-validation and feature selection was higher than 90%. CONCLUSIONS: The combination of the inverse solution with two dipoles and discriminant analysis allows the identification of two simultaneous lesions without a priori information about the number of lesions.

Noninvasive finding of local repolarization changes in the heart using dipole models and simplified torso geometry.

Two inverse methods using dipole models for noninvasive assessment of local repolarization changes were investigated and compared in the simulation study. Lesions with changed repolarization were modeled by shortening of the action potential durations in ventricular regions typically influenced by occlusion of coronary arteries. Corresponding body surface potentials were computed using a multiple dipole model of the cardiac generator and an inhomogeneous torso model. Position of each lesion was then estimated by an inverse solution to a single dipole and to a group of five neighbouring dipoles. For both methods the lesion localization error was evaluated and its dependence on the lesion size and the noise in input data was studied. When no noise was present in the input data, the use of the inverse method to a group of dipoles instead of a single dipole resulted in an unsubstantial reduction of the mean localization error of small lesions from 0.6 to 0.5cm. For medium and especially for large lesions the mean localization errors decreased significantly from 1.1 to 0.6cm and from 2.3 to 1.0cm, respectively. The inverse solution to a group of five dipoles was more sensitive to noise. However, for large lesions it still gave better results than the solution to a single dipole if the signal to noise ratio was higher than 30dB.

Individualized model of torso surface for the inverse problem of electrocardiology.

PURPOSE: We studied the implementation of a patient-specific torso model created without the use of magnetic resonance imaging in the inverse problem of electrocardiology. METHOD: Three types of inhomogeneous numerical torso models were created, with different degrees of adjustment of the outer surface to patients, whereas the heart and lung models remained unchanged. The torso models were used in the inverse localization of small areas with repolarization changes from simulated difference integral QRST maps. The localization error (LE) was evaluated as the distance between the centers of the modeled and the inversely found area with repolarization changes. RESULTS: The mean LE was 1.88 cm with the standard torso model. After adapting the torso shape, the mean LE was 1.83 cm, whereas after adapting both, the shape and electrode positions, the mean LE was 1.02 cm. CONCLUSION: If torso imaging is not available, a torso model with adapted shape and electrode positions gives only slightly less accurate results.

Influence of individual torso geometry on inverse solution to 2 dipoles.

BACKGROUND: The purpose of this study was to observe the influence of variety in individual torso geometries on the results of inverse solution to 2 dipoles. METHODS: The inverse solution to 2 dipoles was computed from the measured data on 8 patients using either standard torso with various shapes and sizes of the heart and lungs in it or using various outer torso geometries with the same inhomogeneities. The vertical position of the heart relative to the fourth intercostal level was kept constant in all models. The results were compared with the reference solution computed in standard torso. RESULTS: The inverse solution was influenced in 4 of 8 cases by changes of torso geometry and only in 1 of 8 cases by changes of internal inhomogeneities. CONCLUSIONS: The use of individual torso geometry with the knowledge of the true heart position is very important for correct inverse results.

Noninvasive detection of repolarization changes in the heart.

OBJECTIVE: Previously reported inverse method based on dipolar representation of differences in QRST integral maps with and without manifestation of local repolarization changes has shown the ability to identify small areas in the myocardium responsible for these changes in a group of patients with coronary artery diseases underwent revascularization. The aim of this study was to verify this approach on a group of 4 healthy persons and a group of 7 patients suffering from effort angina pectoris. METHODS: Changes in QRST integral maps after nitroglycerine sublingual application were examined and single dipole best representing the difference QRST integral map was inversely computed. RESULTS: After attempted compensation of heart rate variations, changes in QRST integral maps greater than expected intra - individual variability (over 15%) were detected in 4 persons. Obtained difference integral maps could be sufficiently approximated by maps generated by single current dipole only in 2 persons with relative root mean square (rms) error less than 35%; in the rest of subjects relative rms error of the dipolar map approximation was greater than 50%. CONCLUSION: Results suggest that small repolarization changes might be detectable after nitroglycerine test, however this test did not induce detectable changes in some patients with effort angina pectoris.