Heart ventricular activation in VAT difference maps from children with chronic kidney disease

Children with chronic kidney disease (CKD) are affected by cardiovascular complications, including disturbances in the intraventricular conduction system. Body surface potential mapping (BSPM) is a non-invasive method of assessing the cardioelectrical field. Our aim was to investigate conduction disturbances in young CKD patients using ventricular activation time (VAT) maps. Our study comprised 22 CKD children (mean age: 13.1 ± 2.5 years) treated conservatively and 29 control patients. For each child 12-lead electrocardiogram (ECG) readings were taken, and blood pressure and serum concentrations of iPTH, Pi, t-Ca, creatinine, Fe+3, ferritin, and Hb, as well as eGFR were measured. All children underwent registration in the 87-lead BSPM system, and group-mean VAT maps and a difference map, which presents statistically significant differences between the groups, were created. The VAT map distribution in CKD patients revealed abnormalities specific to left anterior fascicle block. The difference map displays the areas of intergroup VAT changes, which are of discriminative value in detecting intraventricular conduction disturbances. Intraventricular conduction impairments in the left bundle branch may occur in children with CKD. BSPM enables conduction disturbances in CKD children to be detected earlier than using 12-lead ECG. The difference map derived from the group-mean isochrone maps precisely localizes the sites of disturbed conduction in the heart intraventricular conduction system

Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation

Atrial arrhythmias, and specifically atrial fibrillation (AF), induce rapid and irregular activation patterns that appear on the torso surface as abnormal P-waves in electrocardiograms and body surface potential maps (BSPM). In recent years both P-waves and the BSPM have been used to identify the mechanisms underlying AF, such as localizing ectopic foci or high-frequency rotors. However, the relationship between the activation of the different areas of the atria and the characteristics of the BSPM and P-wave signals are still far from being completely understood. In this work we developed a multi-scale framework, which combines a highly-detailed 3D atrial model and a torso model to study the relationship between atrial activation and surface signals in sinus rhythm. Using this multi scale model, it was revealed that the best places for recording P-waves are the frontal upper right and the frontal and rear left quadrants of the torso. Our results also suggest that only nine regions (of the twenty-one structures in which the atrial surface was divided) make a significant contribution to the BSPM and determine the main P-wave characteristics.This work was partially supported by the "VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica" from the Ministerio de Economia y Competitividad of Spain and the European Commission (European Regional Development Funds - ERDF - FEDER), Award Number: TIN2012-37546-C03-01 (Recipient: Ana Ferrer); the "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientado a los Retos de la Sociedad" from the Ministerio de Economia y Competitividad and the European Commission (European Regional Development Funds - ERDF - FEDER), Award Number: TIN2014-59932-JIN (Recipient: Rafael Sebastion); and the "Programa Prometeo" from the Generalitat Valenciana, Award Number: 2012/030 (Recipient: Laura Martinez).Ferrer Albero, A.; Sebastián Aguilar, R.; Sánchez Quintana, D.; Rodriguez, JF.; Godoy, EJ.; Martinez, L.; Saiz Rodríguez, FJ. (2015). Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation. PLoS ONE. 10(11):1-29. https://doi.org/10.1371/journal.pone.0141573S129101

Age dependence of the vulnerability index in young people

Abstract. Index of vulnerabilty is a parameter evaluating the risk of arrhythmia development, which is derived from isointegral maps of QRST interval (IIM QRS