| Autor: |
Hartwig V; Institute of Clinical Physiology (IFC), 56124 Pisa, Italy., Morelli MS; Fondazione Toscana Gabriele Monasterio, 56124 Pisa, Italy., Martini N; Fondazione Toscana Gabriele Monasterio, 56124 Pisa, Italy., Seghetti P; Institute of Clinical Physiology (IFC), 56124 Pisa, Italy.; Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, 56127 Pisa, Italy., Tirabasso D; Dipartimento di Ingegneria dell'Informazione, University of Pisa, 56124 Pisa, Italy., Positano V; Fondazione Toscana Gabriele Monasterio, 56124 Pisa, Italy., Latrofa S; Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56124 Pisa, Italy., Mansi G; Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56124 Pisa, Italy., Rossi A; Fondazione Toscana Gabriele Monasterio, 56124 Pisa, Italy., Giannoni A; Fondazione Toscana Gabriele Monasterio, 56124 Pisa, Italy.; Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, 56127 Pisa, Italy., Tognetti A; Dipartimento di Ingegneria dell'Informazione, University of Pisa, 56124 Pisa, Italy.; Research Center 'E. Piaggio', University of Pisa, 56124 Pisa, Italy., Vanello N; Dipartimento di Ingegneria dell'Informazione, University of Pisa, 56124 Pisa, Italy.; Research Center 'E. Piaggio', University of Pisa, 56124 Pisa, Italy. |
| Abstrakt: |
Brugada Syndrome (BrS) is a primary electrical epicardial disease characterized by ST-segment elevation followed by a negative T-wave in the right precordial leads on the surface electrocardiogram (ECG), also known as the 'type 1' ECG pattern. The risk stratification of asymptomatic individuals with spontaneous type 1 ECG pattern remains challenging. Clinical and electrocardiographic prognostic markers are known. As none of these predictors alone is highly reliable in terms of arrhythmic prognosis, several multi-factor risk scores have been proposed for this purpose. This article presents a new workflow for processing endocardial signals acquired with high-density RV electro-anatomical mapping (HDEAM) from BrS patients. The workflow, which relies solely on Matlab software, calculates various electrical parameters and creates multi-parametric maps of the right ventricle. The workflow, but it has already been employed in several research studies involving patients carried out by our group, showing its potential positive impact in clinical studies. Here, we will provide a technical description of its functionalities, along with the results obtained on a BrS patient who underwent an endocardial HDEAM. |
