Aortic dissection: simulation tools for disease management and understanding

Aortic dissection is a severe cardiovascular pathology in which a tear in the intimal layer of the aortic wall allows blood to flow between the vessel wall layers, forming a 'false lumen'. In type-B aortic dissections, those involving only the descending aorta, the decision to medically manage or surgically intervene is not clear and is highly dependent on the patient. In addition to clinical imaging data, clinicians would benefit greatly from additional physiological data to inform their decision-making process. Computational fluid dynamics methods show promise for providing data on haemodynamic parameters in cardiovascular diseases, which cannot otherwise be predicted or safely measured. The assumptions made in the development of such models have a considerable impact on the accuracy of the results, and thus require careful investigation. Application of appropriate boundary conditions is a challenging but critical component of such models. In the present study, imaging data and invasive pressure measurements from a patient with a type-B aortic dissection were used to assist numerical modelling of the haemodynamics in a dissected aorta. A technique for tuning parameters for coupled Windkessel models was developed and evaluated. Two virtual treatments were modelled and analysed using the developed dynamic boundary conditions. Finally, the influence of wall motion was considered, of which the intimal flap that separates the false lumen from the true lumen, is of particular interest. The present results indicate that dynamic boundary conditions are necessary in order to achieve physiologically meaningful flows and pressures at the boundaries, and hence within the dissected aorta. Additionally, wall motion is of particular importance in the closed regions of the false lumen, wherein rigid wall simulations fail to capture the motion of the fluid due to the elasticity of the vessel wall and intimal flap

Heart Valve Mathematical Models

Nearly 100,000 heart valve replacements or repairs are performed in the US every year. Mathematical models of heart valves are used to improve artificial valve design and to guide surgeons performing valve-repairing surgeries. Models can be used to define the geometry of a valve, predict blood flow dynamics, or demonstrate operating mechanisms of the valve. In this thesis we reviewed features that are typically considered when developing a model of a heart valve. The main modeling methods include representing a heart valve using lumped parameters, finite elements, or isogeometric elements. Examples of a lumped-parameter model and isogeometric analysis are explored. First, we developed a simulation for the lumped-parameter model of Virag and Lulić, and we demonstrated its ability to capture the dynamical behavior of blood pressures, volumes, and flows in the aortic valve region. A Newton-Krylov method was used to estimate periodic solution trajectories, which provide a basis for examining the response to perturbations about initial conditions. Next, an isogeometric model of a heart valve was constructed based on NURBS geometry. The mechanical stiffness of the valve was computed. We discussed how the isogeometric representation could be used in a more complex fluid-structure interaction model to measure surface shear and estimate fatigue failure

Equivalence testing for identity authentication using pulse waves from photoplethysmograph

Doctor of PhilosophyDepartment of StatisticsSuzanne DubnickaChristopher VahlPhotoplethysmograph sensors use a light-based technology to sense the rate of blood flow as controlled by the heart’s pumping action. This allows for a graphical display of a patient’s pulse wave form and the description of its key features. A person’s pulse wave has been proposed as a tool in a wide variety of applications. For example, it could be used to diagnose the cause of coldness felt in the extremities or to measure stress levels while performing certain tasks. It could also be applied to quantify the risk of heart disease in the general population. In the present work, we explore its use for identity authentication. First, we visualize the pulse waves from individual patients using functional boxplots which assess the overall behavior and identify unusual observations. Functional boxplots are also shown to be helpful in preprocessing the data by shifting individual pulse waves to a proper starting point. We then employ functional analysis of variance (FANOVA) and permutation tests to demonstrate that the identities of a group of subjects could be differentiated and compared by their pulse wave forms. One of the primary tasks of the project is to confirm the identity of a person, i.e., we must decide if a given person is whom they claim to be. We used an equivalence test to determine whether the pulse wave of the person under verification and the actual person were close enough to be considered equivalent. A nonparametric bootstrap functional equivalence test was applied to evaluate equivalence by constructing point-wise confidence intervals for the metric of identity assurance. We also proposed new testing procedures, including the way of building the equivalence hypothesis and test statistics, determination of evaluation range and equivalence bands, to authenticate the identity

Study of a medical device to treat aortic dissection with Finite Element Analysis

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Carmona Flores, Manuel, Soudah Prieto, EduardoThe aortic dissection is a cardiovascular disease that results from the rupture of the inner layer of the aorta. Type B aortic dissections commonly become a chronic disease with a high long-term morbidity and mortality rates. Current treatments include open surgery repair and thoracic endovascular aortic repair (TEVAR). However, new non-invasive treatments are being developed that favour the own regeneration of the tissue, avoiding the permanent presence of a foreign device in the body. This project focuses on the understanding of a new treatment with a medical device, an aortic patch, by in silico testing. The goal is to determine the performance of the patch in a simulated aortic dissection and then compare it with the current treatment with the stent graft (TEVAR), to determine if it would avoid the hypertension that can be caused by the stent. To do the first part, it was created a model of the aortic dissection, but due to complications with the simulation, this part of the project couldn’t be finished, and the performance of the patch in the aortic dissection couldn’t be determined. To do the second part three models were created: healthy aorta, aortic dissection with stent graft and aortic dissection with patch. A transient simulation was run for the three models and the pressure waveform was analyzed. The results show that the pressure in the stent graft model is higher, and the patch has a similar response to the healthy aorta. However, all the models presented hypertension (including the healthy aorta) and the differences between the models are too small to be concluding, so it cannot be assured that the patch is a better option than the stent graft to avoid causing hypertension in the aortic dissection treatment

Fluid-structure interaction in a fully coupled three-dimensional mitral-atrium-pulmonary model

This paper aims to investigate detailed mechanical interactions between the pulmonary haemodynamics and left heart function in pathophysiological situations (e.g. atrial fibrillation and acute mitral regurgitation). This is achieved by developing a complex computational framework for a coupled pulmonary circulation, left atrium and mitral valve model. The left atrium and mitral valve are modelled with physiologically realistic three-dimensional geometries, fibre-reinforced hyperelastic materials and fluid–structure interaction, and the pulmonary vessels are modelled as one-dimensional network ended with structured trees, with specified vessel geometries and wall material properties. This new coupled model reveals some interesting results which could be of diagnostic values. For example, the wave propagation through the pulmonary vasculature can lead to different arrival times for the second systolic flow wave (S2 wave) among the pulmonary veins, forming vortex rings inside the left atrium. In the case of acute mitral regurgitation, the left atrium experiences an increased energy dissipation and pressure elevation. The pulmonary veins can experience increased wave intensities, reversal flow during systole and increased early-diastolic flow wave (D wave), which in turn causes an additional flow wave across the mitral valve (L wave), as well as a reversal flow at the left atrial appendage orifice. In the case of atrial fibrillation, we show that the loss of active contraction is associated with a slower flow inside the left atrial appendage and disappearances of the late-diastole atrial reversal wave (AR wave) and the first systolic wave (S1 wave) in pulmonary veins. The haemodynamic changes along the pulmonary vessel trees on different scales from microscopic vessels to the main pulmonary artery can all be captured in this model. The work promises a potential in quantifying disease progression and medical treatments of various pulmonary diseases such as the pulmonary hypertension due to a left heart dysfunction

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

Methods and Algorithms for Cardiovascular Hemodynamics with Applications to Noninvasive Monitoring of Proximal Blood Pressure and Cardiac Output Using Pulse Transit Time

Advanced health monitoring and diagnostics technology are essential to reduce the unrivaled number of human fatalities due to cardiovascular diseases (CVDs). Traditionally, gold standard CVD diagnosis involves direct measurements of the aortic blood pressure (central BP) and flow by cardiac catheterization, which can lead to certain complications. Understanding the inner-workings of the cardiovascular system through patient-specific cardiovascular modeling can provide new means to CVD diagnosis and relating treatment. BP and flow waves propagate back and forth from heart to the peripheral sites, while carrying information about the properties of the arterial network. Their speed of propagation, magnitude and shape are directly related to the properties of blood and arterial vasculature. Obtaining functional and anatomical information about the arteries through clinical measurements and medical imaging, the digital twin of the arterial network of interest can be generated. The latter enables prediction of BP and flow waveforms along this network. Point of care devices (POCDs) can now conduct in-home measurements of cardiovascular signals, such as electrocardiogram (ECG), photoplethysmogram (PPG), ballistocardiogram (BCG) and even direct measurements of the pulse transit time (PTT). This vital information provides new opportunities for designing accurate patient-specific computational models eliminating, in many cases, the need for invasive measurements. One of the main efforts in this area is the development of noninvasive cuffless BP measurement using patient’s PTT. Commonly, BP prediction is carried out with regression models assuming direct or indirect relationships between BP and PTT. However, accounting for the nonlinear FSI mechanics of the arteries and the cardiac output is indispensable. In this work, a monotonicity-preserving quasi-1D FSI modeling platform is developed, capable of capturing the hyper-viscoelastic vessel wall deformation and nonlinear blood flow dynamics in arbitrary arterial networks. Special attention has been dedicated to the correct modeling of discontinuities, such as mechanical properties mismatch associated with the stent insertion, and the intertwining dynamics of multiscale 3D and 1D models when simulating the arterial network with an aneurysm. The developed platform, titled Cardiovascular Flow ANalysis (CardioFAN), is validated against well-known numerical, in vitro and in vivo arterial network measurements showing average prediction errors of 5.2%, 2.8% and 1.6% for blood flow, lumen cross-sectional area, and BP, respectively. CardioFAN evaluates the local PTT, which enables patient-specific calibration and its application to input signal reconstruction. The calibration is performed based on BP, stroke volume and PTT measured by POCDs. The calibrated model is then used in conjunction with noninvasively measured peripheral BP and PTT to inversely restore the cardiac output, proximal BP and aortic deformation in human subjects. The reconstructed results show average RMSEs of 1.4% for systolic and 4.6% for diastolic BPs, as well as 8.4% for cardiac output. This work is the first successful attempt in implementation of deterministic cardiovascular models as add-ons to wearable and smart POCD results, enabling continuous noninvasive monitoring of cardiovascular health to facilitate CVD diagnosis

Digital twin of analogue man:development of a computational modelling platform to assess heart-vessel interaction in humans

The concept of using ‘twins’ is not new. For many years, plastic replicas of skeletons (i.e. ‘physical twins’) have been used in the classroom as well as in the general practitioner’s office to explain aspects of the human skeletal anatomy. Physical twins were also used during NASA’s Project Apollo in which two identical spacecraft were built, one to remain on the basis, which allowed engineers to recreate the conditions of the spacecraft during missions. Digital twin technology is a novel concept originating from manufacturing industry. A digital twin refers to a virtual or computational model containing a comprehensive physical and functional description of a component, product or system. In this thesis, we applied the digital twin concept to cardiovascular research by developing and evaluating a computational modelling platform to assess heart-vessel interaction. The developed models were employed in two use-cases concerning patient-specific modelling: 1) non-invasive computational methods to allow screening for cardiac abnormalities and 2) non-invasive identification of arterial wall mechanical properties to assess the effect of (novel) vascular drugs on cardiovascular system dynamics

Computational analysis of blood flow and stress patterns in the aorta of patients with Marfan syndrome

Personalised external aortic root support (PEARS) was designed to prevent progressive aortic dilatation, and the associated risk of aortic dissection, in patients with Marfan syndrome by providing an additional support to the aorta. The objective of this thesis was to understand the biomechanical implications of PEARS surgery as well as to investigate the altered haemodynamics associated with the disease and its treatment. Finite element (FE) models were developed using patient-specific aortic geometries reconstructed from pre and post-PEARS magnetic resonance (MR) images of three Marfan patients. The wall and PEARS materials were assumed to be isotropic, incompressible and linearly elastic. A static load on the inner wall corresponding to the patients’ pulse pressure was applied with a zero-displacement constraint at all boundaries. Results showed that peak aortic stresses and displacements before PEARS were located at the sinuses of Valsalva but following PEARS surgery, they were shifted to the aortic arch, at the intersection between the supported and unsupported aorta. The zero-displacement constraint at the aortic root was subsequently removed and replaced with downward motion measured from in vivo images. This revealed significant increases in the longitudinal wall stress, especially in the pre-PEARS models. Computational fluid dynamics (CFD) models were developed to evaluate flow characteristics. The correlation-based transitional Shear Stress Transport (SST-Tran) model was adopted to simulate potential transitional and turbulence flow during part of the cardiac cycle and flow waveforms derived from phase-contrast MR images were imposed at the inlets. Qualitative patterns of the haemodynamics were similar pre- and post-PEARS with variations in mean helicity flow index (HFI) of -10%, 35% and 20% in the post-PEARS aortas of the three patients. A fluid-structure interaction (FSI) model was developed for one patient, pre- and post-PEARS in order to examine the effect of wall compliance on aortic flow as well as the effect of pulsatile flow on wall stress. This model excluded the sinuses and was based on the laminar flow assumption. The results were similar to those obtained using the rigid wall and static structural models, with minor quantitative differences. Considering the higher computational cost of FSI simulations and the relatively small differences observed in peak wall stress, it is reasonable to suggest that static structural models would be sufficient for wall stress prediction. Additionally, aortic root motion had a more profound effect on wall stress than wall compliance. Further studies are required to assess the statistical significance of the findings outlined in this thesis. Recommendations for future work were also highlighted, with emphasis on model assumptions including material properties, residual stress and boundary conditions.Open Acces