2 research outputs found
Electromechanical large scale computational models of the ventricular myocardium
Els models computacionals del cor sĂłn una eina important que pot donar als investigadors biomèdics una font addicional d’informaciĂł per entendre el funcionament del miocardi. Els models numèrics poden ajudar a interpretar dades experimentals i proporcionar informaciĂł complementĂ ria sobre mecanismes cardĂacs que no poden ser determinats amb precisiĂł mitjançant dispositius clĂnics clĂ ssics. En aquesta tesi, s’apliquen tècniques de computaciĂł a gran escala per construir una eina computacional capaç d’executar-se en paral•lel en milers de processadors, permetent simulacions
d’alta fidelitat en malles fines. Per simular el bombeig del cor, s’utilitza un esquema d’acoblament explĂcit entre les equacions electrofisiològiques en tres dimensions i la formulaciĂł en mecĂ nica de sòlids. Per trobar la soluciĂł numèrica, s’utilitza el mètode d’elements finits. A mĂ©s, s’implementen tècniques en assimilaciĂł de dades per a l’estimaciĂł efectiva dels parĂ metres electrofisiològics i mecĂ nics rellevants que apareixen a les equacions, la qual cosa ´es un pas crucial cap a un model cardĂac sensible a cada pacient. El codi computacional s’aplica per simular problemes fĂsics reals. S’estudia la propagaciĂł electromecĂ nica en una geometria de conill, on es prova la sensibilitat del model a les variacions d’entrada. En particular, l’eina de cĂ lcul s’utilitza per avaluar la influència del camp de fibres cardĂaques en la contracciĂł del teixit.
Per desenvolupar una simulaciĂł cardĂaca Ăştil per a fins clĂnics, el model requereix la integraciĂł i combinaciĂł de la mecĂ nica computacional i les tècniques de processament d’imatge mĂ©s recents. El model resultant pot ser la base d’estudis teòrics sobre mecanismes de patologies, oferint als investigadors i cardiòlegs pistes addicionals per comprendre el funcionament del cor. Pot ajudar a la planificaciĂł de cirurgia i modelitzaciĂł, com Ă©s la predicciĂł dels efectes de compostos farmacològics en el ritme cardĂac o l’estudi de l’efecte de medicaments. Aquest projecte nomĂ©s Ă©s possible en un equip multidisciplinar, on grups especialitzats uneixen les seves forces en les respectives disciplines: cardiòlegs, investigadors imatge, bioenginyers i cientĂfics de la computaciĂł. El present model computacional del cor Ă©s un pas mĂ©s cap a la creaciĂł d’un laboratori cardĂac virtual.A cardiac computational model is a relevant tool that can give biomedical researchers an additional source of information to understand how the heart works. Numerical models can help to interpret experimental data and provide information about cardiac mechanisms that can not be determined accurately by classical clinical devices. In this thesis, High Performance Computing (HPC) techniques are used to build a cardiac computational tool, which is capable of running in parallel in thousands of processors, bioengineers and computational scientists. The present cardiac computational model is one further step towards the creation of a virtual lab, allowing high fidelity simulations on fine meshes. To simulate the pumping heart, an explicit coupling scheme between the three-dimensional electrophysiological equations and the solid mechanics formulation is used, solving the governing equations with finite element methods. Also, data assimilation techniques are implemented for the effective estimation of some relevant electrophysiological parameters, which is a crucial step towards the patient-sensitive cardiac model. The data assimilation techniques are assessed on synthetic data generated by the model. Finally, the computational code is applied to simulate real physical problems. The electromechanical propagation in a rabbit geometry is studied to test the sensitivity of the framework to input variations. Particularly, the computational tool is used to evaluate the influence of the fiber field in the contraction of the tissue. To develop a cardiac simulation useful for clinical purposes, the integrative model requires combining computational mechanics and image processing techniques via data assimilation methods. Coupled with the most advanced image processing analysis, the framework can be the base of theoretical studies into the mechanisms of cardiac pathologies. It can help surgery planning and cardiac modeling, such as the prediction of the impact of pharmacological compounds on the heart’s rhythm or to improve the knowledge of drug study, giving medical researchers additional hints to understand the heart. This realization is only possible in a multidisciplinary team, where specialized groups join forces in their respective disciplines: cardiologists, image researchers, bioengineers and computational scientists. The present cardiac computational model is one further step towards the creation of a virtual la