The Development of a Patient-Specific, Open Source Computational Fluid Dynamics Tool to Comprehensively and Innovatively Study Coarctation of the Aorta in a Limited Resource Clinical Context

Congenital heart disease (CHD) has a global prevalence of 8 per 1000 births [1] and coarctation of the aorta (CoA) is one of the most common defects with a prevalence of 7% of all cases. The occurrence of CHD in Africa is estimated to be significantly lower, which is attributed to a lack of data [2]. This emphasises the restricted human resources, as well as diagnostic and intervention capacity of specialists in Africa which leads to delayed treatment, presentation with established severity and, consequently, a worse prognosis. Computational Fluid Dynamics (CFD) is seen as the tool that will lead to a better understanding of the haemodynamic effects caused by the malformations related to CoA and provide insights into post-repair morbidity. In addition, the development of a computational tool is envisaged to improve the clinical capacity for diagnosis as well as provide a tool to conduct in silico repair planning. In a low and lower-middle income country healthcare facility, the supplementary data that CFD can provide can add diagnostic value, plan interventions to be more effective and efficient, as well as provide data that may improve postrepair patient management. The aim of this project is to develop a patient-specific, open source, computational fluid dynamics toolchain that is able to study the haemodynamics relating to CoA. In order to do so, a protocol for the collection of doppler echocardiography (echo) and CTA data is proposed. The method for processing the echo data and manually segmenting the CTA data is presented and evaluated. The open source, OpenFOAM code is used to simulate a patient-specific CoA case as well as two in silico designs of coarctation repairs based on expanding the coarctation from the original dataset. The CFD toolchain was developed such that patient data collected from the hospital could be processed to present key haemodynamic metrics such as velocities in the field at the coarctation zone, the pressure gradient across the coarctation and volumetric flow rates through each supra-aortic branch. These results are obtained for each case's geometry, and the trends and impacts that increasing the coarctation ratio has on each of the haemodynamic metrics is presented. The results show that the coarctation pressure gradient and maximum coarctation velocity decrease while perfusion of the lower limbs recovers with expanding coarctation ratio. Following an analysis of the results, it is evident that the pipeline is capable of running patient-specific CFD simulations and can present clinically relevant results. It is noted that this work is a proof of concept and so several steps are discussed that will improve the pipeline

Analysis of Blood Flow in Patient-specific Models of Type B Aortic Dissection

Aortic dissection is the most common acute catastrophic event affecting the aorta. The majority of patients presenting with an uncomplicated type B dissection are treated medically, but 25% of these patients develop subsequent dilatation and aortic aneurysm formation. The reasons behind the long‐term outcomes of type B aortic dissection are poorly understood. As haemodynamic factors have been involved in the development and progression of a variety of cardiovascular diseases, the flow phenomena and environment in patient‐specific models of type B aortic dissection have been studied in this thesis by applying computational fluid dynamics (CFD) to in vivo data. The present study aims to gain more detailed knowledge of the links between morphology, flow characteristics and clinical outcomes in type B dissection patients. The thesis includes two parts of patient‐specific study: a multiple case cross‐sectional study and a single case longitudinal study. The multiple cases study involved a group of ten patients with classic type B aortic dissection with a focus on examining the flow characteristics as well as the role of morphological factors in determining the flow patterns and haemodynamic parameters. The single case study was based on a series of follow‐up scans of a patient who has a stable dissection, with an aim to identify the specified haemodynamic factors that are associated with the progression of aortic dissection. Both studies were carried out based on computed tomography images acquired from the patients. 4D Phase‐contrast magnetic resonance imaging was performed on a typical type B aortic dissection patient to provide detailed flow data for validation purpose. This was achieved by qualitative and quantitative comparisons of velocity‐encoded images with simulation results of the CFD model. The analysis of simulation results, including velocity, wall shear stress and turbulence intensity profiles, demonstrates certain correlations between the morphological features and haemodynamic factors, and also their effects on long‐term outcomes of type B aortic dissections. The simulation results were in good agreement with in vivo MR flow data in the patient‐specific validation case, giving credence to the application of the computational model to the study of flow conditions in aortic dissection. This study made an important contribution by identifying the role of certain morphological and haemodynamic factors in the development of type B aortic dissection, which may help provide a better guideline to assist surgeons in choosing optimal treatment protocol for individual patient

Investigation of Flow Disturbances and Multi-Directional Wall Shear Stress in the Stenosed Carotid Artery Bifurcation Using Particle Image Velocimetry

Hemodynamics and shear forces are associated with pathological changes in the vascular wall and its function, resulting in the focal development of atherosclerosis. Flow complexities that develop in the presence of established plaques create environments favourable to thrombosis formation and potentially plaque rupture leading to stroke. The carotid artery bifurcation is a common site of atherosclerosis development. Recently, the multi-directional nature of shear stress acting on the endothelial layer has been highlighted as a risk factor for atherogenesis, emphasizing the need for accurate measurements of shear stress magnitude as well direction. In the absence of comprehensive patient specific datasets numerical simulations of hemodynamics are limited by modeling assumptions. The objective of this thesis was to investigate the relative contributions of various factors - including geometry, rheology, pulsatility, and compliance – towards the development of disturbed flow and multi-directional wall shear stress (WSS) parameters related to the development of atherosclerosis An experimental stereoscopic particle image velocimetry (PIV) system was used to measure instantaneous full-field velocity in idealized asymmetrically stenosed carotid artery bifurcation models, enabling the extraction of bulk flow features and turbulence intensity (TI). The velocity data was combined with wall location information segmented from micro computed tomography (CT) to obtain phase-averaged maps of WSS magnitude and direction. A comparison between Newtonian and non-Newtonian blood-analogue fluids demonstrated that the conventional Newtonian viscosity assumption underestimates WSS magnitude while overestimating TI. Studies incorporating varying waveform pulsatility demonstrated that the levels of TI and oscillatory shear index (OSI) depend on the waveform amplitude in addition to the degree of vessel constriction. Local compliance resulted in a dampening of disturbed flow due to volumetric capacity of the upstream vessel, however wall tracking had a negligible effect on WSS prediction. While the degree of stenosis severity was found to have a dominant effect on local hemodynamics, comparable relative differences in metrics of flow and WSS disturbances were found due to viscosity model, waveform pulsatility and local vessel compliance

Computational analysis of hemodynamics and thrombosis in aortic dissection for clinical applications

Type B aortic dissection is a potentially devastating disease of the aorta initiated by a tear in the inner lining of the aortic wall. Blood flow through this tear causes the aortic wall layers to separate and a secondary channel of blood flow know as the ‘false lumen’ forms. Complete thrombosis (clotting) of the false lumen, is the desired outcome of either medical or endovascular (TEVAR) treatment. However, it is currently unclear at the time of diagnosis how a specific dissection will progress with either treatment option. Anatomical studies have identified a range of morphological factors that may be influential in disease progression, though no single parameter has been found to be independently predictive of patient prognosis. Computational fluid dynamics (CFD) studies have aimed to assess the hemodynamic state of dissection, however, studies have generally been limited due to simplified geometries and unphysiological boundary conditions due to the lack of patient-specific in vivo flow data. Thanks to recent developments in imaging technologies, in vivo flow data can now be acquired through 4D-flow magnetic resonance imaging (MRI), though detailed evaluation of dissection flow fields is limited due to poor image quality. CFD has the potential to be a useful tool in clinical practice for predicting disease progression, as long as the results are physiological to specific patients. 4D-flow MRI data could provide the patient-specific details required to build detailed and accurate CFD models. The primary objective of this thesis is to develop clinically applicable computational models to accurately simulate hemodynamics and thrombus formation in type B dissection patients. A 4D-flow MRI based CFD workflow was developed and key model inputs were assessed in detail. The use of a patient-specific 3D inlet velocity profile was compared to commonly used idealised profiles, with the 3D profile producing results which agreed best with in vivo data. The importance of major and minor aortic branches in geometry segmentation was assessed, and results showed that exclusion of such branches can significantly impact predicted hemodynamics and thrombus formation. The finalised CFD workflow was evaluated against in vivo data and was shown to be able to faithfully reproduce dissection hemodynamics in a study of 5 patients. A hemodynamics-based thrombus predicting model was evaluated and simplified in order to improve computational efficiency for clinical application. Finally, the CFD workflow and thrombus model were utilised in studies on the influence of re-entry tears both pre- and post-TEVAR.Open Acces

Efficient cardio-vascular 4D-Flow MRI enabled CFD to improve in-silico predictions of post-surgical haemodynamics in individual patients

This thesis focuses on creating a workflow that combines four dimensional flow magnetic resonance imaging with computational fluid dynamics techniques, and identifying the main difficulties that are associated with patient-specific modelling. With further development, the proposed work- flow will allow post-surgical haemodynamics to be predicted prior to surgical intervention taking place, ensuring the best possible outcome is achieved for the individual patient. The use of patient-specific computational fluid dynamic modelling in diagnostics and risk stratification, treatment planning, and surgical intervention is quickly becoming an invaluable tool and has proven key in multiple medical advances and breakthroughs. However, existing methods to combine medical imaging and computational fluid dynamics techniques often require invasive procedures to collect appropriate patient-specific data, require expensive software licenses, or have significant limitations within the methodologies, such as inlet conditions or spatial resolutions. The research within this thesis provides a workflow to combine four dimensional flow magnetic resonance imaging and computational fluid dynamics, using open source software when possible, and a non-invasive and non-ionising imaging technique. The major challenges of patient-specific modelling are investigated. By increasing the complexity of the workflow incrementally, the impacts of physiologically accurate inlet boundary conditions are assessed, as is the human error that is introduced into patient-specific modelling through the geometry reconstruction process. The workflow created is tested on a wide age range of patients and bicuspid aortic valve phenotypes. To validate the workflow created, the methods used were applied to an anatomical flow phantom, therefore the in-vivo challenges of the thoracic aorta moving radially and vertically, and the systemic circulatory system distal to the outlets were removed. This research has shown that the workflow proposed produces good agreement with four dimensional flow magnetic resonance imaging data, notably in the ascending aorta during the systolic phase of the cardiac cycle. A significant challenge of patient-specific modelling that is often acknowledged yet not fully quantified is the spatial resolution of the four dimensional flow magnetic resonance imaging. Research therefore focused on determining how the spatial resolution at which the four dimensional flow magnetic resonance imaging data is acquired at impacts the subsequent patient-specific computational fluid dynamics simulations. The results presented show that coarse spatial resolutions have a significant impact on the results of numerical simulations. From the results presented, a recommendation of a minimum spatial resolution that should be used when conducting patient-specific simulations was made to avoid errors being introduced into the numerical simulations

A Systematic Review and Discussion of the Clinical Potential

Funding Information: Funding by Portuguese Foundation for Science and Technology (FCT-MCTES) under the following projects: PTDC/EMD-EMD/1230/2021—Fluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice ; UNIDEMI UIDB/00667/2020; A. Mourato PhD grant UI/BD/151212/2021; R. Valente PhD grant 2022.12223.BD. Publisher Copyright: © 2022 by the authors.Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.publishersversionpublishe