Identificación del sustrato de las taquicardias ventriculares mono mórficas sostenidas durante ritmo sinusal en pacientes con infarto previo de miocardio: implicaciones para la ablación de TV no cartografiables

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Medicina, leída el 21-12-2012Identificación del sustrato de las taquicardias monomórficas sostenidas durante ritmo sinusal en pacientes con infarto previo de miocardio. Implicaciones para la ablación de TV no cartografiables Ángel Arenal Antecedentes; Estudios cartográficos de las cicatrices postinfarto con sistemas de reconstrucción tridimensional han demostrado que los electrogramas con componentes aislados tardíos (E-CAT) y los Canales de conducción (CC) son el sustrato de la mayoría de las TV. Tanto los E-CAT como los CC son marcadores sensibles y específicos de los istmos de conducción lenta de las TV ya que en más del 90 por ciento de estos istmos se registran E-CAT durante ritmo sinusal (RS). La ablación de todos los E-CAT y CC durante RS, a partir de este momento denominada ablación completa del sustrato endocárdico de las TV (ACSETV) podría simplificar y facilitar el procedimiento de ablación, principalmente en los pacientes sin ECG de las TV clínicas y por tanto sin referencias parar la localización del sustrato de una taquicardia específica. Objetivo. El objetivo de este estudio fue determinar la seguridad, eficacia e identificar los predictores de recurrencia de la ACSETV.Fac. de MedicinaTRUEunpu

Ecología y epidemiología de las salmonellas en las aguas polucionadas del canal del Jarama : nueva metodología de detección

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída en 1981.Fac. de Ciencias BiológicasTRUEProQuestpu

Ecología y epidemiología de las salmonellas en las aguas polucionadas del canal del Jarama : nueva metodología de detección

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída en 1981.Fac. de Ciencias BiológicasTRUEProQuestpu

Real-time ventricular cancellation in unipolar atrial fibrillation electrograms

Unipolar atrial fibrillation (AF) electrograms (EGMs) require far-field ventricle cancellation to recover hidden atrial activations. Current methods cannot achieve real-time cancellation because of the temporal delay they introduce. We propose a new real-time ventricular cancellation (RVC) method based on causal implementation optimized for real-time functioning. The method is similar to the classical average beat subtraction (ABS) method but it computes the ventricular contribution before the ventricular activation finishes. We compare the proposed method to the ABS on synthetic and real EGM databases for the time and frequency domains. All parameters and their optimal values are analyzed and validated. The RVC method provides a good reconstruction of the unipolar EGMs and a better local activation time detection than the classical approach with average F1scores 0.7307 and 0.7125, respectively. The spectral analysis shows that the average power after ventricular cancellation is reduced for frequency bands between 3 and 5.5 Hz, demonstrating that the proposed method removes the ventricular component present in the unipolar EGM signals compared to the ABS method. The phase mapping analysis on the RVC method presented lower error when comparing the annotated EGM cycles with the phase inversion intervals. In terms of performance ABS and RVC behave similarly, but the real-time capability of the latter justifies its preference over the offline implementations. In the clinical environment other online investigations, e.g., rotational activity assessment, dominant frequency or local activation time mapping, might benefit from the real-time potential of the proposed cancellation method.This study was supported by grants PI18/01895 from the Instituto de Salud Carlos III, and RD16/0011/0029 Red de Terapia Celular from the Instituto de Salud Carlos III, projects RTI2018-099655-B-I00; TEC2017-92552-EXP from Ministerio de Ciencia, Innovación y Universidades, Y2018/TCS-4705, PRACTICO-CM Comunidad de Madrid, and the support of NVIDIA Corporation with the donation of the Titan V GPU used during this research

Radiation shielding properties of siderurgical aggregate concrete

ABSTRACT: The world is changing, and consequently so are policies on the use of natural resources. One of the most convenient ways to reduce the consumption of natural aggregates in the production of more sustainable construction materials is the use of recovered industrial by-products. In this study, concretes are designed using siderurgical aggregates from electric arc furnaces, taking advantage of their high density to use them as radiation shielding concrete. To verify the suitability of these aggregates, four concrete mixes were designed with different aggregates: limestone, siderurgical magnetite aggregates (the most commonly used in the nuclear field). The comparison of the different mixes was carried out focusing on the physical?mechanical properties in the field of ionizing radiation shielding (gamma radiation and neutron shielding) by means of simulations. In addition, an analysis was performed to establish how the w/c ratio and the amount of CEM affect shielding properties. In terms of linear attenuation coefficient and neutron transmission rate, the concrete with siderurgical aggregates shows intermediate capability in comparison with the limestone aggregate and magnetite concrete. The increase in the amount of cement and the w/c ratio caused a decrease in the linear attenuation coefficient and a reduction in the neutron transmission rate, but the variation in the w/c ratio did not have a significant impact on the neutron transmission rate.This research was co-financed by the European Regional Development Fund (ERDF) and the Ministry of Economy, Industry and Competitiveness (MINECO) within the framework of the project RTC2016-5637-3. The research has been possible thanks to the collaboration of the company INGECID, the department LADICIM (University of Cantabria) the Modern Physics Department of the University of Cantabria and the companies ROCACERO and SIDENOR

Patient-Tailored In Silico 3D Simulations and Models From Electroanatomical Maps of the Left Atrium

Proceeding of 2018 Computing in Cardiology Conference (CinC), September 23-26, 2018, Maastricht, The NetherlandsThe mechanisms underlying atrial fibrillation (AF) are still under debate, making treatments for this arrhythmia remain suboptimal, with most treatments applied in a standard fashion with no patient personalization. Recent technological advances in electroanatomical mapping (EAM) using multi-electrode catheter allow the physicians to better characterize the substrate, thanks to a better spatial resolution and higher density of acquisition points. Taking advantage of this technology, we describe a workflow to build personalized electrophysiological atrial models for AF patients. We seek to better predict the outcome of a treatment and study the AF problem in a more specific scenario. We generated physiological 3D models from the EAM data using hexahedral meshing of element size 300μm, and added fiber orientation based on a generic model. We used the local activation time (LAT) maps performed in sinus rhythm (SR) to estimate the conduction velocity (CV) of the regions in the atrium with a new method that combines the LATs of neighboring tissue as the average CV of triplets of points. We also characterized the cellular model by Maleckar et al. in terms of longitudinal conductivity and CV to personalize the atrial models. We were able to simulate SR and AF scenarios on the personalized models, and we generated a database of atrial models for future analysis.This work has been partly supported by MINECO/FEDER (ADVENTURE, id. TEC2015-69868-C2-1-R), Co munidad de Madrid (CASI-CAM-CM, id. S2013/ICE-2845), Centro de Investigación Biomédica en Red (CIBER), proyecto DPI2016-75458, and the Programa Prometeo, Generalitat Valenciana, Award Number: 2016/088.Publicad

A new algorithm for rhythm discrimination in cardioverter defibrillators based on the initial voltage changes of the ventricular electrogram

Aims: Ventricular activation onset is faster in supraventricular beats than in ventricular rhythms. The aim of this study was to evaluate a criterion to differentiate supraventricular (SVT) from ventricular tachycardia (VT) based on the analysis of the initial voltage changes in ICD-stored morphology electrograms. Methods. Far field ICD-stored EGMs were obtained from 68 VT and 38 SVT episodes in 16 patients. The first EGM peak was detected, three consecutive time epochs were defined within the preceding 80 ms window and the voltage changes with respect to a sinus template were analysed during each time period and combined into a single parameter for rhythm discrimination. Results. The algorithm was tested in an independent validation group of 442 VT and 97 SVT spontaneous episodes obtained from 22 patients with a dual chamber ICD. The area under the receiver-operator characteristics (ROC) curve indicated that the arrhythmia separability with this method was 0.95 (tolerance interval: 0.85-0.99) and 0.98 (0.87-0.99) for the control and validation groups respectively. A specificity of 0.91 was obtained at 95% sensitivity in the validation group. Conclusion. The analysis of voltage changes during the initial ventricular activation process is feasible using the far field stored electrograms of an ICD system and yields a high sensitivity and specificity for arrhythmia discrimination

Convolutional Neural Networks for Mechanistic Driver Detection in Atrial Fibrillation

The maintaining and initiating mechanisms of atrial fibrillation (AF) remain controversial. Deep learning is emerging as a powerful tool to better understand AF and improve its treatment, which remains suboptimal. This paper aims to provide a solution to automatically identify rotational activity drivers in endocardial electrograms (EGMs) with convolutional recurrent neural networks (CRNNs). The CRNN model was compared with two other state-of-the-art methods (SimpleCNN and attention-based time-incremental convolutional neural network (ATI-CNN)) for different input signals (unipolar EGMs, bipolar EGMs, and unipolar local activation times), sampling frequencies, and signal lengths. The proposed CRNN obtained a detection score based on the Matthews correlation coefficient of 0.680, an ATI-CNN score of 0.401, and a SimpleCNN score of 0.118, with bipolar EGMs as input signals exhibiting better overall performance. In terms of signal length and sampling frequency, no significant differences were found. The proposed architecture opens the way for new ablation strategies and driver detection methods to better understand the AF problem and its treatment