Validating MRI-Derived Myocardial Stiffness Estimates Using In Vitro Synthetic Heart Models

Kolawole, Fikunwa O.; Peirlinck, Mathias; Cork, Tyler E.; Levenston, Marc E.; Kuhl, Ellen; Ennis, Daniel B.

doi:10.1007/s10439-023-03164-7

Cited by 6 publications

(1 citation statement)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using cine-MRI patient data, transversely isotropic laws were used to quantify passive stiffness in patients with aortic coarctation and aortic valve stenosis [136], myocardial infarction [137], and to compare the passive stiffness of healthy controls and patients with dilated cardiomyopathy [138], HF [139], and tetralogy of Fallot [140]. Similar works have also been done using 3D printed phantoms [141]. All these applications made use of transversely isotropic laws and, in many cases, the number of estimated parameters was reduced either by using prior relationship between parameters or by fixing a subset of them.…”

Section: Passive Mechanicsmentioning

confidence: 99%

Advancing clinical translation of cardiac biomechanics models: a comprehensive review, applications and future pathways

Rodero,

Baptiste,

Barrows

et al. 2023

Front. Phys.

View full text Add to dashboard Cite

Cardiac mechanics models are developed to represent a high level of detail, including refined anatomies, accurate cell mechanics models, and platforms to link microscale physiology to whole-organ function. However, cardiac biomechanics models still have limited clinical translation. In this review, we provide a picture of cardiac mechanics models, focusing on their clinical translation. We review the main experimental and clinical data used in cardiac models, as well as the steps followed in the literature to generate anatomical meshes ready for simulations. We describe the main models in active and passive mechanics and the different lumped parameter models to represent the circulatory system. Lastly, we provide a summary of the state-of-the-art in terms of ventricular, atrial, and four-chamber cardiac biomechanics models. We discuss the steps that may facilitate clinical translation of the biomechanics models we describe. A well-established software to simulate cardiac biomechanics is lacking, with all available platforms involving different levels of documentation, learning curves, accessibility, and cost. Furthermore, there is no regulatory framework that clearly outlines the verification and validation requirements a model has to satisfy in order to be reliably used in applications. Finally, better integration with increasingly rich clinical and/or experimental datasets as well as machine learning techniques to reduce computational costs might increase model reliability at feasible resources. Cardiac biomechanics models provide excellent opportunities to be integrated into clinical workflows, but more refinement and careful validation against clinical data are needed to improve their credibility. In addition, in each context of use, model complexity must be balanced with the associated high computational cost of running these models.

show abstract