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Subject Specific Modelling of Aortic Flows

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Applied Complex Flow

Part of the book series: Emerging Trends in Mechatronics ((emerg. Trends in Mechatronics))

Abstract

Cardiovascular diseases (CVDs) are the principal cause of morbidity worldwide. According to the World Health Organisation (WHO), around 17.9 million deaths were reported in 2016 due to CVDs, representing 31% of the global death, while this number is expected to reach over 23.6 million by 2030. Arterial disease, stroke, transient ischaemic attack, and rheumatic heart disease are the most prevalent CVDs. British Heart Foundation (BHF) has reported that around 7.4 million people in the UK are living with CVDs, which imposes a £9 billion annual cost on the healthcare system. In recent years, advances in vascular biology, biomechanics, medical imaging, and computational techniques including Computational Fluid Dynamics (CFD) have provided the research community with a unique opportunity to simulate and analyse blood flow from a new angle and to develop new strategies for intervention. The increasing power-to-cost ratio of computers and the advent of methods for subject-specific modelling of cardiovascular flow have made CFD-based modelling sometimes even more reliable than methods based solely on in-vivo or in-vitro measurement. This chapter explains a workflow for subject-specific modelling of blood flow in the aorta as an exemplar of digitalisation in healthcare. The workflow comprises multi-modal clinical images, a multiscale numerical pipeline, and haemodynamic metrics. Subject-specific modelling primarily relies on clinical data, which is reachable through different clinical imaging modalities to get the anatomy and flow data of the Region of Interest (ROI). At the next stage, the computational pipeline should be set through appropriate boundary conditions. The latter requires a multiscale approach to couple the three-dimensional CFD model to zero/one-dimensional circuits. These circuits normally mimic upstream and downstream regions, which are not included in the three-dimensional CFD domain, however, they affect crucially and are to be considered for an accurate personalised medicine. Once the pipeline has been set, it can suggest complex blood flow behaviour because of different pathological conditions that might emerge throughout the vascular network. At this stage invoking accurate and reliable haemodynamic metrics can translate the simulated data into interpretable clinical output, which is the main goal of the workflow.

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  1. Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), Department of Medical Physics and Biomedical Engineering, University College London, 43-45 Foley Street, London, W1W 7TS, UK

    Amin Deyranlou

  2. Department of Mechanical, Aerospace and Civil Engineering (MACE), The University of Manchester, Manchester, M13 9PL, UK

    Amin Deyranlou, Alistair Revell & Amir Keshmiri

  3. Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Southmoor Road, Wythenshawe, Manchester, M13 9PL, UK

    Amir Keshmiri

Authors
  1. Amin Deyranlou
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  2. Alistair Revell
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  3. Amir Keshmiri
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Correspondence to Amin Deyranlou .

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  1. School of Engineering, Computing and Mathematics, Oxford Brookes University, Oxford, UK

    Aydin Azizi

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Deyranlou, A., Revell, A., Keshmiri, A. (2023). Subject Specific Modelling of Aortic Flows. In: Azizi, A. (eds) Applied Complex Flow. Emerging Trends in Mechatronics. Springer, Singapore. https://doi.org/10.1007/978-981-19-7746-6_4

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  • DOI: https://doi.org/10.1007/978-981-19-7746-6_4

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  • Print ISBN: 978-981-19-7745-9

  • Online ISBN: 978-981-19-7746-6

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