Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Abstract

<jats:p>Patient-specific computer simulations can be a powerful tool in clinical applications, helping in diagnostics and the development of new treatments. However, its practical use depends on the reliability of the models. The construction of cardiac simulations involves several steps with inherent uncertainties, including model parameters, the generation of personalized geometry and fibre orientation assignment, which are semi-manual processes subject to errors. Thus, it is important to quantify how these uncertainties impact model predictions. The present work performs uncertainty quantification and sensitivity analyses to assess the variability in important quantities of interest (QoI). Clinical quantities are analysed in terms of overall variability and to identify which parameters are the major contributors. The analyses are performed for simulations of the left ventricle function during the entire cardiac cycle. Uncertainties are incorporated in several model parameters, including regional wall thickness, fibre orientation, passive material parameters, active stress and the circulatory model. The results show that the QoI are very sensitive to active stress, wall thickness and fibre direction, where ejection fraction and ventricular torsion are the most impacted outputs. Thus, to improve the precision of models of cardiac mechanics, new methods should be considered to decrease uncertainties associated with geometrical reconstruction, estimation of active stress and of fibre orientation.</jats:p> <jats:p>This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.</jats:p>

Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium

“…Another closely related task of UQ is sensitivity analysis for identifying important input parameters. Surrogate models have been used in sensitivity study of cardiac models [ 70 ] for alleviating the computational expense. Till now, most of UQ and sensitivity studies have been carried out on electrophysiology modelling [ 39 , 68 , 69 ] but less on biomechanics modelling of cardiac dynamics [ 70 ].…”

“…Surrogate models have been used in sensitivity study of cardiac models [ 70 ] for alleviating the computational expense. Till now, most of UQ and sensitivity studies have been carried out on electrophysiology modelling [ 39 , 68 , 69 ] but less on biomechanics modelling of cardiac dynamics [ 70 ]. A comprehensive study of UQ in biomechanical cardiac models is necessary if they are aiming for clinical applications.…”

Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning

“…Sensitivity analysis through the evaluation of Sobol indices has been performed in Reference 89 on output QoIs such as the inner cavity volume, apex lengthening, wall thickness and volume by considering material parameters that characterize the global myocardial stiffness and the local muscle fiber orientation, however relying on PC expansions and quasi Monte Carlo sampling techniques. A similar analysis, aiming at quantifying the importance of regional wall thickness, fiber orientation, passive material parameters, active stress and the circulatory model in cardiac mechanics, has been addressed in, 90 where surrogate models have been again generated through PC expansions. However, this approach might suffer from two limitations, namely (i) the assumption that the output is a smooth function of the input parameters, and (ii) the need of constructing an emulator for each output QoI of interest.…”

Impact of uncertainties in cardiac mechanics simulations

“…Esta seção apresenta os resultados de um dos experimentos desenvolvidos na tese e publicado no trabalho [Campos et al 2020]. As análises de quantificação de incertezas e sensibilidade foram realizadas considerando incertezas em parâmetros do modelo constitutivo, na espessura da parede do ventrículo, nosângulos de orientação da fibra e na magnitude da tensão ativa, os quais são regidos por distribuições Normais, com coeficiente de variação de 5%.…”