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

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart

Modelling and application of mitral valve dynamics for reproducing the flow in the left ventricle of the human heart

The fluid dynamics in the left ventricle of the human heart is considered an important player for the prediction of long term cardiovascular outcome. To this end, numerical simulations represent an important tool for integrating the existing medical imaging technology and uncover physical flow phenomena. This study presents a computational method for the fluid dynamics inside the left ventricle designed to be efficiently integrated in clinical scenarios. It includes an original model of the mitral valve dynamics, which describes an asymptotic behavior for tissues with no elastic stiffness other than the constrain of the geometry obtained from medical imaging; in particular, the model provides an asymptotic description without requiring details of tissue properties that may not be measurable in vivo. The advantages of this model with respect to a valveless orifice and its limitations with respect to a complete tissue modeling are verified. Its performances are then analyzed in details to ensure a correct interpretation of results. It represents a potential option when information about tissue mechanical properties is insufficient for the implementations of a full fluid-structure interaction approach. Geometries of left ventricle (LV) and mitral valve (MV) are extracted from 4D-transesophageal echocardiography. MV geometries are extracted in open and closed configurations and the intraventricular fluid dynamics is reproduced by a dedicated approach to direct numerical simulation (DNS) that includes flow-tissue interaction for the MV leaflet (Collia et al. 2019). This approach is applied to normal and pathological ventricles to investigate the dynamics of the MV during the cardiac cycle: how it interacts with the ventricular flow and how it affects clinical measurements. The dynamics of mitral opening at the onset of diastole, as well as the closure at the transition between diastole and systole, is governed by the high pressure gradients associated with the bulk cardiac flow. On the opposite, during the flow diastasis in the middle of the diastolic filling, valvular motion is primarily influenced by the intraventricular circulation that gives an increased tendency to close in enlarged ventricles. This observation provides a physical interpretation to echocardiographic measurements commonly employed in the clinical diagnostic process. Results demonstrated the properties of false regurgitation, blood that did not cross the open MV orifice and returns into the atrium during the backward motion of the MV leaflets, whose entity should be accounted when evaluating small regurgitation (Collia et al. 2019). The regurgitating volume is found to be proportional to the effective orifice area, with the limited dependence of the LV geometry and type of prolapse. These affect the percentage of old blood returning to the atrium which may be associated with thrombogenic risk. This non-invasive method is useful for the assessment of blood flow, to improve early detection of cardiac dysfunctions and for provide a concrete helpful in clinical routines

A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography

Three-dimensional transesophageal echocardiography (3DTEE) is the recommended imaging technique for the assessment of mitral valve (MV) morphology and lesions in case of mitral regurgitation (MR) requiring surgical or transcatheter repair. Such assessment is key to thorough intervention planning and to intraprocedural guidance. However, it requires segmentation from 3DTEE images, which is timeconsuming, operator-dependent, and often merely qualitative. In the present work, a novel workflow to quantify the patient-specific MV geometry from 3DTEE is proposed. The developed approach relies on a 3D multi-decoder residual convolutional neural network (CNN) with a U-Net architecture for multi-class segmentation of MV annulus and leaflets. The CNN was trained and tested on a dataset comprising 55 3DTEE examinations of MR-affected patients. After training, the CNN is embedded into a fully automatic, and hence fully repeatable, pipeline that refines the predicted segmentation, detects MV anatomical landmarks and quantifies MV morphology. The trained 3D CNN achieves an average Dice score of 0.82 +/- 0.06, mean surface distance of 0.43 +/- 0.14 mm and 95% Hausdorff Distance (HD) of 3.57 +/- 1.56 mm before segmentation refinement, outperforming a state-of-the-art baseline residual U-Net architecture, and provides an unprecedented multi-class segmentation of the annulus, anterior and posterior leaflet. The automatic 3D linear morphological measurements of the annulus and leaflets, specifically diameters and lengths, exhibit differences of less than 1.45 mm when compared to ground truth values. These measurements also demonstrate strong overall agreement with analyses conducted by semi-automated commercial software. The whole process requires minimal user interaction and requires approximately 15 seconds

Artificial intelligence and automation in valvular heart diseases

Artificial intelligence (AI) is gradually changing every aspect of social life, and healthcare is no exception. The clinical procedures that were supposed to, and could previously only be handled by human experts can now be carried out by machines in a more accurate and efficient way. The coming era of big data and the advent of supercomputers provides great opportunities to the development of AI technology for the enhancement of diagnosis and clinical decision-making. This review provides an introduction to AI and highlights its applications in the clinical flow of diagnosing and treating valvular heart diseases (VHDs). More specifically, this review first introduces some key concepts and subareas in AI. Secondly, it discusses the application of AI in heart sound auscultation and medical image analysis for assistance in diagnosing VHDs. Thirdly, it introduces using AI algorithms to identify risk factors and predict mortality of cardiac surgery. This review also describes the state-of-the-art autonomous surgical robots and their roles in cardiac surgery and intervention

Analysis of a coupled fluid-structure interaction model of the left atrium and mitral valve

We present a coupled left atrium ‐ mitral valve model based on computed tomography scans with fibre‐reinforced hyperelastic materials. Fluid‐structure interaction is realised by using an immersed boundary‐finite element framework. Effects of pathological conditions, e.g. mitral valve regurgitation and atrial fibrillation, and geometric and structural variations, namely uniform vs non‐uniform atrial wall thickness and rule‐based vs atlas‐based fibre architectures, on the system are investigated. We show that in the case of atrial fibrillation, pulmonary venous flow reversal at late diastole disappears and the filling waves at the left atrial appendage orifice during systole have reduced magnitude. In the case of mitral regurgitation, a higher atrial pressure and disturbed flows are seen, especially during systole, when a large regurgitant jet can be found with the suppressed pulmonary venous flow. We also show that both the rule‐based and atlas‐based fibre defining methods lead to similar flow fields and atrial wall deformations. However, the changes in wall thickness from non‐uniform to uniform tend to underestimate the atrial deformation. Using a uniform but thickened wall also lowers the overall strain level. The flow velocity within the left atrial appendage, which is important in terms of appendage thrombosis, increases with the thickness of the left atrial wall. Energy analysis shows that the kinetic and dissipation energies of the flow within the left atrium are altered differently by atrial fibrillation and mitral valve regurgitation, providing a useful indication of the atrial performance in pathological situations

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

High Frame Rate Ultrasound Velocimetry of Fast Blood Flow Dynamics

In this thesis we develop and validate high frame rate ultrasound sequences for use with echo-particle image velocimetry (in 2D and 3D), with the aim of measuring the high velocity blood flow patterns in the left ventricle and abdominal aorta