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

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

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

International audienceElectrocardiographic 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 fullyautomated 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

International audienceSegmentation 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

Classification of Inverse Solutions to Two Dipoles

Abstract The aim of the simulation study was Introduction The inverse solution using two dipoles was suggested in [1] for localization of two simultaneous lesions which can occur in patients with ischemic heart disease and atherosclerosis. It was supposed that each lesion can be represented by one dipole. As it is known, such inverse solution is ill-posed [2] and the obtained resulting pair of dipoles may not be the proper representative of the location of the pair of lesions. The additional question in such a computation is whether we need the a priori information about the number of lesions or we are able to determine the number of lesions (one or two) from the properties of the obtained pair of dipoles. In this simulation study groups of inverse results were computed for each case. Then various characteristics of the resulting dipoles were specified and used as discriminating features enabling to recognize the correct inverse solutions representing the two lesions and to distinguish them from other solutions obtained either for one lesion or obtained as incorrect identification of the two simultaneous lesions. Material and methods The body surface potential maps (BSPMs) were simulated for several cases with presence of one lesion or pair of lesions in the modeled ventricular myocardium. Each lesion was modeled as an area with changed repolarization properties of action potentials. For each case with one lesion or pair of lesions the inverse solution was computed and some characteristics of the solution as well as the correctness of the solution were evaluated. The characteristics were then used as discriminating features in classification task to recognize correct identification of two lesions. Forward and inverse solution In the analytically defined geometrical model of heart ventricles small lesions with changed repolarization were modeled as part of a sphere or part of an ellipsoid located in the myocardium. Six positions of the lesions (anterior, inferior and posterior; each subendocardial and subepicardial) typical for stenosis of one of the three main coronary vessels were defined To compute body surface potential maps (BSPMs) corresponding to normal ventricular activation and to activations with modeled lesions, the cardiac generato

Noninvasive Identification of Ischemic Lesion in the Heart

A method for noninvasive identification of heart lesions with changed repolarization caused by local ischemia was proposed and tested on a model and on a group of patients. It evaluates changes in QRST integral maps measured on a chest surface of known geometry and computes an equivalent dipole representing the position, size and orientation of the lesion. Testing on a computer model indicated ability of the method to localize small  subendocardial and subepicardial lesions with an error less about 1 cm. From 11 patients with single vessel stenosis mapped before and after the percutaneous cardiac intervention, differences in QRST integral maps could be represented by a dipole in 8 patients. 6 LAD and 1 RCA lesion were identified successfully, localization of 1 RCA lesion failed. Results of the study suggest that difference QRST integral maps can help in identification of small ischemic regions on the epicardial or endocardial surface by estimating parameters of an equivalent dipole characterizing the lesio

Modular Measuring System for Assesment of the Thyroid Gland Functional State

Distributed modular system BioLab for biophysical examinations enabling assessment of the thyroid gland functional state is presented in the paper. The BioLab system is based on a standard notebook or desktop PC connected to an Ethernet-based network of two smart sensors. These sensors are programmed and controlled from PC and enable measurement of selected biosignals of the human cardiovascular and neuromuscular system that are influenced by the production of thyroid gland hormones. Recorded biosignals are processed in a PC and peripheral indicators characterizing thyroid gland functional state are evaluated

Eliminating Speckle Noises for Laser Doppler Vibrometer Based on Empirical Wavelet Transform

This paper presents a novel approach for eliminating speckle noises in Laser Doppler Vibrometer signals based on empirical wavelet transform (EWT). The moving root-mean-square thresholds are utilized to cut off signal drop-outs and produce noise discontinuity that EWT can identify. The extremum ratio behaves as the criterion to reject or accept the EWT decomposed components. While processing simulated signals, the EWT-based approach outperforms others and presents de-speckle robustness. In experiments, EWT reveals the actual vibration despite low signal-to-noise ratios, which indicates de-speckle efficiency