A coupled mitral valve -- left ventricle model with fluid-structure interaction

Understanding the interaction between the valves and walls of the heart is important in assessing and subsequently treating heart dysfunction. With advancements in cardiac imaging, nonlinear mechanics and computational techniques, it is now possible to explore the mechanics of valve-heart interactions using anatomically and physiologically realistic models. This study presents an integrated model of the mitral valve (MV) coupled to the left ventricle (LV), with the geometry derived from in vivo clinical magnetic resonance images. Numerical simulations using this coupled MV-LV model are developed using an immersed boundary/finite element method. The model incorporates detailed valvular features, left ventricular contraction, nonlinear soft tissue mechanics, and fluid-mediated interactions between the MV and LV wall. We use the model to simulate the cardiac function from diastole to systole, and investigate how myocardial active relaxation function affects the LV pump function. The results of the new model agree with in vivo measurements, and demonstrate that the diastolic filling pressure increases significantly with impaired myocardial active relaxation to maintain the normal cardiac output. The coupled model has the potential to advance fundamental knowledge of mechanisms underlying MV-LV interaction, and help in risk stratification and optimization of therapies for heart diseases.Comment: 25 pages, 6 figure

Modelling mitral valvular dynamics–current trend and future directions

Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state-of-the-art modelling of the mitral valve, including static and dynamics models, models with fluid-structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed

Interactive editing of virtual chordae tendineae for the simulation of the mitral valve in a decision support system

Purpose: Decision support systems for mitral valve disease are an important step toward personalized surgery planning. A simulation of the mitral valve apparatus is required for decision support. Building a model of the chordae tendineae is an essential component of a mitral valve simulation. Due to image quality and artifacts, the chordae tendineae cannot be reliably detected in medical imaging. Methods: Using the position-based dynamics framework, we are able to realistically simulate the opening and closing of the mitral valve. Here, we present a heuristic method for building an initial chordae model needed for a successful simulation. In addition to the heuristic, we present an interactive editor to refine the chordae model and to further improve pathology reproduction as well as geometric approximation of the closed valve. Results: For evaluation, five mitral valves were reconstructed based on image sequences of patients scheduled for mitral valve surgery. We evaluated the approximation of the closed valves using either just the heuristic chordae model or a manually refined model. Using the manually refined models, prolapse was correctly reproduced in four of the five cases compared to two of the five cases when using the heuristic. In addition, using the editor improved the approximation in four cases. Conclusions: Our approach is suitable to create realistically parameterized mitral valve apparatus reconstructions for the simulation of normally and abnormally closing valves in a decision support system

NOVEL STRATEGIES FOR THE MORPHOLOGICAL AND BIOMECHANICAL ANALYSIS OF THE CARDIAC VALVES BASED ON VOLUMETRIC CLINICAL IMAGES

This work was focused on the morphological and biomechanical analysis of the heart valves exploiting the volumetric data. Novel methods were implemented to perform cardiac valve structure and sub-structure segmentation by defining long axis planes evenly rotated around the long axis of the valve. These methods were exploited to successfully reconstruct the 3D geometry of the mitral, tricuspid and aortic valve structures. Firstly, the reconstructed models were used for the morphological analysis providing a detailed description of the geometry of the valve structures, also computing novel indexes that could improve the description of the valvular apparatus and help their clinical assessment. Additionally, the models obtained for the mitral valve complex were adopted for the development of a novel biomechanical approach to simulate the systolic closure of the valve, relying on highly-efficient mass-spring models thus obtaining a good trade-off between the accuracy and the computational cost of the numerical simulations. In specific: \u2022 First, an innovative and semi-automated method was implemented to generate the 3D model of the aortic valve and of its calcifications, to quantitively describe its 3D morphology and to compute the anatomical aortic valve area (AVA) based on multi-detector computed tomography images. The comparison of the obtained results vs. effective AVA measurements showed a good correlation. Additionally, these methods accounted for asymmetries or anatomical derangements, which would be difficult to correctly capture through either effective AVA or planimetric AVA. \u2022 Second, a tool to quantitively assess the geometry of the tricuspid valve during the cardiac cycle using multidetector CT was developed, in particular focusing on the 3D spatial relationship between the tricuspid annulus and the right coronary artery. The morphological analysis of the annulus and leaflets confirmed data reported in literature. The qualitative and quantitative analysis of the spatial relationship could standardize the analysis protocol and be pivotal in the procedure planning of the percutaneous device implantation that interact with the tricuspid annulus. \u2022 Third, we simulated the systolic closure of three patient specific mitral valve models, derived from CMR datasets, by means of the mass spring model approach. The comparison of the obtained results vs. finite element analyses (considered as the gold-standard) was performed tuning the parameters of the mass spring model, so to obtain the best trade-off between computational expense and accuracy of the results. A configuration mismatch between the two models lower than two times the in-plane resolution of starting imaging data was yielded using a mass spring model set-up that requires, on average, only ten minutes to simulate the valve closure. \u2022 Finally, in the last chapter, we performed a comprehensive analysis which aimed at exploring the morphological and mechanical changes induced by the myxomatous pathologies in the mitral valve tissue. The analysis of mitral valve thickness confirmed the data and patterns reported in literature, while the mechanical test accurately described the behavior of the pathological tissue. A preliminary implementation of this data into finite element simulations suggested that the use of more reliable patient-specific and pathology-specific characterization of the model could improve the realism and the accuracy of the biomechanical simulations

Recent Applications of Three Dimensional Printing in Cardiovascular Medicine

Three dimensional (3D) printing, which consists in the conversion of digital images into a 3D physical model, is a promising and versatile field that, over the last decade, has experienced a rapid development in medicine. Cardiovascular medicine, in particular, is one of the fastest growing area for medical 3D printing. In this review, we firstly describe the major steps and the most common technologies used in the 3D printing process, then we present current applications of 3D printing with relevance to the cardiovascular field. The technology is more frequently used for the creation of anatomical 3D models useful for teaching, training, and procedural planning of complex surgical cases, as well as for facilitating communication with patients and their families. However, the most attractive and novel application of 3D printing in the last years is bioprinting, which holds the great potential to solve the ever-increasing crisis of organ shortage. In this review, we then present some of the 3D bioprinting strategies used for fabricating fully functional cardiovascular tissues, including myocardium, heart tissue patches, and heart valves. The implications of 3D bioprinting in drug discovery, development, and delivery systems are also briefly discussed, in terms of in vitro cardiovascular drug toxicity. Finally, we describe some applications of 3D printing in the development and testing of cardiovascular medical devices, and the current regulatory frameworks that apply to manufacturing and commercialization of 3D printed products

Imaging-Based, Patient-Specific Three-Dimensional Printing to Plan, Train, and Guide Cardiovascular Interventions: A Systematic Review and Meta-Analysis.

BACKGROUND To tailor cardiovascular interventions, the use of three-dimensional (3D), patient-specific phantoms (3DPSP) encompasses patient education, training, simulation, procedure planning, and outcome-prediction. AIM This systematic review and meta-analysis aims to investigate the current and future perspective of 3D printing for cardiovascular interventions. METHODS We systematically screened articles on Medline and EMBASE reporting the prospective use of 3DPSP in cardiovascular interventions by using combined search terms. Studies that compared intervention time depending on 3DPSP utilisation were included into a meta-analysis. RESULTS We identified 107 studies that prospectively investigated a total of 814 3DPSP in cardiovascular interventions. Most common settings were congenital heart disease (CHD) (38 articles, 6 comparative studies), left atrial appendage (LAA) occlusion (11 articles, 5 comparative, 1 randomised controlled trial [RCT]), and aortic disease (10 articles). All authors described 3DPSP as helpful in assessing complex anatomic conditions, whereas poor tissue mimicry and the non-consideration of physiological properties were cited as limitations. Compared to controls, meta-analysis of six studies showed a significant reduction of intervention time in LAA occlusion (n=3 studies), and surgery due to CHD (n=3) if 3DPSPs were used (Cohen's d=0.54; 95% confidence interval, 0.13 to 0.95; p=0.001), however heterogeneity across studies should be taken into account. CONCLUSIONS 3DPSP are helpful to plan, train, and guide interventions in patients with complex cardiovascular anatomy. Benefits for patients include reduced intervention time with the potential for lower radiation exposure and shorter mechanical ventilation times. More evidence and RCTs including clinical endpoints are needed to warrant adoption of 3DPSP into routine clinical practice

3D printing is a transformative technology in congenital heart disease

Survival in congenital heart disease has steadily improved since 1938, when Dr. Robert Gross successfully ligated for the first time a patent ductus arteriosus in a 7-year-old child. To continue the gains made over the past 80 years, transformative changes with broad impact are needed in management of congenital heart disease. Three-dimensional printing is an emerging technology that is fundamentally affecting patient care, research, trainee education, and interactions among medical teams, patients, and caregivers. This paper first reviews key clinical cases where the technology has affected patient care. It then discusses 3-dimensional printing in trainee education. Thereafter, the role of this technology in communication with multidisciplinary teams, patients, and caregivers is described. Finally, the paper reviews translational technologies on the horizon that promise to take this nascent field even further

A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart

: We propose a mathematical and numerical model for the simulation of the heart function that couples cardiac electrophysiology, active and passive mechanics and hemodynamics, and includes reduced models for cardiac valves and the circulatory system. Our model accounts for the major feedback effects among the different processes that characterize the heart function, including electro-mechanical and mechano-electrical feedback as well as force-strain and force-velocity relationships. Moreover, it provides a three-dimensional representation of both the cardiac muscle and the hemodynamics, coupled in a fluid-structure interaction (FSI) model. By leveraging the multiphysics nature of the problem, we discretize it in time with a segregated electrophysiology-force generation-FSI approach, allowing for efficiency and flexibility in the numerical solution. We employ a monolithic approach for the numerical discretization of the FSI problem. We use finite elements for the spatial discretization of partial differential equations. We carry out a numerical simulation on a realistic human left heart model, obtaining results that are qualitatively and quantitatively in agreement with physiological ranges and medical images

DEVELOPMENT AND IMPLEMENTATION OF NOVEL STRATEGIES TO EXPLOIT 3D ULTRASOUND IMAGING IN CARDIOVASCULAR COMPUTATIONAL BIOMECHANICS

Introduction In the past two decades, major advances have been made in cardiovascular diseases assessment and treatment owing to the advent of sophisticated and more accurate imaging techniques, allowing for better understanding the complexity of 3D anatomical cardiovascular structures1. Volumetric acquisition enables the visualization of cardiac districts from virtually any perspective, better appreciating patient-specific anatomical complexity, as well as an accurate quantitative functional evaluation of chamber volumes and mass avoiding geometric assumptions2. Additionally, this scenario also allowed the evolution from generic to patient-specific 3D cardiac models that, based on in vivo imaging, faithfully represent the anatomy and different cardiac features of a given alive subject, being pivotal either in diagnosis and in planning guidance3. Precise morphological and functional knowledge about either the heart valves\u2019 apparatus and the surrounding structures is crucial when dealing with diagnosis as well as preprocedural planning4. To date, computed tomography (CT) and real-time 3D echocardiography (rt3DE) are typically exploited in this scenario since they allow for encoding comprehensive structural and dynamic information even in the fourth dimension (i.e., time)5,6. However, owing to its cost-effectiveness and very low invasiveness, 3D echocardiography has become the method of choice in most situations for performing the evaluation of cardiac function, developing geometrical models which can provide quantitative anatomical assessment7. Complementing this scenario, computational models have been introduced as numerical engineering tools aiming at adding qualitative and quantitative information on the biomechanical behavior in terms of stress-strain response and other multifactorial parameters8. In particular, over the two last decades, their applications have been ranging from elucidating the heart biomechanics underlying different patho-physiological conditions9 to predicting the effects of either surgical or percutaneous procedures, even comparing several implantation techniques and devices10. At the early stage, most of the studies focused on FE modeling in cardiac environment were based on paradigmatic models11\u201315, being mainly exploited to explore and investigate biomechanical alterations following a specific pathological scenario or again to better understand whether a surgical treatment is better or worse than another one. Differently, nowadays the current generation of computational models heavily exploits the detailed anatomical information yielded by medical imaging to provide patient-specific analyses, paving the way toward the development of virtual surgical-planning tools16\u201319. In this direction, cardiac magnetic resonance (CMR) and CT/micro-CT are the mostly accomplished imaging modality, since they can provide well-defined images thanks to their spatial and temporal resolutions20\u201325. Nonetheless, they cannot be applied routinely in clinical practice, as it can be differently done with rt3DE, progressively became the modality of choice26 since it has no harmful effects on the patient and no radiopaque contrast agent is needed. Despite these advantages, 3D volumetric ultrasound imaging shows intrinsic limitations beyond its limited resolution: i) the deficiency of morphological detail owing to either not so easy achievable detection (e.g., tricuspid valve) or not proper acoustic window, ii) the challenge of tailoring computational models to the patient-specific scenario mimicking the morphology as well as the functionality of the investigated cardiac district (e.g., tethering effect exerted by chordal apparatus in mitral valve insufficiency associated to left ventricular dilation), and iii) the needing to systematically analyse devices performances when dealing with real-life cases where ultrasound imaging is the only performable technique but lacking of standardized acquisition protocol. Main findings In the just described scenario, the main aim of this work was focused on the implementation, development and testing of numerical strategies in order to overcome issues when dealing with 3D ultrasound imaging exploitation towards predictive patient-specific modelling approaches focused on both morphological and biomechanical analyses. Specifically, the first specific objective was the development of a novel approach integrating in vitro imaging and finite element (FE) modeling to evaluate tricuspid valve (TV) biomechanics, facing with the lack of information on anatomical features owing to the clinically evident demanding detection of this anatomical district through in vivo imaging. \u2022 An innovative and semi-automated framework was implemented to generate 3D model of TV, to quantitively describe its 3D morphology and to assess its biomechanical behaviour. At this aim, an image-based in vitro experimental approach was integrated with numerical models based on FE strategy. Experimental measurements directly performed on the benchmark (mock circulation loop) were compared with geometrical features computed on the 3D reconstructed model, pinpointing a global good consistency. Furthermore, obtained realistic reconstructions were used as the input of the FE models, even accounting for proper description of TV leaflets\u2019 anisotropic mechanical response. As done experimentally, simulations reproduced both \u201cincompetent\u201d (FTR) and \u201ccompetent-induced\u201d (PMA), proving the efficiency of such a treatment and suggesting translational potential to the clinic. The second specific aim was the implementation of a computational framework able to reproduce a functionally equivalent model of the mitral valve (MV) sub-valvular apparatus through chordae tendineae topology optimization, aiming at chordae rest length arrangement to be able to include their pre-stress state associated to specific ventricular conformation. \u2022 We sought to establish a framework to build geometrically tractable, functionally equivalent models of the MV chordae tendineae, addressing one of the main topics of the computational scientific literature towards the development of faithful patient-specific models from in vivo imaging. Exploiting the mass spring model (MSM) approach, an iterative tool was proposed aiming to the topology optimization of a paradigmatic chordal apparatus of MVs affected by functional regurgitation, in order to be able to equivalently account for tethering effect exerted by the chordae themselves. The results have shown that the algorithm actually lowered the error between the simulated valve and ground truth data, although the intensity of this improvement is strongly valve-dependent.Finally, the last specific aim was the creation of a numerical strategy able to allow for patient-specific geometrical reconstruction both pre- and post- LVAD implantation, in a specific high-risk clinical scenario being rt3DE the only available imaging technique to be used but without any acquisition protocol. \u2022 We proposed a numerical approach which allowed for a systematic and selective analysis of the mechanism associated to intraventricular thrombus formation and thrombogenic complications in a LVAD-treated dilated left ventricle (LV). Ad-hoc geometry reconstruction workflow was implemented to overcome limitations associated to imaging acquisition in this specific scenario, thus being able to generate computational model of the LV assisted with LVAD. In details, results suggested that blood stasis is influenced either by LVAD flow rate and, to a greater extent, by LV residual contractility, being the positioning of the inflow cannula insertion mandatory to be considered when dealing with LVAD thrombogenic potential assessment

The mitral valve computational anatomy and geometry analysis

We present a novel methodology to characterize and quantify the Mitral Valve (MV) geometry and physical attributes in a multi-resolution framework. A multi-scale decomposition was implemented to model the MV geometry by using superquadric shape primitives and spectral reconstruction of the finer-scale geometric details. Superquadrics provide a basis to normalize the size and approximate a basic model of the MV geometry. The point-wise difference between the original geometry and the superquadric model denotes the finer-scale geometric details, which can be modeled as a scalar attribute for the MV model development. The additive decomposition of the basic MV geometry from geometric details (attributes) allows recovering the actual geometry by superposition of the superquadric approximation and the finer-details model. We implemented a lasso optimization algorithm to perform spectral analysis and develop the Fourier reconstruction of the geometric details. The spectral modeling enabled us to resample the geometric details or use spectral filters in order to adjust the spatial resolution in the model reconstruction. It also provides the basis to control the level of detail in the final model reconstruction by applying low-pass filters in the frequency domain. The higher-order attributes such as internal fiber architecture can be integrated with the geometric models using the same framework. We applied our pipeline to create models of three ovine MVs based on computed-tomography 3D images with micrometer resolution. We were able to quantify the MV leaflet geometry, reconstruct models with custom level of geometric details, and develop medial representation of the MV leaflet structure. The results show that our methodology for geometry analysis provides a basis for assessing patient-specific geometries and facilitates developing population-averaged models. Ultimately, this approach allows building personalized image-based computational models for medical device design and surgical treatment simulations.Mechanical Engineerin