Fluid–Structure-Electrophysiology interaction (FSEI) in the left-heart: A multi-way coupled computational model

Viola, Francesco; Meschini, Valentina; Verzicco, Roberto

doi:10.1016/j.euromechflu.2019.09.006

Cited by 54 publications

(91 citation statements)

References 77 publications

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“…Furthermore, this model is seen to reproduce cardiac phenomena including ischaemic events and defibrillation [15] and it has been validated through animal experiments [16,17]. More recently, the bidomain model has been coupled with a fluid-structure solver to build a multiphysics model for the left heart including the mitral and aortic valves with the aim of using computer simulations to evaluate medical quantities that would be exceedingly difficult or impossible to be measured in vivo or in vitro [18].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of an electrophysiology model for the left ventricle

Corso

Verzicco

Viola

2020

J. R. Soc. Interface.

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Modelling the cardiac electrophysiology entails dealing with the uncertainties related to the input parameters such as the heart geometry and the electrical conductivities of the tissues, thus calling for an uncertainty quantification (UQ) of the results. Since the chambers of the heart have different shapes and tissues, in order to make the problem affordable, here we focus on the left ventricle with the aim of identifying which of the uncertain inputs mostly affect its electrophysiology. In a first phase, the uncertainty of the input parameters is evaluated using data available from the literature and the output quantities of interest (QoIs) of the problem are defined. According to the polynomial chaos expansion, a training dataset is then created by sampling the parameter space using a quasi-Monte Carlo method whereas a smaller independent dataset is used for the validation of the resulting metamodel. The latter is exploited to run a global sensitivity analysis with nonlinear variance-based indices and thus reduce the input parameter space accordingly. Thereafter, the uncertainty probability distribution of the QoIs are evaluated using a direct UQ strategy on a larger dataset and the results discussed in the light of the medical knowledge.

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Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of an electrophysiology model for the left ventricle

Corso

Verzicco

Viola

2020

J. R. Soc. Interface.

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“…The droplets are fully coupled to the liquid phase DNS using the immersed boundary method (IBM) and the interaction potential approach, both of which are versatile numerical methodologies to simulate fully coupled fluid flows with deformable interfaces (e.g. Meschini et al 2018; Spandan, Verzicco & Lohse 2018 b ; Viola, Meschini & Verzicco 2020). Furthermore, IBM offers some computational advantages over existing numerical methods for multiphase flows (e.g.…”

Section: Introductionmentioning

confidence: 99%

Non-monotonic transport mechanisms in vertical natural convection with dispersed light droplets

Spandan

Verzicco

et al. 2020

J. Fluid Mech.

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“…with a moving boundary in an attempt to quantify blood flow (local hemodynamics) inside the LV, but none of these studies considered LV tissue thickness or other tissue characteristics 40,59,62,64,66,[132][133][134][135][136] . In addition, several researchers have recently used FSI as a promising tool for computational cardiology because it allows for the complete coupling of the heart wall and blood flow mechanics, thus demonstrating its worth as the most comprehensive tool for numerical modeling of the LV 60,[137][138][139][140][141][142][143][144][145][146][147][148][149][150][151][152][153][154] . However, since: (1) patient-specific boundary conditions were not used; (2) normal valves and ventricles were modeled instead of those with C3VD; and (3) patient-specific geometries were not used, the models developed in these studies didn't satisfy the three requirements outlined in the Introduction 60,[137][138][139][140][141][142][143][144][145][146][147][148]…”

Section: Discussionmentioning

confidence: 99%

“…However, since: (1) patient-specific boundary conditions were not used; (2) normal valves and ventricles were modeled instead of those with C3VD; and (3) patient-specific geometries were not used, the models developed in these studies didn't satisfy the three requirements outlined in the Introduction 60,[137][138][139][140][141][142][143][144][145][146][147][148][149][150][151][152][153][154] . While some models were partially validated using DE 145,152 or MRI 60 , many were not validated. Five of the studies 60,74,137,143,147 did impose boundary conditions on the calculations by coupling fluid-structure modeling calculations with lumped-parameter modeling, but the lumped-parameter models were either not patient-specific and/or they required information from MRI.…”

Section: Discussionmentioning

confidence: 99%

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

Khodaei

Henstock

Sadeghi

et al. 2021

Sci Rep

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One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

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Fluid–Structure-Electrophysiology interaction (FSEI) in the left-heart: A multi-way coupled computational model

Cited by 54 publications

References 77 publications

Sensitivity analysis of an electrophysiology model for the left ventricle

Sensitivity analysis of an electrophysiology model for the left ventricle

Non-monotonic transport mechanisms in vertical natural convection with dispersed light droplets

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework

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