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 - Swanson, Liam (Department of Mechanical Engineering, 2021)
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.