ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2020
Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Simulating impaired left ventricular-arterial coupling in aging and disease: a systematic review.Biomedical engineering online · 2024Pooled it
- Post-MI Remodeling Mechanics of Left Ventricle: Microstructure-Informed Models, Identifiability, and Uncertainty for Patient-Specific Prediction.Bioengineering (Basel, Switzerland) · 2026Review
- Towards personalization of 1D blood flow models: sensitivity analysis and parameter calibration.Biomechanics and modeling in mechanobiology · 2026Article
- Characterizing variability in passive myocardial stiffness in healthy human left ventricles using personalized MRI and finite element modeling.Scientific reports · 2025Article
- Parameter inference in a computational model of haemodynamics in pulmonary hypertension.Journal of the Royal Society, Interface · 2023Article
- Quantitative mapping of force-pCa curves to whole-heart contraction and relaxation.The Journal of physiology · 2022Article
- A Computationally Efficient Approach to Simulate Heart Rate Effects Using a Whole Human Heart Model.Bioengineering (Basel, Switzerland) · 2022Article
- Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics.Biomechanics and modeling in mechanobiology · 2022Article
- Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation.PLoS computational biology · 2022Article
- Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data.NMR in biomedicine · 2022Article
- Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle.International journal for numerical methods in biomedical engineering · 2022Article
- Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods.Frontiers in physiology · 2022Article
- Causes of altered ventricular mechanics in hypertrophic cardiomyopathy: an in-silico study.Biomedical engineering online · 2021Article
- Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning.International journal for numerical methods in biomedical engineering · 2021Article
- Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function.International journal for numerical methods in biomedical engineering · 2021Article
- An Implementation of Patient-Specific Biventricular Mechanics Simulations With a Deep Learning and Computational Pipeline.Frontiers in physiology · 2021Article
- Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium.Royal Society open science · 2021Article
- Commentary: Fast and accurate surrogate of finite-element analysis: For bench to bedside, we need it now!JTCVS techniques · 2020Article
- The fickle heart: uncertainty quantification in cardiac and cardiovascular modelling and simulation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.