ArticleBiomechanics and modeling in mechanobiology2016
Estimation of passive and active properties in the human heart using 3D tagged MRI.
Article in Biomechanics and modeling in mechanobiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Non-invasive Model-Based Assessment of Passive Left-Ventricular Myocardial Stiffness in Healthy Subjects and in Patients with Non-ischemic Dilated Cardiomyopathy.Annals of biomedical engineering · 2017Trial
- Inverse analysis of patient-specific parameters of a 3D-0D closed-loop cardiovascular model with an exemplary application to an adult tetralogy of Fallot case.Biomechanics and modeling in mechanobiology · 2025Article
- Article
- Estimation of Active Tension in Cardiac Microtissues by Solving a PDE-Constrained Optimization Problem.International journal for numerical methods in biomedical engineering · 2025Article
- Personalized computational electro-mechanics simulations to optimize cardiac resynchronization therapy.Biomechanics and modeling in mechanobiology · 2024Article
- Validating MRI-Derived Myocardial Stiffness Estimates Using In Vitro Synthetic Heart Models.Annals of biomedical engineering · 2023Article
- Robust and efficient fixed-point algorithm for the inverse elastostatic problem to identify myocardial passive material parameters and the unloaded reference configuration.Journal of computational physics · 2022Article
- Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics.Biomechanics and modeling in mechanobiology · 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
- Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications.Applied sciences (Basel, Switzerland) · 2022Article
- An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics.Mathematics (Basel, Switzerland) · 2022Article
- A guide for assessment of myocardial stiffness in health and disease.Nature cardiovascular research · 2022Review
- Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods.Frontiers in physiology · 2022Article
- Biomechanical Modeling to Inform Pulmonary Valve Replacement in Tetralogy of Fallot Patients After Complete Repair.The Canadian journal of cardiology · 2021Observational
- An Implementation of Patient-Specific Biventricular Mechanics Simulations With a Deep Learning and Computational Pipeline.Frontiers in physiology · 2021Article
- Synergy in the heart: RV systolic function plays a key role in optimizing LV performance during exercise.American journal of physiology. Heart and circulatory physiology · 2020Article
- Analysis of Cardiac Amyloidosis Progression Using Model-Based Markers.Frontiers in physiology · 2020Article
- On the AIC-based model reduction for the general Holzapfel-Ogden myocardial constitutive law.Biomechanics and modeling in mechanobiology · 2019Article
- A Contemporary Look at Biomechanical Models of Myocardium.Annual review of biomedical engineering · 2019Review
- Patient-specific in vivo right ventricle material parameter estimation for patients with tetralogy of Fallot using MRI-based models with different zero-load diastole and systole morphologies.International journal of cardiology · 2019Article
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Authors and funding
13 authors.
Funding
Abstract
Advances in medical imaging and image processing are paving the way for personalised cardiac biomechanical modelling. Models provide the capacity to relate kinematics to dynamics and-through patient-specific modelling-derived material parameters to underlying cardiac muscle pathologies. However, for clinical utility to be achieved, model-based analyses mandate robust model selection and parameterisation. In this paper, we introduce a patient-specific biomechanical model for the left ventricle aiming to balance model fidelity with parameter identifiability. Using non-invasive data and common clinical surrogates, we illustrate unique identifiability of passive and active parameters over the full cardiac cycle. Identifiability and accuracy of the estimates in the presence of controlled noise are verified with a number of in silico datasets. Unique parametrisation is then obtained for three datasets acquired in vivo. The model predictions show good agreement with the data extracted from the images providing a pipeline for personalised biomechanical analysis.
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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.