Rafael Sebastian

Rafael Sebastian
University of Valencia | UV · Department of Informatic

PhD Computer Science

About

162
Publications
17,344
Reads
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1,485
Citations
Citations since 2016
95 Research Items
902 Citations
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2016201720182019202020212022050100150200
2016201720182019202020212022050100150200
Introduction
I am Full Professor at the department of computer science of Universitat de Valencia. In 2010 I started the Computational Modelling Simulation Lab (CoMMLab) in the University of Valencia, which focuses on mathematically modelling cellular, tissue and organ structures of the heart. Currently, I am interested in using machine learning techniques combined with biophysical simulation to study cardiac arrhythmia, and aid in therapy planning and optimisation.
Additional affiliations
September 2021 - September 2021
University of Valencia
Position
  • Professor (Full)
October 2015 - present
University of Valencia
Position
  • Professor
February 2010 - present
University of Valencia
Position
  • Profesor Ayudante Doctor

Publications

Publications (162)
Article
Full-text available
In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automa...
Article
Full-text available
Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patien...
Article
Full-text available
Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale b...
Article
Full-text available
The combination of machine learning methods together with computational modeling and simulation of the cardiovascular system brings the possibility of obtaining very valuable information about new therapies or clinical devices through in-silico experiments. However, the application of machine learning methods demands access to large cohorts of pati...
Chapter
The ellipse can be an appropriate geometry for aorta cross-section fitting on the lumen contour. However, in some regions of the aorta, such as the Sinuses of Valsalva, this approximation can suffer of a relatively high error. Thus, some authors use closed polynomial curves for a better representation of the cross section. This paper presents a det...
Chapter
Intracardiac devices separate atrial arrhythmias (AA) from sinus rhythm (SR) using electrogram (EGM) features such as rate, that are imperfect. We hypothesized that machine learning could improve this classification.
Chapter
Full-text available
Patients that have suffered a myocardial infarction are at lifetime high risk for sudden cardiac death (SCD). Personalized 3D computational modeling and simulation can help to find non-invasively arrhythmogenic features of patients’ infarcts, and to provide additional information for stratification and planning of radiofrequency ablation (RFA). Cur...
Article
The Purkinje system is a heart structure responsible for transmitting electrical impulses through the ventricles in a fast and coordinated way to trigger mechanical contraction. Estimating a patient-specific compatible Purkinje Network from an electro-anatomical map is a challenging task, that could help to improve models for electrophysiology simu...
Article
Full-text available
Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High...
Article
Full-text available
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior i...
Article
Resumen Las enfermedades cardiovasculares tienen en la actualidad un gran impacto social y económico y constituyen una de las principales causas de mortalidad y morbilidad. Los modelos computacionales personalizados del corazón están demostrando ser útiles tanto para ayudar a comprender los mecanismos subyacentes a las patologías cardiacas como par...
Article
Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's r...
Article
Full-text available
Aims: A pre-operative non-invasive identification of the site of origin (SOO) of outflow tract ventricular arrhythmias (OTVAs) is important to properly plan radiofrequency ablation procedures. Although some algorithms based on electrocardiograms (ECGs) have been developed to predict left vs. right ventricular origins, their accuracy is still limit...
Chapter
Optimization of lead placement and interventricular delay settings in patients under cardiac resynchronization therapy is a complex task that might benefit from prior information based on models. Biophysical models can be used to predict the sequence of electrical heart activation in a patient given a set of parameters which should be personalized...
Article
The cardiac conduction system is a network structure that allows the initiation and fast propagation of electrical impulses that trigger the electrical depolarization of the myocardial tissue. The purpose of this work is to study the histological and morphometric characteristics of the different components of the sinus and atrioventricular nodes in...
Article
Full-text available
In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this...
Article
Full-text available
Patients suffering from heart failure and left bundle branch block show electrical ventricular dyssynchrony causing an abnormal blood pumping. Cardiac resynchronization therapy (CRT) is recommended for these patients. Patients with positive therapy response normally present QRS shortening and an increased left ventricle (LV) ejection fraction. Howe...
Article
Full-text available
Purkinje cells (PCs) are more resistant to ischemia than myocardial cells, and are suspected to participate in ventricular arrhythmias following myocardial infarction (MI). Histological studies afford little evidence on the behavior and adaptation of PCs in the different stages of MI, especially in the chronic stage, and no quantitative data have b...
Data
ARRIVE guidelines checklist. Completed checklist in accordance to the ARRIVE Guidelines. (PDF)
Article
Rule‐based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule‐based methods often does not match histological data in other areas of the heart such as the right ventricle,...
Article
Purpose Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connecti...
Preprint
Full-text available
Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle,...
Article
Purpose: Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connecti...
Article
The reconstruction of the ventricular cardiac conduction system (CCS) from patient‐specific data is a challenging problem. High‐resolution imaging techniques have allowed only the segmentation of proximal sections of the CCS from images acquired ex‐vivo. In this paper we present an algorithm to estimate the location of a set of Purkinje‐myocardial...
Article
Full-text available
Introduction: Focal atrial tachycardia is commonly treated by radio frequency ablation with an acceptable long-term success. Although the location of ectopic foci tends to appear in specific hot-spots, they can be located virtually in any atrial region. Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for...
Article
Modeling the cardiac conduction system is a challenging problem in the context of computational cardiac electrophysiology. Its ventricular section, the Purkinje system, is responsible for triggering tissue electrical activation at discrete terminal locations, which subsequently spreads throughout the ventricles. In this paper, we present an algorit...
Article
Full-text available
Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain a...
Data
Basket’s phase maps in the SVC position. Color-coded phase maps computed based on the HT of the filtered and interpolated basket’s EGMs. PSs are depicted in white superimposed over the phase maps. (AVI)
Data
Sources regions to analyze the effect of far field. A) Views of the tissue encompassing the CT rotor and the RWE (A1), IMPSs and RWE (A2) and CT rotor (A3) on the endocardial phase maps. B) Views of the tissue encompassing only the CT rotor (B1), RWE (B2) and CT rotor (B3) on the endocardial phase maps. Black lines enhance the border of the sources...
Data
Sensitivity of the phase maps. Color scale magnification in the EGMs maps shown in Fig 8 (first and second column), and corresponding traces of the EGMs at points 1 and 2 when considering for the computations with the limited sources regions as shown in Fig 8: whole atrial tissue (A1), tissue encompassing the CT rotor and the RWE (B1) and tissue en...
Data
Basket’s phase maps in the CT position. The layout of this video is the same as in S2 Video. (AVI)
Data
Atrial activation times. Snapshots of the atrial activation spread following Sino-atrial node (SAN) activation and comparison of the simulated activation times at different points of the atria with the experimental activation times reported by Lemery et al[36]. (TIFF)
Data
Inter-electrode distances. Inter-electrode distances for 4 x 16 (A), 8 x 8 (B) and 16 x 16 (C) basket configurations. (TIF)
Data
Phases computed based on the HT of filtered EGMs. Plots of the phases: in the endocardium corresponding to points 1–5 (left) and 6–10 (right) in Fig 3 (A); at some electrodes in the basket for the SVC (B), CT (C) and CS (D) positions, corresponding to Fig 5–7 respectively. (TIF)
Data
Phases at the basket’s south pole. A) Phases in the last (south-most) ring of electrodes (A8 to H8) at t = 5200 ms when the basket was located at the SVC, CT and CS positions. Only in case of the CT position a circulating activation corresponding to the RWE (black arrow) can be observed, as shown by the phases’ color code. In case of the SVC and CS...
Data
Basket phase maps of simulation following secession of the high frequency pacing close to the CS. Snapshots for the SVC (A), CT (B) and CS (C) baskets positions are shown for 11200 and 15000 ms time points and demonstrate IMPSs presence as in the simulation that includes the stimuli train. SVC and IVC: superior and inferior vena cava; TV: tricuspid...
Data
Simulated atrial propagation and phase maps on the endocardium-blood interface. A) Electrical propagation in the atria along the simulation time; B) Phase maps on the endocardium-blood interface, whose computation was based on the HT of the filtered EGMs. PS detections are overlapped to the phase maps (white). (AVI)
Data
Basket’s phase maps in the CS position. The layout of this video is the same as in S2 Video. (AVI)
Data
Phase maps hypersensitivity. Video of the EGMs and phase map corresponding to Fig 8 and S7 Fig. (MP4)
Data
PS detections with baskets with various densities of electrodes. Percentage time of detection of the CT rotor, RWE, IMPSs and FIPSs for the 3 positions of the basket when the density of electrodes was 4×6, 8×8 and 16×16. aNo PSs but sequential activation A8→H8. bDetection possibly masked by the FIPSs at electrodes A4-A5-A6-B4-B5-B6. cThe low densit...
Data
(panel A) Comparison of duration of dynamin 1–2 events with and without dynab (expressed in seconds), and statistical report.
Data
(panel C) Data and statistical analysis of EGF internalization in HeLa cells.
Data
(panel C) Relative frequency Δt values; Δt distribution expressed in percentage of relative dynamin duration.
Data
(panel D and F) Maximum intensity values of dynab peaks vs dynamin peaks.
Data
(panel B) Comparison of duration of dynamin 1–2 events with dynab events in TKO cells (expressed in seconds), and statistical report.
Data
(panel B) Comparison of duration of dynamin 1–2 events with dynab events in Hela cells (expressed in seconds), and statistical report.
Data
(panel C) Cumulative probability of time difference between t(dynab)-t(dyn1-2) and DYNctrl in HeLa cells, and statistical report.
Data
Data and statistical analysis of CCPs persistence in presence of dynab in HeLa cells.
Data
(panel C) Cumulative probability of time difference between t(dynab)-t(dyn1-2) and DYNctrl in TKO cells, and statistical report.
Data
(panel C) Data and statistical analysis of transferrin internalization in HeLa cells.
Article
Full-text available
Dynamin is a large GTPase that forms a helical collar at the neck of endocytic pits, and catalyzes membrane fission (1, 2). Dynamin fission reaction is strictly dependent on GTP hydrolysis, but how fission is mediated is still debated (3): GTP energy could be spent in membrane constriction required for fission, or in disassembly of the dynamin poly...
Conference Paper
Full-text available
The activation of the myocardial muscle is triggered by Purkinje-myocardial junctions (PMJs), which are the terminal sites of the specialised cardiac conduction system (CCS). Obtaining the location of the PMJs and other sources of endocardial ectopic activity would be desirable for building computer models of cardiac electrophysiology and planning...
Article
The cardiac electrophysiology (EP) problem is governed by a nonlinear anisotropic reaction-diffusion system with a very rapidly varying reaction term associated with the transmembrane cell current. The nonlinearity associated with the cell models requires a stabilization process before any simulation is carried out. More importantly, when used in a...
Article
Full-text available
Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward bod...
Data
P-wave morphologies registered for the 57 ectopic sites plus de SAN. Position of the precordial leads on the torso surface and P-wave morphology registered at V1 (blue), V3 (red) and V5 (green) for the sites stimulated on RA (30 sites plus SAN) and the sites stimulated on LA (27 sites). The doted purple square, for example, identifies the P-waves r...
Data
Validation of the atrial and torso models comparing the experimental activations with the simulations carried out by activating ectopic foci at the same sites. a) Local activation times (LATs) computed by activating the SAN, and the 17 RA sites (upper panel) defined in [8] and at the 14 LA sites (lower panel) defined in [10,11]. Bluish colours corr...
Data
Anatomical sites of the atrial ectopic foci. 58 ectopic foci (including the SAN) grouped by RA and LA segment locations. The first 17 and 14 sites on RA and LA respectively (31 sites in total) were placed at the same positions used in previous experimental studies [8,10]. The additional 13 sites on each atrium (26 sites in total) were randomly sele...