New methodologies for the development and validation of electrophysiological models
- Autores: Jesús Carro Fernández
- Directores de la Tesis: José Félix Rodríguez Matas (dir. tes.), Esther Pueyo Paules (dir. tes.)
- Lectura: En la Universidad de Zaragoza ( España ) en 2019
- Idioma: español
- Tribunal Calificador de la Tesis: José María Ferrero de Loma-Osorio (presid.), Violeta Monasterio Bazán (secret.), Carlos Sánchez Tapia (voc.), Trine Krogh-Madsen (voc.), Elisabetta Angela Passoni (voc.)
- Programa de doctorado: Programa de Doctorado en Ingeniería Biomédica por la Universidad Politécnica de Catalunya y la Universidad de Zaragoza
- Materias:
- Enlaces
- Tesis en acceso abierto en: Zaguán
- Resumen
According to data from the World Health Organization (WHO), 17.7 million people were estimated to have died of cardiovascular diseases (CVDs) in 2015. This represents 31 of all global deaths, making CVDs the leading cause of death worldwide. The heart is a complex system that works due to the interaction of a large number of elements at different temporal and spatial scales. The main function of the heart is to pump blood throughout the body, with this mechanical action being triggered by electrical impulses. Issues arising in the electrical or mechanical actions of the heart at any of the involved temporal and spatial scales can lead to cardiac malfunctioning. Mathematical modeling and simulation of the heart's electrical activity (so-called cardiac electrophysiology) combined with signal processing of bioelectrical signals provide an ideal framework to join the information from clinical and experimental studies with the understanding of the mechanisms underlying them. Due to the high number of factors involved in the development and validation of cardiac computational electrophysiological models and the intricate interrelationships between them, novel methodologies that help to control the design, update and validation of new models become of great advantage. These methodologies can target from the definition of ionic gating in the simulated cells to the propagation of the electrical impulse in multi-scale models. This thesis aims to improve the existing knowledge on heart's electrophysiology by proposing novel techniques to develop and validate cardiac computational models while accounting for the interactions between model components and including simulations of a range of spatio-temporal scales.
In chapter 2, a new paradigm was introduced to develop a novel human ventricular cell model, the CRLP model, by departing from a previously published model, the Grandi-Pasqualini-Bers model (Grandi et al., 2009). Novel experimental measurements of potassium currents were incorporated and the L-type calcium current was reformulated. The introduced paradigm was based on the analysis of the model's ability to replicate a set of well-established electrophysiological markers and on a sensitivity analysis of those markers to variations in model parameters (Romero et al., 2008). A major advantage of the proposed paradigm was the possibility to identify model parameter values that do not directly depend on individual current measurements or concentrations, which are commonly set in an ad hoc manner. The developed CRLP model was validated and its improved capacity to investigate arrhythmia-related properties, as compared to the cell model it was based on, was corroborated.
In chapter 3, the CRLP model developed in chapter 2 was updated to introduce the formulation of intracellular potassium ([K+]i) dynamics. This is an important characteristic for investigation of ventricular arrhythmias arising under conditions of hyperkalemia, one of the components of myocardial ischemia (Coronel et al. 1988). Direct introduction of [K+]i dynamics into the model generated an imbalance in the potassium currents leading to a drift in [K+]i. To correct for such an imbalance, an optimization framework was proposed that allowed estimating the ionic current conductances of the CRLP model while guaranteeing physiologically plausible values of selected electrophysiological properties, many of them highly relevant for investigation of ventricular arrhythmias.
As mentioned above, when proposing a new model, or when updating an existing model, consistency between simulated and experimental data should be verified by considering all involved effects and scales. The closer the experimental conditions are reproduced in the computer simulations, the more robust the process of model development and validation can be. In chapter 4, in silico simulation of experimental protocols was proposed to analyze: how interactions between model components affect the development and validation of mathematical ion channel models; and how propagation affects action potential (AP)-based markers simulated in isolated cells and in tissue preparations, with identification of the ionic contributors in each case.
The CRLP model, developed in chapter 2 and updated in chapter 3, presented a rather atypical shape at the end of the depolarization phase of the AP (phase 1). In chapter 5, the in silico simulations of experimental protocols described in chapter and the optimization methodology introduced in chapter 3 were used to improve the AP shape, while validating the adjusted model at ionic, cell and tissue scales.
In chapter 6, all the initial formulations and subsequent updates of the CRLP model proposed in previous chapters were integrated and the ionic conductances of the integrated model were readjusted to improve replication of experimental electrophysiological measures. All the methodologies introduced throughout the thesis were thus used to build a novel human ventricular AP model. For model validation, a range of available experimental data at different scales targetting different electrophysiological properties was considered. Conditions underlying each of the experimental studies were replicated as faithfully as possible. Results simulated with the final version of the CRLP model were in all cases compared with all available experimental evidences and with the most recent human ventricular cell models published in the literature.
Chapter 7, summarizes the main conclusions of the thesis and presents new lines of research that could be undertaken in future studies.
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