Search

Introduction: Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry., Methods: Multiple‑lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes., Results: CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%., Conclusion: Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice., Competing Interests: Declaration of Competing Interest R. Molero and A. González-Ascaso have no conflict of interests., (Copyright © 2022. Published by Elsevier Inc.)

Bundle branch block (BBB) is a defect on the electrical conduction system of the heart diagnosed by analyzing electrocardiogram (ECG) morphology. Our study aims to determine whether mapping information, specifically QRS duration and observation data from maps obtained using body surface potential mapping (BSPM), can be helpful in BBB diagnosis. We studied 64-lead BSPM recordings of 18 BBB patients and 9 controls with normal ventricular conduction. QRS duration was measured from the BSPM information obtained. The BSPM maps were computed along the QRS complex for each individual and group, and maps for each group were compared with maps for each individual. QRS complexes of the 12 standard leads were computed for each individual and group, and complexes of each group were compared with the complexes of each individual. QRS duration measured for all available leads (64 unipolar leads and 12 standard leads) was 7.4 +/- 3.9 milliseconds longer than QRS duration measured only in the standard 12-lead ECG for left BBB patients (LBBB) and 15.3 +/- 10.8 milliseconds longer for right BBB with left anterior fascicular block patients (RBBB_LAFB). In case of comparisons based on the standard ECG, sensitivity was 76.9% for LBBB patients and 66.6% for control subjects. However, classification based on map comparisons showed a sensitivity of 93% for LBBB patients and 89% for controls. QRS duration measured from BSPM information does not differ significantly from 12-lead standard ECG measurement for LBBB. However, differences are higher for RBBB_LAFB patients. Representative BSPM maps permit an automatic classification of the subjects.

The objective of this study was the evaluation of the accuracy of Dower inverse transform for the derivation of the P wave in orthogonal leads. We tested the accuracy of Dower transform on the P wave and compared it with a P-wave-optimized transform in a database of 123 simultaneous recordings of electrocardiograms and vectorcardiograms. This new transform achieved a lower error when we compared derived vs true measured P waves (mean +/- SD, 12.2 +/- 8.0 VRMS) than Dower transform (14.4 +/- 9.5 Root mean squared voltage) and higher correlation values (Rx, 0.93 +/- 0.12; Ry, 0.90 +/- 0.27; Rz, 0.91 +/- 0.18; vs Dower: Rx, 0.88 +/- 0.15; Ry, 0.91 +/- 0.26; Rz, 0.85 +/- 0.23). We conclude that derivation of orthogonal leads for the P wave can be improved by using an atrial-based transform matrix.

In this study, several methods for optimal lead selection from multilead electrocardiographic recordings are analyzed. Two different lead selection methods have been implemented. For their evaluation, a linear transformation that reconstructs nonselected leads from selected leads is computed according to the least squares optimization, and the performance is evaluated in terms of the mean square error of the derived potentials and correlation. The algorithms were tested on a database of 72 body surface potential recordings: 18 controls, 18 bundle-branch block, 18 myocardial infarction, and 18 ventricular hypertrophy. Each data set was divided into a study and test subsets. Two experiments were carried out: (1) The lead selection, transformation matrix, and performance evaluation is carried out over the test data set (ideal case), and (2) the lead selection and transformation matrix is carried out over the study data set, but the performance is evaluated over the test data set (real case). Our results show important reconstruction errors with either lead selection methods, and only increasing the number of leads reduces the error in reconstruction. However, if a reduced number of leads are to be selected outside the standard 12-lead electrocardiogram, the method proposed by Lux has been shown to be the best option.