In vivo estimation of normal left ventricular stiffness and contractility based on routine cine MR acquisition

Rumindo, Gerardo Kenny; Ohayon, Jacques; Croisille, Pierre; Clarysse, Patrick

doi:10.1016/j.medengphy.2020.09.003

Cited by 16 publications

(8 citation statements)

References 47 publications

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“…According to Sommer et al, the myocardial stiffness in the fiber direction was about twice as stiff as in the cross-fiber direction from the biaxial extension testing (Sommer et al 2015 ). Therefore, we specified to be 29.8, twice that of and , which were 14.9, in accordance with the previous FEM studies (Rumindo et al 2020 ; Shavik et al 2018 ).…”

Section: Methodsmentioning

confidence: 74%

“…The incompressible criteria were enforced in the FE solver, by minimizing the deformation Jacobian (Shavik et al 2018 ). For simulations of healthy LV, C was assumed to be 100 Pa, which was consistent with past simulation work (Rumindo et al 2020 ; Shavik et al 2018 ), but for HCM and DCM diseased conditions, they could increase to 300 Pa and 200 Pa, respectively, as informed by findings that diastolic dysfunction increases myocardial stiffness by 2–3 times (Klotz et al 2005 ; Wang et al 2018 ; Westermann et al 2008 ).…”

Section: Methodsmentioning

confidence: 76%

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Effects of myocardial sheetlet sliding on left ventricular function

Zheng

Chan

Nielles‐Vallespin

et al. 2023

Biomech Model Mechanobiol

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Left ventricle myocardium has a complex micro-architecture, which was revealed to consist of myocyte bundles arranged in a series of laminar sheetlets. Recent imaging studies demonstrated that these sheetlets re-orientated and likely slided over each other during the deformations between systole and diastole, and that sheetlet dynamics were altered during cardiomyopathy. However, the biomechanical effect of sheetlet sliding is not well-understood, which is the focus here. We conducted finite element simulations of the left ventricle (LV) coupled with a windkessel lumped parameter model to study sheetlet sliding, based on cardiac MRI of a healthy human subject, and modifications to account for hypertrophic and dilated geometric changes during cardiomyopathy remodeling. We modeled sheetlet sliding as a reduced shear stiffness in the sheet-normal direction and observed that (1) the diastolic sheetlet orientations must depart from alignment with the LV wall plane in order for sheetlet sliding to have an effect on cardiac function, that (2) sheetlet sliding modestly aided cardiac function of the healthy and dilated hearts, in terms of ejection fraction, stroke volume, and systolic pressure generation, but its effects were amplified during hypertrophic cardiomyopathy and diminished during dilated cardiomyopathy due to both sheetlet angle configuration and geometry, and that (3) where sheetlet sliding aided cardiac function, it increased tissue stresses, particularly in the myofibre direction. We speculate that sheetlet sliding is a tissue architectural adaptation to allow easier deformations of the LV walls so that LV wall stiffness will not hinder function, and to provide a balance between function and tissue stresses. A limitation here is that sheetlet sliding is modeled as a simple reduction in shear stiffness, without consideration of micro-scale sheetlet mechanics and dynamics.

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Section: Methodsmentioning

confidence: 74%

Section: Methodsmentioning

confidence: 76%

Effects of myocardial sheetlet sliding on left ventricular function

Zheng

Chan

Nielles‐Vallespin

et al. 2023

Biomech Model Mechanobiol

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“…These methods use imaging techniques (MRI, ultrasound, etc.) in combination with 3D simulations of the contracting myocardium, to predict mechanical tissue properties (Wang et al 2013c;Mojsejenko et al 2015;Wang et al 2018b;Palit et al 2018;Rumindo et al 2020). Computational models of MRI-based diastolic ventricular anatomy are constructed using finite element methods including either measured, predicted or generic prevailing CM directions to define tissue anisotropy.…”

Section: In Vivo Techniques With Potential Clinical Applicationmentioning

confidence: 99%

Passive myocardial mechanical properties: meaning, measurement, models

et al. 2021

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Passive mechanical tissue properties are major determinants of myocardial contraction and relaxation and, thus, shape cardiac function. Tightly regulated, dynamically adapting throughout life, and affecting a host of cellular functions, passive tissue mechanics also contribute to cardiac dysfunction. Development of treatments and early identification of diseases requires better spatio-temporal characterisation of tissue mechanical properties and their underlying mechanisms. With this understanding, key regulators may be identified, providing pathways with potential to control and limit pathological development. Methodologies and models used to assess and mimic tissue mechanical properties are diverse, and available data are in part mutually contradictory. In this review, we define important concepts useful for characterising passive mechanical tissue properties, and compare a variety of in vitro and in vivo techniques that allow one to assess tissue mechanics. We give definitions of key terms, and summarise insight into determinants of myocardial stiffness in situ. We then provide an overview of common experimental models utilised to assess the role of environmental stiffness and composition, and its effects on cardiac cell and tissue function. Finally, promising future directions are outlined.

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“…Cardiac material parameters have been evaluated from FEA models of large animals, either from passive left ventricles (LVs) (Wang et al 2009;Nikou et al 2016a, b) or from biventricular hearts of animals with both passive and active contributions (Sack et al 2018;Dabiri et al 2019). The LV of the human heart has also been considered for computational modeling with passive (Nasopoulou et al 2017;Balaban et al 2018;Wang et al 2018) or both passive and active effects (Xi et al 2013;Genet et al 2014;Asner et al 2016;Gao et al 2017;Finsberg et al 2018a;Rumindo et al 2020;Zhang et al 2020). Marx et al (2022) used an inverse method to identify the unloaded mesh and the passive material parameters of the LV simultaneously in patients diagnosed with aortic valve stenosis and aortic coarctation.…”

Section: Introductionmentioning

confidence: 99%

Personalized Evaluation of the Passive Myocardium in Ischemic Cardiomyopathy via Computational Modeling Using Bayesian Optimization

Torbati,

Daneshmehr,

Pouraliakbar

et al. 2024

Preprint

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Biomechanics-based patient-specific modeling is a promising approach that has proved invaluable for its clinical potential to assess the adversities caused by ischemic heart disease (IDH). In the present study, we propose a framework to find the passive material properties of the myocardium and the unloaded shape of cardiac ventricles simultaneously in patients diagnosed with ischemic cardiomyopathy (ICM). This was achieved by minimizing the difference between the simulated and target end-diastolic pressure-volume relationships (EDPVRs) using black-box Bayesian optimization, based on the finite element analysis (FEA). End-diastolic (ED) biventricular geometry and the location of the ischemia were determined from cardiac magnetic resonance (CMR) imaging. We employed our pipeline to model the cardiac ventricles of three patients aged between 57 and 66 years, with and without the inclusion of valves. An excellent agreement between the simulated and target EDPVRs has been reached. Our results revealed that the incorporation of valvular springs typically leads to lower hyperelastic parameters for both healthy and ischemic myocardium, as well as a higher fiber Green strain in the viable regions compared to models without valvular stiffness. Furthermore, the addition of valve-related effects did not result in significant changes in myofiber stress after optimization. We concluded that more accurate results could be obtained when cardiac valves were considered in modeling ventricles. The present novel and practical methodology paves the way for developing digital twins of ischemic cardiac ventricles, providing a non-invasive assessment for designing optimal personalized therapies in precision medicine.

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In vivo estimation of normal left ventricular stiffness and contractility based on routine cine MR acquisition

Cited by 16 publications

References 47 publications

Effects of myocardial sheetlet sliding on left ventricular function

Effects of myocardial sheetlet sliding on left ventricular function

Passive myocardial mechanical properties: meaning, measurement, models

Personalized Evaluation of the Passive Myocardium in Ischemic Cardiomyopathy via Computational Modeling Using Bayesian Optimization

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