Development of a novel computational framework to support therapeutic-planning in selecting the optimal thromboembolic prevention treatment for AF

1) Brief description of the context of the research including potential impact

Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is characterised by rapid and disorganised heartbeats. It affects 2-3% of the population, with prevalence rising to 9% for individuals > 65 years. It is the leading cause of thromboembolic events (i.e. stroke and vascular dementia), and its projected incidence is more than double by 2035.
It is estimated that > 90% of thrombi responsible for thromboembolic events under AF originate in the left atrial appendage (LAA), a complex-shaped protrusion of 2-4 cm, which departs from the left atrium (LA).
The most common therapy to prevent thrombi in AF patients is oral anticoagulation; this is however contraindicated in up to 44% of AF patients, due to associated lifetime haemorrhagic risk, cost and several food/drug interactions needing frequent laboratory monitoring. Alternatively, surgical LAA exclusion can be performed applying an external suture ligation - e.g. LARIAT snare device (SentreHEART) - or a self-closing clamping device - e.g. AtriClip LAA Exclusion System (AtriCure). Percutaneous LAA occlusion devices overcome the drawbacks of invasive surgery, based on self-expanding nitinol frames supporting polyester occlusion patches. The two most common solutions are the Watchman FLX (Boston Scientific) and the Amplatzer Amulet (Abbott). However, these can develop peri-device leaks, requiring long-term anticoagulants treatment, thus inherently defeating the main procedure purpose.
As all these options present major drawbacks, it is crucial to develop a novel approach to identify the patient groups for which the risk of thromboembolic events justifies a specific therapeutic approach, and the safest and most effective therapy for each subject.

2) Aims and Objectives

The overall project goal is developing a novel computational framework to support clinical decision-making in selecting the optimal thromboembolic prevention therapy for each AF patient, identifying fluid-dynamic parameters that are impossible to measure in-vivo.

1. Analyse and segment in-vivo medical images of AF patients to obtain LAA's 3D morphological/dynamic characteristics.
2. Develop Fluids Structure Interaction (FSI) computational models for the AF population, including LAA/LA anatomical features, investigating the relations between different LAA morphologies and hemodynamics, as well as the capturing of the ones not available from clinical diagnostics.
3. Develop models of the main thromboembolic prevention treatments (i.e. anticoagulants and LAA excluder and occluding devices), allowing the evaluation of anatomy-treatment interaction and fluid-dynamic conditions.
4. Validate the computational models with retrospective clinical data.

3) Novelty of Research Methodology

Development of a validated FSI computational framework, here specifically applied to AF patients, to select the most suitable therapeutic strategy to prevent thromboembolic events among those currently available: anticoagulation drugs, surgical/percutaneous occlusion of the LAA.

4) Alignment to EPSRC's strategies and research areas

The project aims at developing a novel computational framework to support therapeutic-planning in the selection of the optimal thromboembolic prevention treatment for AF patients. This will be based on fluid dynamic parameters impossible to measure in-vivo, and will require the synergy between recent developments in medical imaging and computational engineering. It aligns ideally with the EPSRC's strategic priorities of patient-specific illness prediction, accurate diagnosis, and also transforming health and healthcare.

5) Any companies or collaborators involved

Professor Pier Lambiase, Co-Director of Cardiovascular Research Barts NHS Trust/UCL Institute of Cardiovascular Science (ICS)
Dr Oliver Segal from Cardiac Units at UCLH and the Barts Health NHS Trust
Dr Claire Martin

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.